WMAP haze: Directly observing dark matter?
International Nuclear Information System (INIS)
Forbes, Michael McNeil; Zhitnitsky, Ariel R.
2008-01-01
In this paper, we show that dark matter in the form of dense matter/antimatter nuggets could provide a natural and unified explanation for several distinct bands of diffuse radiation from the core of the Galaxy spanning over 13 orders of magnitude in frequency. We fix all of the phenomenological properties of this model by matching to x-ray observations in the keV band, and then calculate the unambiguously predicted thermal emission in the microwave band, at frequencies smaller by 11 orders of magnitude. Remarkably, the intensity and spectrum of the emitted thermal radiation are consistent with - and could entirely explain - the so-called 'WMAP haze': a diffuse microwave excess observed from the core of our Galaxy by the Wilkinson Microwave Anisotropy Probe (WMAP). This provides another strong constraint of our proposal, and a remarkable nontrivial validation. If correct, our proposal identifies the nature of the dark matter, explains baryogenesis, and provides a means to directly probe the matter distribution in our Galaxy by analyzing several different types of diffuse emissions.
Weiland, J. L.; Odegard, N.; Hill, R. S.; Wollack, E.; Hinshaw, G.; Greason, M. R.; Jarosik, N.; Page, L.; Bennett, C. L.; Dunkley, J.; Gold, B.; Halpern, M.; Kogut, A.; Komatsu, E.; Larson, D.; Limon, M.; Meyer, S. S.; Nolta, M. R.; Smith, K. M.; Spergel, D. N.; Tucker, G. S.; Wright, E. L.
2011-02-01
We present WMAP seven-year observations of bright sources which are often used as calibrators at microwave frequencies. Ten objects are studied in five frequency bands (23-94 GHz): the outer planets (Mars, Jupiter, Saturn, Uranus, and Neptune) and five fixed celestial sources (Cas A, Tau A, Cyg A, 3C274, and 3C58). The seven-year analysis of Jupiter provides temperatures which are within 1σ of the previously published WMAP five-year values, with slightly tighter constraints on variability with orbital phase (0.2% ± 0.4%), and limits (but no detections) on linear polarization. Observed temperatures for both Mars and Saturn vary significantly with viewing geometry. Scaling factors are provided which, when multiplied by the Wright Mars thermal model predictions at 350 μm, reproduce WMAP seasonally averaged observations of Mars within ~2%. An empirical model is described which fits brightness variations of Saturn due to geometrical effects and can be used to predict the WMAP observations to within 3%. Seven-year mean temperatures for Uranus and Neptune are also tabulated. Uncertainties in Uranus temperatures are 3%-4% in the 41, 61, and 94 GHz bands; the smallest uncertainty for Neptune is 8% for the 94 GHz band. Intriguingly, the spectrum of Uranus appears to show a dip at ~30 GHz of unidentified origin, although the feature is not of high statistical significance. Flux densities for the five selected fixed celestial sources are derived from the seven-year WMAP sky maps and are tabulated for Stokes I, Q, and U, along with polarization fraction and position angle. Fractional uncertainties for the Stokes I fluxes are typically 1% to 3%. Source variability over the seven-year baseline is also estimated. Significant secular decrease is seen for Cas A and Tau A: our results are consistent with a frequency-independent decrease of about 0.53% per year for Cas A and 0.22% per year for Tau A. We present WMAP polarization data with uncertainties of a few percent for Tau A
International Nuclear Information System (INIS)
Weiland, J. L.; Odegard, N.; Hill, R. S.; Greason, M. R.; Wollack, E.; Hinshaw, G.; Kogut, A.; Jarosik, N.; Page, L.; Bennett, C. L.; Gold, B.; Larson, D.; Dunkley, J.; Halpern, M.; Komatsu, E.; Limon, M.; Meyer, S. S.; Nolta, M. R.; Smith, K. M.; Spergel, D. N.
2011-01-01
We present WMAP seven-year observations of bright sources which are often used as calibrators at microwave frequencies. Ten objects are studied in five frequency bands (23-94 GHz): the outer planets (Mars, Jupiter, Saturn, Uranus, and Neptune) and five fixed celestial sources (Cas A, Tau A, Cyg A, 3C274, and 3C58). The seven-year analysis of Jupiter provides temperatures which are within 1σ of the previously published WMAP five-year values, with slightly tighter constraints on variability with orbital phase (0.2% ± 0.4%), and limits (but no detections) on linear polarization. Observed temperatures for both Mars and Saturn vary significantly with viewing geometry. Scaling factors are provided which, when multiplied by the Wright Mars thermal model predictions at 350 μm, reproduce WMAP seasonally averaged observations of Mars within ∼2%. An empirical model is described which fits brightness variations of Saturn due to geometrical effects and can be used to predict the WMAP observations to within 3%. Seven-year mean temperatures for Uranus and Neptune are also tabulated. Uncertainties in Uranus temperatures are 3%-4% in the 41, 61, and 94 GHz bands; the smallest uncertainty for Neptune is 8% for the 94 GHz band. Intriguingly, the spectrum of Uranus appears to show a dip at ∼30 GHz of unidentified origin, although the feature is not of high statistical significance. Flux densities for the five selected fixed celestial sources are derived from the seven-year WMAP sky maps and are tabulated for Stokes I, Q, and U, along with polarization fraction and position angle. Fractional uncertainties for the Stokes I fluxes are typically 1% to 3%. Source variability over the seven-year baseline is also estimated. Significant secular decrease is seen for Cas A and Tau A: our results are consistent with a frequency-independent decrease of about 0.53% per year for Cas A and 0.22% per year for Tau A. We present WMAP polarization data with uncertainties of a few percent for Tau
Page, L.; Barnes, C.; Hinshaw, G.; Spergel, D. N.; Weiland, J. L.; Wollack, E.; Bennett, C. L.; Halpern, M.; Jarosik, N.; Kogut, A.; Limon, M.; Meyer, S. S.; Tucker, G. S.; Wright, E. L.
2003-09-01
Knowledge of the beam profiles is of critical importance for interpreting data from cosmic microwave background experiments. In this paper, we present the characterization of the in-flight optical response of the WMAP satellite. The main-beam intensities have been mapped to the satellite in the same observing mode as for CMB observations. The beam patterns closely follow the prelaunch expectations. The full width at half-maximum is a function of frequency and ranges from 0.82d at 23 GHz to 0.21d at 94 GHz; however, the beams are not Gaussian. We present (a) the beam patterns for all 10 differential radiometers, showing that the patterns are substantially independent of polarization in all but the 23 GHz channel; (b) the effective symmetrized beam patterns that result from WMAP's compound spin observing pattern; (c) the effective window functions for all radiometers and the formalism for propagating the window function uncertainty; and (d) the conversion factor from point-source flux to antenna temperature. A summary of the systematic uncertainties, which currently dominate our knowledge of the beams, is also presented. The constancy of Jupiter's temperature within a frequency band is an essential check of the optical system. The tests enable us to report a calibration of Jupiter to 1%-3% accuracy relative to the CMB dipole. WMAP is the result of a partnership between Princeton University and the NASA Goddard Space Flight Center. Scientific guidance is provided by the WMAP Science Team.
NINE-YEAR WILKINSON MICROWAVE ANISOTROPY PROBE (WMAP) OBSERVATIONS: FINAL MAPS AND RESULTS
Energy Technology Data Exchange (ETDEWEB)
Bennett, C. L.; Larson, D.; Weiland, J. L. [Department of Physics and Astronomy, The Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218-2686 (United States); Jarosik, N.; Page, L. [Department of Physics, Jadwin Hall, Princeton University, Princeton, NJ 08544-0708 (United States); Hinshaw, G.; Halpern, M. [Department of Physics and Astronomy, University of British Columbia, Vancouver, BC V6T 1Z1 (Canada); Odegard, N.; Hill, R. S. [ADNET Systems, Inc., 7515 Mission Drive, Suite A100, Lanham, MD 20706 (United States); Smith, K. M. [Perimeter Institute for Theoretical Physics, Waterloo, ON N2L 2Y5 (Canada); Gold, B. [School of Physics and Astronomy, University of Minnesota, 116 Church Street S.E., Minneapolis, MN 55455 (United States); Komatsu, E. [Max-Planck-Institut für Astrophysik, Karl-Schwarzschild Str. 1, D-85741 Garching (Germany); Nolta, M. R. [Canadian Institute for Theoretical Astrophysics, 60 St. George Street, University of Toronto, Toronto, ON M5S 3H8 (Canada); Spergel, D. N. [Department of Astrophysical Sciences, Peyton Hall, Princeton University, Princeton, NJ 08544-1001 (United States); Wollack, E.; Kogut, A. [Code 665, NASA/Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Dunkley, J. [Oxford Astrophysics, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH (United Kingdom); Limon, M. [Columbia Astrophysics Laboratory, 550 West 120th Street, Mail Code 5247, New York, NY 10027-6902 (United States); Meyer, S. S. [Departments of Astrophysics and Physics, KICP and EFI, University of Chicago, Chicago, IL 60637 (United States); Tucker, G. S., E-mail: cbennett@jhu.edu [Department of Physics, Brown University, 182 Hope Street, Providence, RI 02912-1843 (United States); and others
2013-10-01
of 68,000 for the standard six-parameter ΛCDM model, based on CMB data alone. For a model including tensors, the allowed seven-parameter volume has been reduced by a factor 117,000. Other cosmological observations are in accord with the CMB predictions, and the combined data reduces the cosmological parameter volume even further. With no significant anomalies and an adequate goodness of fit, the inflationary flat ΛCDM model and its precise and accurate parameters rooted in WMAP data stands as the standard model of cosmology.
NINE-YEAR WILKINSON MICROWAVE ANISOTROPY PROBE (WMAP) OBSERVATIONS: FINAL MAPS AND RESULTS
International Nuclear Information System (INIS)
Bennett, C. L.; Larson, D.; Weiland, J. L.; Jarosik, N.; Page, L.; Hinshaw, G.; Halpern, M.; Odegard, N.; Hill, R. S.; Smith, K. M.; Gold, B.; Komatsu, E.; Nolta, M. R.; Spergel, D. N.; Wollack, E.; Kogut, A.; Dunkley, J.; Limon, M.; Meyer, S. S.; Tucker, G. S.
2013-01-01
, based on CMB data alone. For a model including tensors, the allowed seven-parameter volume has been reduced by a factor 117,000. Other cosmological observations are in accord with the CMB predictions, and the combined data reduces the cosmological parameter volume even further. With no significant anomalies and an adequate goodness of fit, the inflationary flat ΛCDM model and its precise and accurate parameters rooted in WMAP data stands as the standard model of cosmology
Nine-Year Wilkinson Microwave Anisotropy Probe (WMAP) Observations: Final Maps and Results
Bennett, C. L.; Larson, D.; Weiland, J. L.; Jaorsik, N.; Hinshaw, G.; Odegard, N.; Smith, K. M.; Hill, R. S.; Gold, B.; Halpern, M;
2013-01-01
-parameter ?Lambda-CDM model, based on CMB data alone. For a model including tensors, the allowed seven-parameter volume has been reduced by a factor 117,000. Other cosmological observations are in accord with the CMB predictions, and the combined data reduces the cosmological parameter volume even further.With no significant anomalies and an adequate goodness of fit, the inflationary flat Lambda-CDM model and its precise and accurate parameters rooted in WMAP data stands as the standard model of cosmology.
Intermediate inflation in light of the three-year WMAP observations
International Nuclear Information System (INIS)
Barrow, John D.; Liddle, Andrew R.; Pahud, Cedric
2006-01-01
The three-year observations from the Wilkinson Microwave Anisotropy Probe have been hailed as giving the first clear indication of a spectral index n s s =1 and allowing the tensor-to-scalar ratio r to be nonzero. The combination n s =1 and r>0 is given (within the slow-roll approximation) by a version of the intermediate inflation model with expansion rate H(t)∝t -1/3 . We assess the status of this model in light of the WMAP3 data
Energy Technology Data Exchange (ETDEWEB)
Verschuur, G. L.; Schmelz, J. T., E-mail: gverschu@naic.edu [Arecibo Observatory, HC-3 Box 53995, Arecibo PR 00612 (Puerto Rico)
2016-12-01
Small-scale features observed by Wilkinson Microwave Anisotropy Probe ( WMAP ) and PLANCK in the frequency range of 22–90 GHz show a nearly flat spectrum, which meets with expectations that they originate in the early universe. However, free–free emission from electrons in small angular scale galactic sources that suffer beam dilution very closely mimic the observed spectrum in this frequency range. Fitting such a model to the PLANCK and WMAP data shows that the angular size required to fit the data is comparable to the angular width of associated H i filaments found in the Galactic Arecibo L-Band Feed Array-H isurvey data. Also, the temperature of the electrons is found to be in the range of 100–300 K. The phenomenon revealed by these data may contribute to a more precise characterization of the foreground masks required to interpret the cosmological aspect of PLANCK and WMAP data.
Barnes, C.; Hill, R. S.; Hinshaw, G.; Page, L.; Bennett, C. L.; Halpern, M.; Jarosik, N.; Kogut, A.; Limon, M.; Meyer, S. S.; Tucker, G. S.; Wollack, E.; Wright, E. L.
2003-09-01
Since the Galactic center is ~1000 times brighter than fluctuations in the cosmic microwave background (CMB), CMB experiments must carefully account for stray Galactic pickup. We present the level of contamination due to sidelobes for the first-year CMB maps produced by the Wilkinson Microwave Anisotropy Probe (WMAP) observatory. For each radiometer, full 4π sr antenna gain patterns are determined from a combination of numerical prediction and ground-based and space-based measurements. These patterns are convolved with the WMAP first-year sky maps and observatory scan pattern to generate the expected sidelobe signal contamination, for both intensity and polarized microwave sky maps. When the main beams are outside of the Galactic plane, we find rms values for the expected sidelobe pickup of 15, 2.1, 2.0, 0.3, and 0.5 μK for the K, Ka, Q, V, and W bands, respectively. Except for at the K band, the rms polarized contamination is the Galactic pickup are presented. WMAP is the result of a partnership between Princeton University and the NASA Goddard Space Flight Center. Scientific guidance is provided by the WMAP Science Team.
Fermi LAT and WMAP observations of the supernova remnant HB 21
Energy Technology Data Exchange (ETDEWEB)
Pivato, G. [Dipartimento di Fisica e Astronomia " G. Galilei," Università di Padova, I-35131 Padova (Italy); Hewitt, J. W. [CRESST, University of Maryland, Baltimore County, Baltimore, MD 21250 (United States); Tibaldo, L. [W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305 (United States); Acero, F.; Brandt, T. J. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Ballet, J. [Laboratoire AIM, CEA-IRFU/CNRS/Université Paris Diderot, Service d' Astrophysique, CEA Saclay, F-91191 Gif sur Yvette (France); De Palma, F.; Giordano, F. [Dipartimento di Fisica " M. Merlin" dell' Università e del Politecnico di Bari, I-70126 Bari (Italy); Janssen, G. H. [University of Manchester, Manchester, M13 9PL (United Kingdom); Jóhannesson, G. [Science Institute, University of Iceland, IS-107 Reykjavik (Iceland); Smith, D. A., E-mail: giovanna.pivato@pd.infn.it, E-mail: john.w.hewitt@nasa.gov, E-mail: ltibaldo@slac.stanford.edu [Centre d' Études Nucléaires de Bordeaux Gradignan, IN2P3/CNRS, Université Bordeaux 1, BP120, F-33175 Gradignan Cedex (France)
2013-12-20
We present the analysis of Fermi Large Area Telescope γ-ray observations of HB 21 (G89.0+4.7). We detect significant γ-ray emission associated with the remnant: the flux >100 MeV is 9.4 ± 0.8 (stat) ± 1.6 (syst) × 10{sup –11} erg cm{sup –2} s{sup –1}. HB 21 is well modeled by a uniform disk centered at l = 88.°75 ± 0.°04, b = +4.°65 ± 0.°06 with a radius of 1.°19 ± 0.°06. The γ-ray spectrum shows clear evidence of curvature, suggesting a cutoff or break in the underlying particle population at an energy of a few GeV. We complement γ-ray observations with the analysis of the WMAP 7 yr data from 23 to 93 GHz, achieving the first detection of HB 21 at these frequencies. In combination with archival radio data, the radio spectrum shows a spectral break, which helps to constrain the relativistic electron spectrum, and, in turn, parameters of simple non-thermal radiation models. In one-zone models multiwavelength data favor the origin of γ rays from nucleon-nucleon collisions. A single population of electrons cannot produce both γ rays through bremsstrahlung and radio emission through synchrotron radiation. A predominantly inverse-Compton origin of the γ-ray emission is disfavored because it requires lower interstellar densities than are inferred for HB 21. In the hadronic-dominated scenarios, accelerated nuclei contribute a total energy of ∼3 × 10{sup 49} erg, while, in a two-zone bremsstrahlung-dominated scenario, the total energy in accelerated particles is ∼1 × 10{sup 49} erg.
NINE-YEAR WILKINSON MICROWAVE ANISOTROPY PROBE (WMAP) OBSERVATIONS: COSMOLOGICAL PARAMETER RESULTS
International Nuclear Information System (INIS)
Hinshaw, G.; Halpern, M.; Larson, D.; Bennett, C. L.; Weiland, J. L.; Komatsu, E.; Spergel, D. N.; Dunkley, J.; Nolta, M. R.; Hill, R. S.; Odegard, N.; Page, L.; Jarosik, N.; Smith, K. M.; Gold, B.; Kogut, A.; Wollack, E.; Limon, M.; Meyer, S. S.; Tucker, G. S.
2013-01-01
We present cosmological parameter constraints based on the final nine-year Wilkinson Microwave Anisotropy Probe (WMAP) data, in conjunction with a number of additional cosmological data sets. The WMAP data alone, and in combination, continue to be remarkably well fit by a six-parameter ΛCDM model. When WMAP data are combined with measurements of the high-l cosmic microwave background anisotropy, the baryon acoustic oscillation scale, and the Hubble constant, the matter and energy densities, Ω b h 2 , Ω c h 2 , and Ω Λ , are each determined to a precision of ∼1.5%. The amplitude of the primordial spectrum is measured to within 3%, and there is now evidence for a tilt in the primordial spectrum at the 5σ level, confirming the first detection of tilt based on the five-year WMAP data. At the end of the WMAP mission, the nine-year data decrease the allowable volume of the six-dimensional ΛCDM parameter space by a factor of 68,000 relative to pre-WMAP measurements. We investigate a number of data combinations and show that their ΛCDM parameter fits are consistent. New limits on deviations from the six-parameter model are presented, for example: the fractional contribution of tensor modes is limited to r k = -0.0027 +0.0039 -0.0038 ; the summed mass of neutrinos is limited to Σm ν eff = 3.84 ± 0.40, when the full data are analyzed. The joint constraint on N eff and the primordial helium abundance, Y He , agrees with the prediction of standard big bang nucleosynthesis. We compare recent Planck measurements of the Sunyaev-Zel'dovich effect with our seven-year measurements, and show their mutual agreement. Our analysis of the polarization pattern around temperature extrema is updated. This confirms a fundamental prediction of the standard cosmological model and provides a striking illustration of acoustic oscillations and adiabatic initial conditions in the early universe
Unbinned likelihood analysis of EGRET observations
International Nuclear Information System (INIS)
Digel, Seth W.
2000-01-01
We present a newly-developed likelihood analysis method for EGRET data that defines the likelihood function without binning the photon data or averaging the instrumental response functions. The standard likelihood analysis applied to EGRET data requires the photons to be binned spatially and in energy, and the point-spread functions to be averaged over energy and inclination angle. The full-width half maximum of the point-spread function increases by about 40% from on-axis to 30 degree sign inclination, and depending on the binning in energy can vary by more than that in a single energy bin. The new unbinned method avoids the loss of information that binning and averaging cause and can properly analyze regions where EGRET viewing periods overlap and photons with different inclination angles would otherwise be combined in the same bin. In the poster, we describe the unbinned analysis method and compare its sensitivity with binned analysis for detecting point sources in EGRET data
Testing the dark matter origin of the WMAP-Planck haze with radio observations of spiral galaxies
Energy Technology Data Exchange (ETDEWEB)
Carlson, Eric; Linden, Tim; Profumo, Stefano [Department of Physics, University of California, Santa Cruz, 1156 High Street, Santa Cruz, CA, 95064 (United States); Hooper, Dan, E-mail: erccarls@ucsc.edu, E-mail: dhooper@fnal.gov, E-mail: tlinden@ucsc.edu, E-mail: profumo@ucsc.edu [Center for Particle Astrophysics, Fermi National Accelerator Laboratory, Batavia, IL 60510 (United States)
2013-07-01
If the Galactic WMAP radio haze, as recently confirmed by Planck, is produced by dark matter annihilation or decay, similar diffuse radio halos should exist around other galaxies with physical properties comparable to the Milky Way. If instead the haze is due to an astrophysical mechanism peculiar to the Milky Way or to a transient event, a similar halo need not exist around all Milky Way ''twins''. We use radio observations of 66 spiral galaxies to test the dark matter origin of the haze. We select galaxies based on morphological type and maximal rotational velocity, and obtain their luminosities from a 1.49 GHz catalog and additional radio observations at other frequencies. We find many instances of galaxies with radio emission that is less than 5% as bright as naively expected from dark matter models that could produce the Milky Way haze, and at least 3 galaxies that are less than 1% as bright as expected, assuming dark matter distributions, magnetic fields, and cosmic ray propagation parameters equal to those of the Milky Way. For reasonable ranges for the variation of these parameters, we estimate the fraction of galaxies that should be expected to be significantly less bright in radio, and argue that this is marginally compatible with the observed distribution. While our findings therefore cannot rule out a dark matter origin for the radio haze at this time, we find numerous examples (including the Andromeda Galaxy) where, if dark matter is indeed the origin of the Milky Way haze, some mechanism must be in place to suppress the corresponding haze of the external galaxy. We point out that Planck data will offer opportunities to improve this type of constraint in a highly relevant frequency range and for a potentially larger set of candidate galaxies.
Confronting quasi-exponential inflation with WMAP seven
International Nuclear Information System (INIS)
Pal, Barun Kumar; Pal, Supratik; Basu, B.
2012-01-01
We confront quasi-exponential models of inflation with WMAP seven years dataset using Hamilton Jacobi formalism. With a phenomenological Hubble parameter, representing quasi exponential inflation, we develop the formalism and subject the analysis to confrontation with WMAP seven using the publicly available code CAMB. The observable parameters are found to fair extremely well with WMAP seven. We also obtain a ratio of tensor to scalar amplitudes which may be detectable in PLANCK
Large-scale alignments from WMAP and Planck
Copi, Craig J.; Schwarz, Dominik J.; Starkman, Glenn D.
2015-01-01
We revisit the alignments of the largest structures observed in the cosmic microwave background (CMB) using the seven and nine-year WMAP and first-year Planck data releases. The observed alignments -- the quadrupole with the octopole and their joint alignment with the direction of our motion with respect to the CMB (the dipole direction) and the geometry of the Solar System (defined by the Ecliptic plane) -- are generally in good agreement with results from the previous WMAP data releases. However, a closer look at full-sky data on the largest scales reveals discrepancies between the earlier WMAP data releases (three to seven-year) and the final nine-year release. There are also discrepancies between all the WMAP data releases and the first-year Planck release. Nevertheless, both the WMAP and Planck data confirm the alignments of the largest observable CMB modes in the Universe. In particular, the p-values for the mutual alignment between the quadrupole and octopole, and the alignment of the plane defined by ...
Mildly mixed coupled models vs. WMAP7 data
International Nuclear Information System (INIS)
La Vacca, Giuseppe; Bonometto, Silvio A.
2011-01-01
Mildly mixed coupled models include massive ν's and CDM-DE coupling. We present new tests of their likelihood vs. recent data including WMAP7, confirming it to exceed ΛCDM, although at ∼2--σ's. We then show the impact on the physics of the dark components of ν-mass detection in 3 H β-decay or 0νββ-decay experiments.
Running-mass inflation model and WMAP
International Nuclear Information System (INIS)
Covi, Laura; Lyth, David H.; Melchiorri, Alessandro; Odman, Carolina J.
2004-01-01
We consider the observational constraints on the running-mass inflationary model, and, in particular, on the scale dependence of the spectral index, from the new cosmic microwave background (CMB) anisotropy measurements performed by WMAP and from new clustering data from the SLOAN survey. We find that the data strongly constraints a significant positive scale dependence of n, and we translate the analysis into bounds on the physical parameters of the inflaton potential. Looking deeper into specific types of interaction (gauge and Yukawa) we find that the parameter space is significantly constrained by the new data, but that the running-mass model remains viable
Likelihood based inference for partially observed renewal processes
van Lieshout, Maria Nicolette Margaretha
2016-01-01
This paper is concerned with inference for renewal processes on the real line that are observed in a broken interval. For such processes, the classic history-based approach cannot be used. Instead, we adapt tools from sequential spatial point process theory to propose a Monte Carlo maximum
COSMIC MICROWAVE BACKGROUND LIKELIHOOD APPROXIMATION BY A GAUSSIANIZED BLACKWELL-RAO ESTIMATOR
International Nuclear Information System (INIS)
Rudjord, Oe.; Groeneboom, N. E.; Eriksen, H. K.; Huey, Greg; Gorski, K. M.; Jewell, J. B.
2009-01-01
We introduce a new cosmic microwave background (CMB) temperature likelihood approximation called the Gaussianized Blackwell-Rao estimator. This estimator is derived by transforming the observed marginal power spectrum distributions obtained by the CMB Gibbs sampler into standard univariate Gaussians, and then approximating their joint transformed distribution by a multivariate Gaussian. The method is exact for full-sky coverage and uniform noise and an excellent approximation for sky cuts and scanning patterns relevant for modern satellite experiments such as the Wilkinson Microwave Anisotropy Probe (WMAP) and Planck. The result is a stable, accurate, and computationally very efficient CMB temperature likelihood representation that allows the user to exploit the unique error propagation capabilities of the Gibbs sampler to high ls. A single evaluation of this estimator between l = 2 and 200 takes ∼0.2 CPU milliseconds, while for comparison, a singe pixel space likelihood evaluation between l = 2 and 30 for a map with ∼2500 pixels requires ∼20 s. We apply this tool to the five-year WMAP temperature data, and re-estimate the angular temperature power spectrum, C l , and likelihood, L(C l ), for l ≤ 200, and derive new cosmological parameters for the standard six-parameter ΛCDM model. Our spectrum is in excellent agreement with the official WMAP spectrum, but we find slight differences in the derived cosmological parameters. Most importantly, the spectral index of scalar perturbations is n s = 0.973 ± 0.014, 1.9σ away from unity and 0.6σ higher than the official WMAP result, n s = 0.965 ± 0.014. This suggests that an exact likelihood treatment is required to higher ls than previously believed, reinforcing and extending our conclusions from the three-year WMAP analysis. In that case, we found that the suboptimal likelihood approximation adopted between l = 12 and 30 by the WMAP team biased n s low by 0.4σ, while here we find that the same approximation
The running-mass inflation model and WMAP
Covi, Laura; Lyth, David H.; Melchiorri, Alessandro; Odman, Carolina J.
2004-01-01
We consider the observational constraints on the running-mass inflationary model, and in particular on the scale-dependence of the spectral index, from the new Cosmic Microwave Background (CMB) anisotropy measurements performed by WMAP and from new clustering data from the SLOAN survey. We find that the data strongly constraints a significant positive scale-dependence of $n$, and we translate the analysis into bounds on the physical parameters of the inflaton potential. Looking deeper into sp...
Natural inflation: Status after WMAP 3-year data
International Nuclear Information System (INIS)
Savage, Christopher; Freese, Katherine; Kinney, William H.
2006-01-01
The model of natural inflation is examined in light of recent 3-year data from the Wilkinson Microwave Anisotropy Probe and shown to provide a good fit. The inflaton potential is naturally flat due to shift symmetries, and in the simplest version takes the form V(φ)=Λ 4 [1±cos(Nφ/f)]. The model agrees with WMAP3 measurements as long as f>0.7m Pl (where m Pl =1.22x10 19 GeV) and Λ∼m GUT . The running of the scalar spectral index is shown to be small--an order of magnitude below the sensitivity of WMAP3. The location of the field in the potential when perturbations on observable scales are produced is examined; for f>5m Pl , the relevant part of the potential is indistinguishable from a quadratic, yet has the advantage that the required flatness is well-motivated. Depending on the value of f, the model falls into the large field (f≥1.5m Pl ) or small field (f Pl ) classification scheme that has been applied to inflation models. Natural inflation provides a good fit to WMAP3 data
arXiv FlavBit: A GAMBIT module for computing flavour observables and likelihoods
Bernlochner, Florian U.; Dal, Lars A.; Farmer, Ben; Jackson, Paul; Kvellestad, Anders; Mahmoudi, Farvah; Putze, Antje; Rogan, Christopher; Scott, Pat; Serra, Nicola; Weniger, Christoph; White, Martin
2017-11-21
Flavour physics observables are excellent probes of new physics up to very high energy scales. Here we present FlavBit, the dedicated flavour physics module of the global-fitting package GAMBIT. FlavBit includes custom implementations of various likelihood routines for a wide range of flavour observables, including detailed uncertainties and correlations associated with LHCb measurements of rare, leptonic and semileptonic decays of B and D mesons, kaons and pions. It provides a generalised interface to external theory codes such as SuperIso, allowing users to calculate flavour observables in and beyond the Standard Model, and then test them in detail against all relevant experimental data. We describe FlavBit and its constituent physics in some detail, then give examples from supersymmetry and effective field theory illustrating how it can be used both as a standalone library for flavour physics, and within GAMBIT.
FlavBit. A GAMBIT module for computing flavour observables and likelihoods
Energy Technology Data Exchange (ETDEWEB)
Bernlochner, Florian U. [Physikalisches Institut der Rheinischen Friedrich-Wilhelms-Universitaet Bonn (Germany); Chrzaszcz, Marcin [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Polish Academy of Sciences, H. Niewodniczanski Institute of Nuclear Physics, Krakow (Poland); Dal, Lars A. [University of Oslo, Department of Physics, Oslo (Norway); Farmer, Ben [Oskar Klein Centre for Cosmoparticle Physics, AlbaNova University Centre, Stockholm (Sweden); Stockholm University, Department of Physics, Stockholm (Sweden); Jackson, Paul; White, Martin [University of Adelaide, Department of Physics, Adelaide, SA (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); Kvellestad, Anders [NORDITA, Stockholm (Sweden); Mahmoudi, Farvah [Univ Lyon, Univ Lyon 1, ENS de Lyon, CNRS, Centre de Recherche Astrophysique de Lyon UMR5574, Saint-Genis-Laval (France); CERN, Theoretical Physics Department, Geneva (Switzerland); Putze, Antje [LAPTh, Universite de Savoie, CNRS, Annecy-le-Vieux (France); Rogan, Christopher [Harvard University, Department of Physics, Cambridge, MA (United States); Scott, Pat [Imperial College London, Department of Physics, Blackett Laboratory, London (United Kingdom); Serra, Nicola [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Weniger, Christoph [University of Amsterdam, GRAPPA, Institute of Physics, Amsterdam (Netherlands); Collaboration: The GAMBIT Flavour Workgroup
2017-11-15
Flavour physics observables are excellent probes of new physics up to very high energy scales. Here we present FlavBit, the dedicated flavour physics module of the global-fitting package GAMBIT. FlavBit includes custom implementations of various likelihood routines for a wide range of flavour observables, including detailed uncertainties and correlations associated with LHCb measurements of rare, leptonic and semileptonic decays of B and D mesons, kaons and pions. It provides a generalised interface to external theory codes such as SuperIso, allowing users to calculate flavour observables in and beyond the Standard Model, and then test them in detail against all relevant experimental data. We describe FlavBit and its constituent physics in some detail, then give examples from supersymmetry and effective field theory illustrating how it can be used both as a standalone library for flavour physics, and within GAMBIT. (orig.)
Directory of Open Access Journals (Sweden)
Chang-bae Moon
2011-01-01
Full Text Available Although there have been many researches on mobile robot localization, it is still difficult to obtain reliable localization performance in a human co-existing real environment. Reliability of localization is highly dependent upon developer's experiences because uncertainty is caused by a variety of reasons. We have developed a range sensor based integrated localization scheme for various indoor service robots. Through the experience, we found out that there are several significant experimental issues. In this paper, we provide useful solutions for following questions which are frequently faced with in practical applications: 1 How to design an observation likelihood model? 2 How to detect the localization failure? 3 How to recover from the localization failure? We present design guidelines of observation likelihood model. Localization failure detection and recovery schemes are presented by focusing on abrupt wheel slippage. Experiments were carried out in a typical office building environment. The proposed scheme to identify the localizer status is useful in practical environments. Moreover, the semi-global localization is a computationally efficient recovery scheme from localization failure. The results of experiments and analysis clearly present the usefulness of proposed solutions.
Directory of Open Access Journals (Sweden)
Chang-bae Moon
2010-12-01
Full Text Available Although there have been many researches on mobile robot localization, it is still difficult to obtain reliable localization performance in a human co-existing real environment. Reliability of localization is highly dependent upon developer's experiences because uncertainty is caused by a variety of reasons. We have developed a range sensor based integrated localization scheme for various indoor service robots. Through the experience, we found out that there are several significant experimental issues. In this paper, we provide useful solutions for following questions which are frequently faced with in practical applications: 1 How to design an observation likelihood model? 2 How to detect the localization failure? 3 How to recover from the localization failure? We present design guidelines of observation likelihood model. Localization failure detection and recovery schemes are presented by focusing on abrupt wheel slippage. Experiments were carried out in a typical office building environment. The proposed scheme to identify the localizer status is useful in practical environments. Moreover, the semi-global localization is a computationally efficient recovery scheme from localization failure. The results of experiments and analysis clearly present the usefulness of proposed solutions.
DarkBit. A GAMBIT module for computing dark matter observables and likelihoods
Energy Technology Data Exchange (ETDEWEB)
Bringmann, Torsten; Dal, Lars A. [University of Oslo, Department of Physics, Oslo (Norway); Conrad, Jan; Edsjoe, Joakim; Farmer, Ben [AlbaNova University Centre, Oskar Klein Centre for Cosmoparticle Physics, Stockholm (Sweden); Stockholm University, Department of Physics, Stockholm (Sweden); Cornell, Jonathan M. [McGill University, Department of Physics, Montreal, QC (Canada); Kahlhoefer, Felix; Wild, Sebastian [DESY, Hamburg (Germany); Kvellestad, Anders; Savage, Christopher [NORDITA, Stockholm (Sweden); Putze, Antje [LAPTh, Universite de Savoie, CNRS, Annecy-le-Vieux (France); Scott, Pat [Blackett Laboratory, Imperial College London, Department of Physics, London (United Kingdom); Weniger, Christoph [University of Amsterdam, GRAPPA, Institute of Physics, Amsterdam (Netherlands); White, Martin [University of Adelaide, Department of Physics, Adelaide, SA (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale, Parkville (Australia); Collaboration: The GAMBIT Dark Matter Workgroup
2017-12-15
We introduce DarkBit, an advanced software code for computing dark matter constraints on various extensions to the Standard Model of particle physics, comprising both new native code and interfaces to external packages. This release includes a dedicated signal yield calculator for gamma-ray observations, which significantly extends current tools by implementing a cascade-decay Monte Carlo, as well as a dedicated likelihood calculator for current and future experiments (gamLike). This provides a general solution for studying complex particle physics models that predict dark matter annihilation to a multitude of final states. We also supply a direct detection package that models a large range of direct detection experiments (DDCalc), and that provides the corresponding likelihoods for arbitrary combinations of spin-independent and spin-dependent scattering processes. Finally, we provide custom relic density routines along with interfaces to DarkSUSY, micrOMEGAs, and the neutrino telescope likelihood package nulike. DarkBit is written in the framework of the Global And Modular Beyond the Standard Model Inference Tool (GAMBIT), providing seamless integration into a comprehensive statistical fitting framework that allows users to explore new models with both particle and astrophysics constraints, and a consistent treatment of systematic uncertainties. In this paper we describe its main functionality, provide a guide to getting started quickly, and show illustrative examples for results obtained with DarkBit (both as a stand-alone tool and as a GAMBIT module). This includes a quantitative comparison between two of the main dark matter codes (DarkSUSY and micrOMEGAs), and application of DarkBit's advanced direct and indirect detection routines to a simple effective dark matter model. (orig.)
Maximum-likelihood estimation of the hyperbolic parameters from grouped observations
DEFF Research Database (Denmark)
Jensen, Jens Ledet
1988-01-01
a least-squares problem. The second procedure Hypesti first approaches the maximum-likelihood estimate by iterating in the profile-log likelihood function for the scale parameter. Close to the maximum of the likelihood function, the estimation is brought to an end by iteration, using all four parameters...
WMAP constraints on k-inflation
International Nuclear Information System (INIS)
Devi, N. Chandrachani; Sen, Anjan A.; Nautiyal, Akhilesh
2011-01-01
We study the k-inflation models where the inflaton field has a noncanonical kinetic term. In particular, we consider the Dirac-Born-Infeld (DBI) form for the kinetic energy of the inflaton field. We consider quadratic and quartic potentials as well as the potential for the natural inflation. We use a modified version of MODECODE[M. J. Mortonson, H. V. Peiris, and R. Easther, Phys. Rev. D 83, 043505 (2011).] to calculate the power spectrum of the primordial perturbations generated by the inflaton field and subsequently use the WMAP7 results to constrain the models. Interestingly, with the DBI type kinetic term, less gravity waves are produced as one approaches scale invariance. This is true for all the potentials considered. Unlike the canonical case, this feature, in particular, helps the quartic (λφ 4 ) potential with the DBI type kinetic term to be consistent with the WMAP data.
WMAP five-year constraints on lepton asymmetry and radiation energy density: implications for Planck
International Nuclear Information System (INIS)
Popa, L A; Vasile, A
2008-01-01
In this paper we set bounds on the radiation content of the Universe and neutrino properties by using the WMAP (Wilkinson microwave anisotropy probe) five-year CMB (cosmic microwave background) measurements complemented with most of the existing CMB and LSS (large scale structure) data (WMAP5+All), imposing also self-consistent BBN (big bang nucleosynthesis) constraints on the primordial helium abundance. We consider lepton asymmetric cosmological models parametrized by the neutrino degeneracy parameter ξ ν and the variation of the relativistic degrees of freedom, ΔN eff oth , due to possible other physical processes occurring between BBN and structure formation epochs. We get a mean value of the effective number of relativistic neutrino species of N eff = 2.98 2.27 3.60 1.65 4.37 , providing an important improvement over the similar result obtained from WMAP5+BAO+SN+HST (BAO: baryonic acoustic oscillations; SN: supernovae; HST: Hubble Space Telescope) data (Komatsu et al (WMAP Collaboration), 2008 Astrophys. J. Suppl. submitted [0803.0547]). We also find a strong correlation between Ω m h 2 and z eq , showing that we observe N eff mainly via the effect of z eq , rather than via neutrino anisotropic stress as claimed by the WMAP team (Komatsu et al (WMAP Collaboration), 2008 Astrophys. J. Suppl. submitted [0803.0547]). WMAP5+All data provide a strong bound on the helium mass fraction of Y p = 0.2486 ± 0.0085 (68% CL), that rivals the bound on Y p obtained from the conservative analysis of the present data on helium abundance. For the neutrino degeneracy parameter we find a bound of −0.216≤ξ ν ≤0.226 (68% CL), which represents an important improvement over the similar result obtained by using the WMAP three-year data. The inclusion in the analysis of LSS data reduces the upper limit of the neutrino mass to m ν ν and Y p down to σ(ξ ν )≅0.089 (68% CL) and σ(Y p ) = 0.013 (68% CL) respectively, values fully consistent with the BBN bounds on
WMAP - A Glimpse of the Early Universe
Wollack, Edward
2009-01-01
The early Universe was incredibly hot, dense, and homogeneous. A powerful probe of this time is provided by the relic radiation which we refer to today as the Cosmic Microwave Background (CMB). Images produced from this light contain the earliest glimpse of the Universe after the "Big Bang" and the signature of the evolution of its contents. By exploiting these clues, precise constraints on the age, mass density, and geometry of the early Universe can be derived. The history of this intriguing cosmological detective story will be reviewed. Recent results from NASA's Wilkinson Microwave Anisotropy Probe (WMAP) will be presented.
Prochaska, Judith J; Michalek, Anne K; Brown-Johnson, Catherine; Daza, Eric J; Baiocchi, Michael; Anzai, Nicole; Rogers, Amy; Grigg, Mia; Chieng, Amy
2016-05-01
, stable housing, reliable transportation, criminal history, and prior treatment for alcohol or drug use (25.3% of observations trimmed) reduced the difference in employment attributed to smoking status to 24% (95% CI, 7%-39%), which was still a significant difference. Among those reemployed at 1 year, the average hourly wage for smokers was significantly lower (mean [SD], $15.10 [$4.68]) than for nonsmokers (mean [SD], $20.27 [$10.54]; F(1,86) = 6.50, P = .01). To our knowledge, this is the first study to prospectively track reemployment success by smoking status. Smokers had a lower likelihood of reemployment at 1 year and were paid significantly less than nonsmokers when reemployed. Treatment of tobacco use in unemployment service settings is worth testing for increasing reemployment success and financial well-being.
Cosmological parameters from SDSS and WMAP
International Nuclear Information System (INIS)
Tegmark, Max; Strauss, Michael A.; Bahcall, Neta A.; Schlegel, David; Finkbeiner, Douglas; Gunn, James E.; Ostriker, Jeremiah P.; Seljak, Uros; Ivezic, Zeljko; Knapp, Gillian R.; Lupton, Robert H.; Blanton, Michael R.; Scoccimarro, Roman; Hogg, David W.; Abazajian, Kevork; Xu Yongzhong; Dodelson, Scott; Sandvik, Havard; Wang Xiaomin; Jain, Bhuvnesh
2004-01-01
We measure cosmological parameters using the three-dimensional power spectrum P(k) from over 200 000 galaxies in the Sloan Digital Sky Survey (SDSS) in combination with Wilkinson Microwave Anisotropy Probe (WMAP) and other data. Our results are consistent with a 'vanilla' flat adiabatic cold dark matter model with a cosmological constant without tilt (n s =1), running tilt, tensor modes, or massive neutrinos. Adding SDSS information more than halves the WMAP-only error bars on some parameters, tightening 1σ constraints on the Hubble parameter from h≅0.74 -0.07 +0.18 to h≅0.70 -0.03 +0.04 , on the matter density from Ω m ≅0.25±0.10 to Ω m ≅0.30±0.04 (1σ) and on neutrino masses from 0 ≅16.3 -1.8 +2.3 Gyr to t 0 ≅14.1 -0.9 +1.0 Gyr by adding SDSS and SN Ia data. Including tensors, running tilt, neutrino mass and equation of state in the list of free parameters, many constraints are still quite weak, but future cosmological measurements from SDSS and other sources should allow these to be substantially tightened
Dark matter implications of the WMAP-Planck Haze
International Nuclear Information System (INIS)
Egorov, Andrey E.; Pierpaoli, Elena; Gaskins, Jennifer M.; Pietrobon, Davide
2016-01-01
Gamma rays and microwave observations of the Galactic Center and surrounding areas indicate the presence of anomalous emission, whose origin remains ambiguous. The possibility of dark matter annihilation explaining both signals through prompt emission at gamma rays and secondary emission at microwave frequencies from interactions of high-energy electrons produced in annihilation with the Galactic magnetic fields has attracted much interest in recent years. We investigate the dark matter interpretation of the Galactic Center gamma-ray excess by searching for the associated synchrotron emission in the WMAP and Planck microwave data. Considering various magnetic field and cosmic-ray propagation models, we predict the synchrotron emission due to dark matter annihilation in our Galaxy, and compare it with the WMAP and Planck data at 23–70 GHz. In addition to standard microwave foregrounds, we separately model the microwave counterpart to the Fermi Bubbles and the signal due to dark matter annihilation, and use component separation techniques to extract the signal associated with each template from the total emission. We confirm the presence of the Haze at the level of ≈7% of the total sky intensity at 23 GHz in our chosen region of interest, with a harder spectrum (I ∼ ν −0.8 ) than the synchrotron from regular cosmic-ray electrons. The data do not show a strong preference towards fitting the Haze by either the Bubbles or dark matter emission only. Inclusion of both components provides a better fit with a dark matter contribution to the Haze emission of ≈20% at 23 GHz, however, due to significant uncertainties in foreground modeling, we do not consider this a clear detection of a dark matter signal. We set robust upper limits on the annihilation cross section by ignoring foregrounds, and also report best-fit dark matter annihilation parameters obtained from a complete template analysis. We conclude that the WMAP and Planck data are consistent with a dark
Dark matter implications of the WMAP-Planck Haze
Energy Technology Data Exchange (ETDEWEB)
Egorov, Andrey E.; Pierpaoli, Elena [University of Southern California, 3620 McClintock Ave., SGM 408, Los Angeles, CA 90089 (United States); Gaskins, Jennifer M. [California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125 (United States); Pietrobon, Davide, E-mail: egorov@usc.edu, E-mail: jgaskins@uva.nl, E-mail: pierpaol@usc.edu, E-mail: daddeptr@gmail.com [University of California, Berkeley, Space Sciences Laboratory, 7 Gauss Rd, Berkeley CA 94720 (United States)
2016-03-01
Gamma rays and microwave observations of the Galactic Center and surrounding areas indicate the presence of anomalous emission, whose origin remains ambiguous. The possibility of dark matter annihilation explaining both signals through prompt emission at gamma rays and secondary emission at microwave frequencies from interactions of high-energy electrons produced in annihilation with the Galactic magnetic fields has attracted much interest in recent years. We investigate the dark matter interpretation of the Galactic Center gamma-ray excess by searching for the associated synchrotron emission in the WMAP and Planck microwave data. Considering various magnetic field and cosmic-ray propagation models, we predict the synchrotron emission due to dark matter annihilation in our Galaxy, and compare it with the WMAP and Planck data at 23–70 GHz. In addition to standard microwave foregrounds, we separately model the microwave counterpart to the Fermi Bubbles and the signal due to dark matter annihilation, and use component separation techniques to extract the signal associated with each template from the total emission. We confirm the presence of the Haze at the level of ≈7% of the total sky intensity at 23 GHz in our chosen region of interest, with a harder spectrum (I ∼ ν{sup −0.8}) than the synchrotron from regular cosmic-ray electrons. The data do not show a strong preference towards fitting the Haze by either the Bubbles or dark matter emission only. Inclusion of both components provides a better fit with a dark matter contribution to the Haze emission of ≈20% at 23 GHz, however, due to significant uncertainties in foreground modeling, we do not consider this a clear detection of a dark matter signal. We set robust upper limits on the annihilation cross section by ignoring foregrounds, and also report best-fit dark matter annihilation parameters obtained from a complete template analysis. We conclude that the WMAP and Planck data are consistent with a
International Nuclear Information System (INIS)
Gjerloew, Eirik; Elgaroey, Oystein
2011-01-01
We submit recent claims of hints of primordial tensor perturbations and a scale-dependent spectral index in the WMAP data to a closer scrutiny. Our approach differs in that we use different best-fit values at which to fix the parameters not to be varied, and in that we use CosmoMC, thus incorporating the WMAP likelihood code and EE and BB mode data. We introduce a new parameter to test the claims of a scale-dependent spectral index. While we do find some hints of a scale-dependent spectral index over the multipole range l=2-220, the change in maximum likelihood is too small to justify introducing a new parameter. We conclude that there is no significant detection of primordial tensor perturbations, and that the assumption of a scale-independent spectral index in this multipole range has little effect on the amount of primordial gravitational waves found.
Searching for planar signatures in WMAP
International Nuclear Information System (INIS)
Abramo, L. Raul; Bernui, Armando; Pereira, Thiago S.
2009-01-01
We search for planar deviations of statistical isotropy in the Wilkinson Microwave Anisotropy Probe (WMAP) data by applying a recently introduced angular-planar statistics both to full-sky and to masked temperature maps, including in our analysis the effect of the residual foreground contamination and systematics in the foreground removing process as sources of error. We confirm earlier findings that full-sky maps exhibit anomalies at the planar (l) and angular (l) scales (l,l) = (2,5),(4,7), and (6,8), which seem to be due to unremoved foregrounds since this features are present in the full-sky map but not in the masked maps. On the other hand, our test detects slightly anomalous results at the scales (l,l) = (10,8) and (2,9) in the masked maps but not in the full-sky one, indicating that the foreground cleaning procedure (used to generate the full-sky map) could not only be creating false anomalies but also hiding existing ones. We also find a significant trace of an anomaly in the full-sky map at the scale (l,l) = (10,5), which is still present when we consider galactic cuts of 18.3% and 28.4%. As regards the quadrupole (l = 2), we find a coherent over-modulation over the whole celestial sphere, for all full-sky and cut-sky maps. Overall, our results seem to indicate that current CMB maps derived from WMAP data do not show significant signs of anisotropies, as measured by our angular-planar estimator. However, we have detected a curious coherence of planar modulations at angular scales of the order of the galaxy's plane, which may be an indication of residual contaminations in the full- and cut-sky maps
BAYESIAN ANALYSIS OF WHITE NOISE LEVELS IN THE FIVE-YEAR WMAP DATA
International Nuclear Information System (INIS)
Groeneboom, N. E.; Eriksen, H. K.; Gorski, K.; Huey, G.; Jewell, J.; Wandelt, B.
2009-01-01
We develop a new Bayesian method for estimating white noise levels in CMB sky maps, and apply this algorithm to the five-year Wilkinson Microwave Anisotropy Probe (WMAP) data. We assume that the amplitude of the noise rms is scaled by a constant value, α, relative to a pre-specified noise level. We then derive the corresponding conditional density, P(α | s, C l , d), which is subsequently integrated into a general CMB Gibbs sampler. We first verify our code by analyzing simulated data sets, and then apply the framework to the WMAP data. For the foreground-reduced five-year WMAP sky maps and the nominal noise levels initially provided in the five-year data release, we find that the posterior means typically range between α = 1.005 ± 0.001 and α = 1.010 ± 0.001 depending on differencing assembly, indicating that the noise level of these maps are biased low by 0.5%-1.0%. The same problem is not observed for the uncorrected WMAP sky maps. After the preprint version of this letter appeared on astro-ph., the WMAP team has corrected the values presented on their web page, noting that the initially provided values were in fact estimates from the three-year data release, not from the five-year estimates. However, internally in their five-year analysis the correct noise values were used, and no cosmological results are therefore compromised by this error. Thus, our method has already been demonstrated in practice to be both useful and accurate.
ColliderBit. A GAMBIT module for the calculation of high-energy collider observables and likelihoods
Energy Technology Data Exchange (ETDEWEB)
Balazs, Csaba [Monash University, School of Physics and Astronomy, Melbourne, VIC (Australia); Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); Buckley, Andy [University of Glasgow, SUPA, School of Physics and Astronomy, Glasgow (United Kingdom); Dal, Lars A.; Krislock, Abram; Raklev, Are [University of Oslo, Department of Physics, Oslo (Norway); Farmer, Ben [AlbaNova University Centre, Oskar Klein Centre for Cosmoparticle Physics, Stockholm (Sweden); Jackson, Paul; Murnane, Daniel; White, Martin [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); University of Adelaide, Department of Physics, Adelaide, SA (Australia); Kvellestad, Anders [NORDITA, Stockholm (Sweden); Putze, Antje [Universite de Savoie, LAPTh, Annecy-le-Vieux (France); Rogan, Christopher [Harvard University, Department of Physics, Cambridge, MA (United States); Saavedra, Aldo [Australian Research Council Centre of Excellence for Particle Physics at the Tera-scale (Australia); The University of Sydney, Faculty of Engineering and Information Technologies, Centre for Translational Data Science, School of Physics, Sydney, NSW (Australia); Scott, Pat [Imperial College London, Blackett Laboratory, Department of Physics, London (United Kingdom); Weniger, Christoph [University of Amsterdam, GRAPPA, Institute of Physics, Amsterdam (Netherlands); Collaboration: The GAMBIT Scanner Workgroup
2017-11-15
We describe ColliderBit, a new code for the calculation of high energy collider observables in theories of physics beyond the Standard Model (BSM). ColliderBit features a generic interface to BSM models, a unique parallelised Monte Carlo event generation scheme suitable for large-scale supercomputer applications, and a number of LHC analyses, covering a reasonable range of the BSM signatures currently sought by ATLAS and CMS. ColliderBit also calculates likelihoods for Higgs sector observables, and LEP searches for BSM particles. These features are provided by a combination of new code unique toColliderBit, and interfaces to existing state-of-the-art public codes. ColliderBit is both an important part of the GAMBIT framework for BSM inference, and a standalone tool for efficiently applying collider constraints to theories of new physics. (orig.)
Model independent foreground power spectrum estimation using WMAP 5-year data
International Nuclear Information System (INIS)
Ghosh, Tuhin; Souradeep, Tarun; Saha, Rajib; Jain, Pankaj
2009-01-01
In this paper, we propose and implement on WMAP 5 yr data a model independent approach of foreground power spectrum estimation for multifrequency observations of the CMB experiments. Recently, a model independent approach of CMB power spectrum estimation was proposed by Saha et al. 2006. This methodology demonstrates that the CMB power spectrum can be reliably estimated solely from WMAP data without assuming any template models for the foreground components. In the current paper, we extend this work to estimate the galactic foreground power spectrum using the WMAP 5 yr maps following a self-contained analysis. We apply the model independent method in harmonic basis to estimate the foreground power spectrum and frequency dependence of combined foregrounds. We also study the behavior of synchrotron spectral index variation over different regions of the sky. We use the full sky Haslam map as an external template to increase the degrees of freedom, while computing the synchrotron spectral index over the frequency range from 408 MHz to 94 GHz. We compare our results with those obtained from maximum entropy method foreground maps, which are formed in pixel space. We find that relative to our model independent estimates maximum entropy method maps overestimate the foreground power close to galactic plane and underestimates it at high latitudes.
Cosmic microwave background snapshots: pre-WMAP and post-WMAP.
Bond, J Richard; Contaldi, Carlo; Pogosyan, Dmitry
2003-11-15
We highlight the remarkable evolution in the cosmic microwave background (CMB) power spectrum C(l) as a function of multipole l over the past few years, and in the cosmological parameters for minimal inflation models derived from it: from anisotropy results before 2000; in 2000 and 2001 from Boomerang, Maxima and the Degree Angular Scale Interferometer (DASI), extending l to approximately 1000; and in 2002 from the Cosmic Background Imager (CBI), Very Small Array (VSA), ARCHEOPS and Arcminute Cosmology Bolometer Array Receiver (ACBAR), extending l to approximately 3000, with more from Boomerang and DASI as well. Pre-WMAP (pre-Wilkinson Microwave Anisotropy Probe) optimal band powers are in good agreement with each other and with the exquisite one-year WMAP results, unveiled in February 2003, which now dominate the l less, similar 600 bands. These CMB experiments significantly increased the case for accelerated expansion in the early Universe (the inflationary paradigm) and at the current epoch (dark energy dominance) when they were combined with "prior" probabilities on the parameters. The minimal inflation parameter set, [omega(b), omega(cdm), Omega(tot), Omega(Lambda), n(s), tau(C), sigma(8)], is applied in the same way to the evolving data. C(l) database and Monte Carlo Markov Chain (MCMC) methods are shown to give similar values, which are highly stable over time and for different prior choices, with the increasing precision best characterized by decreasing errors on uncorrelated "parameter eigenmodes". Priors applied range from weak ones to stronger constraints from the expansion rate (HST-h), from cosmic acceleration from supernovae (SN1) and from galaxy clustering, gravitational lensing and local cluster abundance (LSS). After marginalizing over the other cosmic and experimental variables for the weak + LSS prior, the pre-WMAP data of January 2003 compared with the post-WMAP data of March 2003 give Omega(tot) = 1.03(-0.04)(+0.05) compared with 1
Owen, Art B
2001-01-01
Empirical likelihood provides inferences whose validity does not depend on specifying a parametric model for the data. Because it uses a likelihood, the method has certain inherent advantages over resampling methods: it uses the data to determine the shape of the confidence regions, and it makes it easy to combined data from multiple sources. It also facilitates incorporating side information, and it simplifies accounting for censored, truncated, or biased sampling.One of the first books published on the subject, Empirical Likelihood offers an in-depth treatment of this method for constructing confidence regions and testing hypotheses. The author applies empirical likelihood to a range of problems, from those as simple as setting a confidence region for a univariate mean under IID sampling, to problems defined through smooth functions of means, regression models, generalized linear models, estimating equations, or kernel smooths, and to sampling with non-identically distributed data. Abundant figures offer vi...
CERN. Geneva
2015-01-01
Most physics results at the LHC end in a likelihood ratio test. This includes discovery and exclusion for searches as well as mass, cross-section, and coupling measurements. The use of Machine Learning (multivariate) algorithms in HEP is mainly restricted to searches, which can be reduced to classification between two fixed distributions: signal vs. background. I will show how we can extend the use of ML classifiers to distributions parameterized by physical quantities like masses and couplings as well as nuisance parameters associated to systematic uncertainties. This allows for one to approximate the likelihood ratio while still using a high dimensional feature vector for the data. Both the MEM and ABC approaches mentioned above aim to provide inference on model parameters (like cross-sections, masses, couplings, etc.). ABC is fundamentally tied Bayesian inference and focuses on the “likelihood free” setting where only a simulator is available and one cannot directly compute the likelihood for the dat...
Searching for non-Gaussianity in the WMAP data
International Nuclear Information System (INIS)
Bernui, A.; Reboucas, M. J.
2009-01-01
Some analyses of recent cosmic microwave background (CMB) data have provided hints that there are deviations from Gaussianity in the WMAP CMB temperature fluctuations. Given the far-reaching consequences of such a non-Gaussianity for our understanding of the physics of the early universe, it is important to employ alternative indicators in order to determine whether the reported non-Gaussianity is of cosmological origin, and/or extract further information that may be helpful for identifying its causes. We propose two new non-Gaussianity indicators, based on skewness and kurtosis of large-angle patches of CMB maps, which provide a measure of departure from Gaussianity on large angular scales. A distinctive feature of these indicators is that they provide sky maps of non-Gaussianity of the CMB temperature data, thus allowing a possible additional window into their origins. Using these indicators, we find no significant deviation from Gaussianity in the three and five-year WMAP Internal Linear Combination (ILC) map with KQ75 mask, while the ILC unmasked map exhibits deviation from Gaussianity, quantifying therefore the WMAP team recommendation to employ the new mask KQ75 for tests of Gaussianity. We also use our indicators to test for Gaussianity the single frequency foreground unremoved WMAP three and five-year maps, and show that the K and Ka maps exhibit a clear indication of deviation from Gaussianity even with the KQ75 mask. We show that our findings are robust with respect to the details of the method.
Measuring the cosmological background of relativistic particles with WMAP
Crotty, P; Pastor, S; Crotty, Patrick; Lesgourgues, Julien; Pastor, Sergio
2003-01-01
We show that the first year results of the Wilkinson Microwave Anisotropy Probe (WMAP) constrain very efficiently the energy density in relativistic particles in the universe. We derive new bounds on additional relativistic degrees of freedom expressed in terms of an excess in the effective number of light neutrinos Delta N_eff. Within the flat LambdaCDM scenario, the allowed range is Delta N_eff < 6 (95% CL) using WMAP data only, or -2.6 < Delta N_eff < 4 with the prior H_0= 72 \\pm 8 km/s/Mpc. When other cosmic microwave background and large scale structure experiments are taken into account, the window shrinks to -1.5 < Delta N_eff < 4.2. These results are in perfect agreement with the bounds from primordial nucleosynthesis. Non-minimal cosmological models with extra relativistic degrees of freedom are now severely restricted.
WMAP constraints on the Cardassian model
International Nuclear Information System (INIS)
Sen, A.A.; Sen, S.
2003-01-01
We investigate the constraints on the Cardassian model using the recent results from the Wilkinson microwave anisotropy probe for the locations of the peaks of the cosmic microwave background (CMB) anisotropy spectrum. We find that the model is consistent with the recent observational data for a certain range of the model parameter n and the cosmological parameters. We find that the Cardassian model is favored compared to the ΛCDM model for a higher spectral index (n s ≅1) together with a lower value of the Hubble parameter h (h≤0.71). But for smaller values of n s , both ΛCDM and Cardassian models are equally favored. Also, irrespective of supernova constraints, CMB data alone predict the current acceleration of the Universe in this model. We have also studied the constraint on σ 8 , the rms density fluctuations at the 8h -1 Mpc scale
Inflation and WMAP three year data. Features have a feature.
Energy Technology Data Exchange (ETDEWEB)
Covi, L.; Hamann, J. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Melchiorri, A. [INFN, Roma (Italy)]|[Rome-3 Univ. (Italy). Dipt. di Fisica; Slosar, A. [Ljubljana Univ. (Slovenia). Faculty of Mathematics and Physics; Sorbera, I. [Rome-3 Univ. (Italy). Dipt. di Fisica
2006-06-15
The new three year WMAP data seem to confirm the presence of non-standard large scale features in the Cosmic Microwave Anisotropies power spectrum. While these features may hint at uncorrected experimental systematics, it is also possible to generate, in a cosmological way, oscillations on large angular scales by introducing a sharp step in the inflaton potential. Using current cosmological data, we derive constraints on the position, magnitude and gradient of a possible step in the inflaton potential. We show that a step in the potential, while strongly constrained by current data, is still allowed and may provide an interesting explanation to the currently measured deviations from the standard featureless spectrum. (Orig.)
Inflation and WMAP three year data. Features have a future
International Nuclear Information System (INIS)
Covi, L.; Hamann, J.; Melchiorri, A.; Rome-3 Univ.; Slosar, A.; Sorbera, I.
2006-06-01
The new three year WMAP data seem to confirm the presence of non-standard large scale features in the Cosmic Microwave Anisotropies power spectrum. While these features may hint at uncorrected experimental systematics, it is also possible to generate, in a cosmological way, oscillations on large angular scales by introducing a sharp step in the inflaton potential. Using current cosmological data, we derive constraints on the position, magnitude and gradient of a possible step in the inflaton potential. We show that a step in the potential, while strongly constrained by current data, is still allowed and may provide an interesting explanation to the currently measured deviations from the standard featureless spectrum. (Orig.)
WMAP constraints on inflationary models with global defects
International Nuclear Information System (INIS)
Bevis, Neil; Hindmarsh, Mark; Kunz, Martin
2004-01-01
We use the cosmic microwave background angular power spectra to place upper limits on the degree to which global defects may have aided cosmic structure formation. We explore this under the inflationary paradigm, but with the addition of textures resulting from the breaking of a global O(4) symmetry during the early stages of the Universe. As a measure of their contribution, we use the fraction of the temperature power spectrum that is attributed to the defects at a multipole of 10. However, we find a parameter degeneracy enabling a fit to the first-year WMAP data to be made even with a significant defect fraction. This degeneracy involves the baryon fraction and the Hubble constant, plus the normalization and tilt of the primordial power spectrum. Hence, constraints on these cosmological parameters are weakened. Combining the WMAP data with a constraint on the physical baryon fraction from big bang nucleosynthesis calculations and high-redshift deuterium abundance limits the extent of the degeneracy and gives an upper bound on the defect fraction of 0.13 (95% confidence)
Foreground removal from WMAP 7 yr polarization maps using an MLP neural network
DEFF Research Database (Denmark)
Nørgaard-Nielsen, Hans Ulrik
2012-01-01
. As a concrete example, the WMAP 7-year polarization data, the most reliable determination of the polarization properties of the CMB, has been analyzed. The analysis has adopted the frequency maps, noise models, window functions and the foreground models as provided by the WMAP Team, and no auxiliary data...
Optimized Large-scale CMB Likelihood and Quadratic Maximum Likelihood Power Spectrum Estimation
Gjerløw, E.; Colombo, L. P. L.; Eriksen, H. K.; Górski, K. M.; Gruppuso, A.; Jewell, J. B.; Plaszczynski, S.; Wehus, I. K.
2015-11-01
We revisit the problem of exact cosmic microwave background (CMB) likelihood and power spectrum estimation with the goal of minimizing computational costs through linear compression. This idea was originally proposed for CMB purposes by Tegmark et al., and here we develop it into a fully functioning computational framework for large-scale polarization analysis, adopting WMAP as a working example. We compare five different linear bases (pixel space, harmonic space, noise covariance eigenvectors, signal-to-noise covariance eigenvectors, and signal-plus-noise covariance eigenvectors) in terms of compression efficiency, and find that the computationally most efficient basis is the signal-to-noise eigenvector basis, which is closely related to the Karhunen-Loeve and Principal Component transforms, in agreement with previous suggestions. For this basis, the information in 6836 unmasked WMAP sky map pixels can be compressed into a smaller set of 3102 modes, with a maximum error increase of any single multipole of 3.8% at ℓ ≤ 32 and a maximum shift in the mean values of a joint distribution of an amplitude-tilt model of 0.006σ. This compression reduces the computational cost of a single likelihood evaluation by a factor of 5, from 38 to 7.5 CPU seconds, and it also results in a more robust likelihood by implicitly regularizing nearly degenerate modes. Finally, we use the same compression framework to formulate a numerically stable and computationally efficient variation of the Quadratic Maximum Likelihood implementation, which requires less than 3 GB of memory and 2 CPU minutes per iteration for ℓ ≤ 32, rendering low-ℓ QML CMB power spectrum analysis fully tractable on a standard laptop.
Risser, MD; Wehner, MF
2017-01-01
©2017. American Geophysical Union. All Rights Reserved. Record rainfall amounts were recorded during Hurricane Harvey in the Houston, Texas, area, leading to widespread flooding. We analyze observed precipitation from the Global Historical Climatology Network with a covariate-based extreme value statistical analysis, accounting for both the external influence of global warming and the internal influence of El Niño–Southern Oscillation. We find that human-induced climate change likely increase...
Risser, Mark D.; Wehner, Michael F.
2017-12-01
Record rainfall amounts were recorded during Hurricane Harvey in the Houston, Texas, area, leading to widespread flooding. We analyze observed precipitation from the Global Historical Climatology Network with a covariate-based extreme value statistical analysis, accounting for both the external influence of global warming and the internal influence of El Niño-Southern Oscillation. We find that human-induced climate change likely increased the chances of the observed precipitation accumulations during Hurricane Harvey in the most affected areas of Houston by a factor of at least 3.5. Further, precipitation accumulations in these areas were likely increased by at least 18.8% (best estimate of 37.7%), which is larger than the 6-7% associated with an attributable warming of 1°C in the Gulf of Mexico and Clausius-Clapeyron scaling. In a Granger causality sense, these statements provide lower bounds on the impact of climate change and motivate further attribution studies using dynamical climate models.
Xu, Jason; Guttorp, Peter; Kato-Maeda, Midori; Minin, Vladimir N
2015-12-01
Continuous-time birth-death-shift (BDS) processes are frequently used in stochastic modeling, with many applications in ecology and epidemiology. In particular, such processes can model evolutionary dynamics of transposable elements-important genetic markers in molecular epidemiology. Estimation of the effects of individual covariates on the birth, death, and shift rates of the process can be accomplished by analyzing patient data, but inferring these rates in a discretely and unevenly observed setting presents computational challenges. We propose a multi-type branching process approximation to BDS processes and develop a corresponding expectation maximization algorithm, where we use spectral techniques to reduce calculation of expected sufficient statistics to low-dimensional integration. These techniques yield an efficient and robust optimization routine for inferring the rates of the BDS process, and apply broadly to multi-type branching processes whose rates can depend on many covariates. After rigorously testing our methodology in simulation studies, we apply our method to study intrapatient time evolution of IS6110 transposable element, a genetic marker frequently used during estimation of epidemiological clusters of Mycobacterium tuberculosis infections. © 2015, The International Biometric Society.
Sunyaev-Zeldovich effect in WMAP and its effect on cosmological parameters
International Nuclear Information System (INIS)
Huffenberger, Kevin M.; Seljak, Uros; Makarov, Alexey
2004-01-01
We use multifrequency information in first year Wilkinson microwave anisotropy probe (WMAP) data to search for the Sunyaev-Zeldovich (SZ) effect. WMAP has sufficiently broad frequency coverage to constrain the SZ effect without the addition of higher frequency data: the SZ power spectrum amplitude is expected to increase 50% from W to Q frequency band. This, in combination with the low noise in WMAP, allows us to strongly constrain the SZ contribution. We derive an optimal frequency combination of WMAP cross-spectra to extract the SZ effect in the presence of noise, cosmic microwave background (CMB), and radio point sources, which are marginalized over. We find that the SZ contribution is less than 2% (95% C.L.) at the first acoustic peak in W band. Under the assumption that the removed radio point sources are not correlated with the SZ effect this limit implies σ 8 <1.07 at 95% C.L. We investigate the effect on the cosmological parameters of allowing an SZ component. We run Monte Carlo Markov chains with and without an SZ component and find that the addition of the SZ effect does not affect any of the cosmological conclusions. We conclude that the SZ effect does not contaminate the WMAP CMB or change cosmological parameters, refuting the recent claims that they may be corrupted
Ponder, Kara A.
In the late 1990s, Type Ia supernovae (SNeIa) led to the discovery that the Universe is expanding at an accelerating rate due to dark energy. Since then, many different tracers of acceleration have been used to characterize dark energy, but the source of cosmic acceleration has remained a mystery. To better understand dark energy, future surveys such as the ground-based Large Synoptic Survey Telescope and the space-based Wide-Field Infrared Survey Telescope will collect thousands of SNeIa to use as a primary dark energy probe. These large surveys will be systematics limited, which makes it imperative for our insight regarding systematics to dramatically increase over the next decade for SNeIa to continue to contribute to precision cosmology. I approach this problem by improving statistical methods in the likelihood analysis and collecting near infrared (NIR) SNeIa with their host galaxies to improve the nearby data set and search for additional systematics. Using more statistically robust methods to account for systematics within the likelihood function can increase accuracy in cosmological parameters with a minimal precision loss. Though a sample of at least 10,000 SNeIa is necessary to confirm multiple populations of SNeIa, the bias in cosmology is ˜ 2 sigma with only 2,500 SNeIa. This work focused on an example systematic (host galaxy correlations), but it can be generalized for any systematic that can be represented by a distribution of multiple Gaussians. The SweetSpot survey gathered 114 low-redshift, NIR SNeIa that will act as a crucial anchor sample for the future high redshift surveys. NIR observations are not as affected by dust contamination, which may lead to increased understanding of systematics seen in optical wavelengths. We obtained spatially resolved spectra for 32 SweetSpot host galaxies to test for local host galaxy correlations. For the first time, we probe global host galaxy correlations with NIR brightnesses from the current literature
Foreground removal from WMAP 5 yr temperature maps using an MLP neural network
Nørgaard-Nielsen, H. U.
2010-09-01
Aims: One of the main obstacles for extracting the cosmic microwave background (CMB) signal from observations in the mm/sub-mm range is the foreground contamination by emission from Galactic component: mainly synchrotron, free-free, and thermal dust emission. The statistical nature of the intrinsic CMB signal makes it essential to minimize the systematic errors in the CMB temperature determinations. Methods: The feasibility of using simple neural networks to extract the CMB signal from detailed simulated data has already been demonstrated. Here, simple neural networks are applied to the WMAP 5 yr temperature data without using any auxiliary data. Results: A simple multilayer perceptron neural network with two hidden layers provides temperature estimates over more than 75 per cent of the sky with random errors significantly below those previously extracted from these data. Also, the systematic errors, i.e. errors correlated with the Galactic foregrounds, are very small. Conclusions: With these results the neural network method is well prepared for dealing with the high - quality CMB data from the ESA Planck Surveyor satellite. unknown author type, collab
On the Origins of the CMB: Insight from the COBE, WMAP, and Relikt-1 Satellites
Directory of Open Access Journals (Sweden)
Robitaille P.-M.
2007-01-01
Full Text Available The powerful “Cosmic Microwave Background (CMB” signal currently associated with the origins of the Universe is examined from a historical perspective and relative to the experimental context in which it was measured. Results from the COBE satellite are reviewed, with particular emphasis on the systematic error observed in determining the CMB temperature. The nature of the microwave signal emanating from the oceans is also discussed. From this analysis, it is demonstrated that it is improper for the COBE team to model the Earth as a 285 K blackbody source. The assignment of temperatures to objects that fail to meet the requirements set forth in Kirchhoff’s law constitutes a serious overextension of the laws of thermal emission. Using this evidence, and the general rule that powerful signals are associated with proximal sources, the CMB monopole signal is reassigned to the oceans. In turn, through the analysis of COBE, WMAP, and Relikt-1 data, the dipole signal is attributed to motion through a much weaker microwave field present both at the position of the Earth and at the second Lagrange point.
Extended likelihood inference in reliability
International Nuclear Information System (INIS)
Martz, H.F. Jr.; Beckman, R.J.; Waller, R.A.
1978-10-01
Extended likelihood methods of inference are developed in which subjective information in the form of a prior distribution is combined with sampling results by means of an extended likelihood function. The extended likelihood function is standardized for use in obtaining extended likelihood intervals. Extended likelihood intervals are derived for the mean of a normal distribution with known variance, the failure-rate of an exponential distribution, and the parameter of a binomial distribution. Extended second-order likelihood methods are developed and used to solve several prediction problems associated with the exponential and binomial distributions. In particular, such quantities as the next failure-time, the number of failures in a given time period, and the time required to observe a given number of failures are predicted for the exponential model with a gamma prior distribution on the failure-rate. In addition, six types of life testing experiments are considered. For the binomial model with a beta prior distribution on the probability of nonsurvival, methods are obtained for predicting the number of nonsurvivors in a given sample size and for predicting the required sample size for observing a specified number of nonsurvivors. Examples illustrate each of the methods developed. Finally, comparisons are made with Bayesian intervals in those cases where these are known to exist
Earthquake likelihood model testing
Schorlemmer, D.; Gerstenberger, M.C.; Wiemer, S.; Jackson, D.D.; Rhoades, D.A.
2007-01-01
INTRODUCTIONThe Regional Earthquake Likelihood Models (RELM) project aims to produce and evaluate alternate models of earthquake potential (probability per unit volume, magnitude, and time) for California. Based on differing assumptions, these models are produced to test the validity of their assumptions and to explore which models should be incorporated in seismic hazard and risk evaluation. Tests based on physical and geological criteria are useful but we focus on statistical methods using future earthquake catalog data only. We envision two evaluations: a test of consistency with observed data and a comparison of all pairs of models for relative consistency. Both tests are based on the likelihood method, and both are fully prospective (i.e., the models are not adjusted to fit the test data). To be tested, each model must assign a probability to any possible event within a specified region of space, time, and magnitude. For our tests the models must use a common format: earthquake rates in specified “bins” with location, magnitude, time, and focal mechanism limits.Seismology cannot yet deterministically predict individual earthquakes; however, it should seek the best possible models for forecasting earthquake occurrence. This paper describes the statistical rules of an experiment to examine and test earthquake forecasts. The primary purposes of the tests described below are to evaluate physical models for earthquakes, assure that source models used in seismic hazard and risk studies are consistent with earthquake data, and provide quantitative measures by which models can be assigned weights in a consensus model or be judged as suitable for particular regions.In this paper we develop a statistical method for testing earthquake likelihood models. A companion paper (Schorlemmer and Gerstenberger 2007, this issue) discusses the actual implementation of these tests in the framework of the RELM initiative.Statistical testing of hypotheses is a common task and a
A LAST LOOK AT THE MICROWAVE HAZE/BUBBLES WITH WMAP
Energy Technology Data Exchange (ETDEWEB)
Dobler, Gregory, E-mail: dobler@kitp.ucsb.edu [Kavli Institute for Theoretical Physics, University of California, Santa Barbara Kohn Hall, Santa Barbara, CA 93106 (United States)
2012-05-01
The microwave 'haze' was first discovered with the initial release of the full sky data from the Wilkinson Microwave Anisotropy Probe (WMAP). It is diffuse emission toward the center of our Galaxy with spectral behavior that makes it difficult to categorize as any of the previously known emission mechanisms at those wavelengths. With now seven years of WMAP data publicly available, we have learned much about the nature of the haze, and with the release of data from the Fermi Gamma-Ray Space Telescope and the discovery of the gamma-ray haze/bubbles, we have had a spectacular confirmation of its existence at other wavelengths. As the WMAP mission winds down and the Planck mission prepares to release data, I take a last look at what WMAP has to tell us about the origin of this unique Galactic feature. Much like the gamma rays, the microwave haze/bubbles is/are elongated in latitude with respect to longitude by a factor of roughly two, and at high latitudes, the microwave emission cuts off sharply above {approx}35 Degree-Sign (compared to {approx}50 Degree-Sign in the gammas). The hard spectrum of electrons required to generate the microwave synchrotron is consistent with that required to generate gamma-ray emission via inverse Compton scattering, though it is likely that these signals result from distinct regions of the spectrum ({approx}10 GeV for the microwaves and {approx}1 TeV for the gammas). While there is no evidence for significant haze polarization in the seven-year WMAP data, I demonstrate explicitly that it is unlikely such a signal would be detectable above the noise.
PROBING THE DARK FLOW SIGNAL IN WMAP 9 -YEAR AND PLANCK COSMIC MICROWAVE BACKGROUND MAPS
Energy Technology Data Exchange (ETDEWEB)
Atrio-Barandela, F. [Física Teórica, Universidad de Salamanca, E-37008 Salamanca (Spain); Kashlinsky, A. [NASA Goddard Space Flight Center and SSAI, Observational Cosmology Lab, Greenbelt, MD 20771 (United States); Ebeling, H. [Institute for Astronomy, University of Hawaii, Honolulu, HI 96822 (United States); Fixsen, D. J. [NASA Goddard Space Flight Center and UMCP, Observational Cosmology Lab, Greenbelt, MD 20771 (United States); Kocevski, D., E-mail: atrio@usal.es, E-mail: Alexander.Kashlinsky@nasa.gov, E-mail: ebeling@ifa.hawaii.edu, E-mail: Dale.Fixsen@nasa.gov, E-mail: dale.kocevski@colby.edu [Physics and Astronomy, 5800 Mayflower Hill, Waterville, ME 04901 (United States)
2015-09-10
The “dark flow” dipole is a statistically significant dipole found at the position of galaxy clusters in filtered maps of Cosmic Microwave Background (CMB) temperature anisotropies. The dipole measured in WMAP 3-, 5-, and 7- year data releases was (1) mutually consistent, (2) roughly aligned with the all-sky CMB dipole, and (3) correlated with clusters’ X-ray luminosities. We analyzed WMAP 9 -year and Planck 1st- year data releases using a catalog of 980 clusters outside of the Kp0 mask to test our earlier findings. The dipoles measured on these new data sets are fully compatible with our earlier estimates, are similar in amplitude and direction to our previous results, and are in disagreement with the results of an earlier study by the Planck Collaboration. Furthermore, in the Planck data sets dipoles are found to be independent of frequency, ruling out the thermal Sunyaev–Zeldovich as the source of the effect. In the data of both WMAP and Planck we find a clear correlation between the dipole measured at the cluster location in filtered maps and the average anisotropy on the original maps, further proving that the dipole is associated with clusters. The dipole signal is dominated by the most massive clusters, with a statistical significance that is better than 99%, slightly larger than in WMAP. Since both data sets differ in foreground contributions, instrumental noise, and other systematics, the agreement between the WMAP and Planck dipoles argues against them being due to systematic effects in either of the experiments.
International Nuclear Information System (INIS)
Wall, M.J.W.
1992-01-01
The notion of open-quotes probabilityclose quotes is generalized to that of open-quotes likelihood,close quotes and a natural logical structure is shown to exist for any physical theory which predicts likelihoods. Two physically based axioms are given for this logical structure to form an orthomodular poset, with an order-determining set of states. The results strengthen the basis of the quantum logic approach to axiomatic quantum theory. 25 refs
The phylogenetic likelihood library.
Flouri, T; Izquierdo-Carrasco, F; Darriba, D; Aberer, A J; Nguyen, L-T; Minh, B Q; Von Haeseler, A; Stamatakis, A
2015-03-01
We introduce the Phylogenetic Likelihood Library (PLL), a highly optimized application programming interface for developing likelihood-based phylogenetic inference and postanalysis software. The PLL implements appropriate data structures and functions that allow users to quickly implement common, error-prone, and labor-intensive tasks, such as likelihood calculations, model parameter as well as branch length optimization, and tree space exploration. The highly optimized and parallelized implementation of the phylogenetic likelihood function and a thorough documentation provide a framework for rapid development of scalable parallel phylogenetic software. By example of two likelihood-based phylogenetic codes we show that the PLL improves the sequential performance of current software by a factor of 2-10 while requiring only 1 month of programming time for integration. We show that, when numerical scaling for preventing floating point underflow is enabled, the double precision likelihood calculations in the PLL are up to 1.9 times faster than those in BEAGLE. On an empirical DNA dataset with 2000 taxa the AVX version of PLL is 4 times faster than BEAGLE (scaling enabled and required). The PLL is available at http://www.libpll.org under the GNU General Public License (GPL). © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.
The Laplace Likelihood Ratio Test for Heteroscedasticity
Directory of Open Access Journals (Sweden)
J. Martin van Zyl
2011-01-01
Full Text Available It is shown that the likelihood ratio test for heteroscedasticity, assuming the Laplace distribution, gives good results for Gaussian and fat-tailed data. The likelihood ratio test, assuming normality, is very sensitive to any deviation from normality, especially when the observations are from a distribution with fat tails. Such a likelihood test can also be used as a robust test for a constant variance in residuals or a time series if the data is partitioned into groups.
Searching for CPT violation with cosmic microwave background data from WMAP and BOOMERANG.
Feng, Bo; Li, Mingzhe; Xia, Jun-Qing; Chen, Xuelei; Zhang, Xinmin
2006-06-09
We search for signatures of Lorentz and violations in the cosmic microwave background (CMB) temperature and polarization anisotropies by using the Wilkinson Microwave Anisotropy Probe (WMAP) and the 2003 flight of BOOMERANG (B03) data. We note that if the Lorentz and symmetries are broken by a Chern-Simons term in the effective Lagrangian, which couples the dual electromagnetic field strength tensor to an external four-vector, the polarization vectors of propagating CMB photons will get rotated. Using the WMAP data alone, one could put an interesting constraint on the size of such a term. Combined with the B03 data, we found that a nonzero rotation angle of the photons is mildly favored: [Formula: See Text].
CORRELATION ANALYSIS BETWEEN TIBET AS-γ TeV COSMIC RAY AND WMAP NINE-YEAR DATA
Energy Technology Data Exchange (ETDEWEB)
Yin, Qian-Qing; Zhang, Shuang-Nan, E-mail: zhangsn@ihep.ac.cn [Key Laboratory of Particle Astrophysics, Institute of High Energy Physics, Beijing 100049 (China)
2015-08-01
The WMAP team subtracted template-based foreground models to produce foreground-reduced maps, and masked point sources and uncertain sky regions directly; however, whether foreground residuals exist in the WMAP foreground-reduced maps is still an open question. Here, we use Pearson correlation coefficient analysis with AS-γ TeV cosmic ray (CR) data to probe possible foreground residuals in the WMAP nine-year data. The correlation results between the CR and foreground-contained maps (WMAP foreground-unreduced maps, WMAP template-based, and Maximum Entropy Method foreground models) suggest that: (1) CRs can trace foregrounds in the WMAP data; (2) at least some TeV CRs originate from the Milky Way; (3) foregrounds may be related to the existence of CR anisotropy (loss-cone and tail-in structures); (4) there exist differences among different types of foregrounds in the decl. range of <15°. Then, we generate 10,000 mock cosmic microwave background (CMB) sky maps to describe the cosmic variance, which is used to measure the effect of the fluctuations of all possible CMB maps to the correlations between CR and CMB maps. Finally, we do correlation analysis between the CR and WMAP foreground-reduced maps, and find that: (1) there are significant anticorrelations; and (2) the WMAP foreground-reduced maps are credible. However, the significant anticorrelations may be accidental, and the higher signal-to-noise ratio Planck SMICA map cannot reject the hypothesis of accidental correlations. We therefore can only conclude that the foreground residuals exist with ∼95% probability.
Hybrid inflation revisited in light of WMAP5 data
International Nuclear Information System (INIS)
Rehman, Mansoor Ur; Shafi, Qaisar; Wickman, Joshua R.
2009-01-01
We study the effects of including one-loop radiative corrections in a nonsupersymmetric hybrid inflationary model. These corrections can arise from Yukawa couplings between the inflaton and right-handed neutrinos, and induce a maximum in the potential which admits hilltop-type solutions in addition to the standard hybrid solutions. We obtain a red-tilted spectral index n s , consistent with Wilkinson Microwave Anisotropy Probe 5 yr analysis data, for sub-Planckian values of the field. This is in contrast to the tree level hybrid analysis, in which a red-tilted spectrum is achieved only for trans-Planckian values of the field. Successful reheating is obtained at the end of the inflationary phase via a conversion of the inflaton and waterfall fields into right-handed neutrinos, whose subsequent decay can explain the observed baryon asymmetry via leptogenesis.
Taking the Measure of the Universe: Cosmology from the WMAP Mission
Hinshaw, Gary F.
2007-01-01
The data from the first three years of operation of the Wilkinson Microwave Anisotropy Probe (WMAP) satellite provide detailed full-sky maps of the cosmic microwave background temperature anisotropy and new full-sky maps of the polarization. Together, the data provide a wealth of cosmological information, including the age of the universe, the epoch when the first stars formed, and the overall composition of baryonic matter, dark matter, and dark energy. The results also provide constraints on the period of inflationary expansion in the very first moments of time. These and other aspects of the mission will be discussed.
Likelihood estimators for multivariate extremes
Huser, Raphaë l; Davison, Anthony C.; Genton, Marc G.
2015-01-01
The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.
Likelihood estimators for multivariate extremes
Huser, Raphaël
2015-11-17
The main approach to inference for multivariate extremes consists in approximating the joint upper tail of the observations by a parametric family arising in the limit for extreme events. The latter may be expressed in terms of componentwise maxima, high threshold exceedances or point processes, yielding different but related asymptotic characterizations and estimators. The present paper clarifies the connections between the main likelihood estimators, and assesses their practical performance. We investigate their ability to estimate the extremal dependence structure and to predict future extremes, using exact calculations and simulation, in the case of the logistic model.
FERMI-LAT AND WMAP OBSERVATIONS OF THE PUPPIS A SUPERNOVA REMNANT
Energy Technology Data Exchange (ETDEWEB)
Hewitt, J. W. [NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States); Grondin, M.-H. [Max-Planck-Institut fuer Kernphysik, D-69029 Heidelberg (Germany); Lemoine-Goumard, M.; Reposeur, T. [Centre d' Etudes Nucleaires de Bordeaux-Gradignan, Universite Bordeaux 1, CNRS/IN2p3, F-33175 Gradignan (France); Ballet, J. [Laboratoire AIM, CEA-IRFU/CNRS/Universite Paris Diderot, Service d' Astrophysique, CEA Saclay, F-91191 Gif sur Yvette (France); Tanaka, T., E-mail: john.w.hewitt@nasa.gov, E-mail: marie-helene.grondin@mpi-hd.mpg.de, E-mail: lemoine@cenbg.in2p3.fr [W. W. Hansen Experimental Physics Laboratory, Kavli Institute for Particle Astrophysics and Cosmology, Department of Physics and SLAC National Accelerator Laboratory, Stanford University, Stanford, CA 94305 (United States)
2012-11-10
We report the detection of GeV {gamma}-ray emission from the supernova remnant (SNR) Puppis A with the Fermi Gamma-Ray Space Telescope. Puppis A is among the faintest SNRs yet detected at GeV energies, with a luminosity of only 2.7 Multiplication-Sign 10{sup 34} (D/2.2 kpc){sup 2} erg s{sup -1} between 1 and 100 GeV. The {gamma}-ray emission from the remnant is spatially extended, with a morphology matching that of the radio and X-ray emission, and is well described by a simple power law with an index of 2.1. We attempt to model the broadband spectral energy distribution (SED), from radio to {gamma}-rays, using standard nonthermal emission mechanisms. To constrain the relativistic electron population we use 7 years of Wilkinson Microwave Anisotropy Probe data to extend the radio spectrum up to 93 GHz. Both leptonic- and hadronic-dominated models can reproduce the nonthermal SED, requiring a total content of cosmic-ray electrons and protons accelerated in Puppis A of at least W {sub CR} Almost-Equal-To (1-5) Multiplication-Sign 10{sup 49} erg.
ANALYSIS OF WMAP 7 YEAR TEMPERATURE DATA: ASTROPHYSICS OF THE GALACTIC HAZE
Energy Technology Data Exchange (ETDEWEB)
Pietrobon, Davide; Gorski, Krzysztof M.; Bartlett, James; Colombo, Loris P. L.; Jewell, Jeffrey B.; Pagano, Luca; Rocha, Graca; Lawrence, Charles R. [Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Drive, Pasadena, CA 91109-8099 (United States); Banday, A. J. [Universie de Toulouse, UPS-OMP, IRAP, Toulouse (France); Dobler, Gregory [Kavli Institute for Theoretical Physics, University of California, Santa Barbara Kohn Hall, Santa Barbara, CA 93106 (United States); Hildebrandt, Sergi R. [Division of Physics, Mathematics and Astronomy, California Institute of Technology, 1200 East California Boulevard, Pasadena, CA 91125 (United States); Eriksen, Hans Kristian [Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029, Blindern, N-0315 Oslo (Norway); Saha, Rajib, E-mail: davide.pietrobon@jpl.nasa.gov [Physics Department, Indian Institute of Science Education and Research Bhopal, Bhopal, MP 462023 (India)
2012-08-10
We perform a joint analysis of the cosmic microwave background (CMB) and Galactic emission from the WMAP 7 year temperature data. Using the Commander code, based on Gibbs sampling, we simultaneously derive the CMB and Galactic components on scales larger than 1 Degree-Sign with improved sensitivity over previous work. We conduct a detailed study of the low-frequency Galactic foreground, focusing on the 'microwave haze' emission around the Galactic center. We demonstrate improved performance in quantifying the diffuse Galactic emission when including Haslam 408 MHz data and when jointly modeling the spinning and thermal dust emission. We examine whether the hypothetical Galactic haze can be explained by a spatial variation of the synchrotron spectral index, and find that the excess of emission around the Galactic center is stable with respect to variations of the foreground model. Our results demonstrate that the new Galactic foreground component-the microwave haze-is indeed present.
Foreground removal from WMAP 5 yr temperature maps using an MLP neural network
DEFF Research Database (Denmark)
Nørgaard-Nielsen, Hans Ulrik
2010-01-01
CMB signal makes it essential to minimize the systematic errors in the CMB temperature determinations. Methods. The feasibility of using simple neural networks to extract the CMB signal from detailed simulated data has already been demonstrated. Here, simple neural networks are applied to the WMAP 5...... yr temperature data without using any auxiliary data. Results. A simple multilayer perceptron neural network with two hidden layers provides temperature estimates over more than 75 per cent of the sky with random errors significantly below those previously extracted from these data. Also......, the systematic errors, i.e. errors correlated with the Galactic foregrounds, are very small. Conclusions. With these results the neural network method is well prepared for dealing with the high-quality CMB data from the ESA Planck Surveyor satellite. © ESO, 2010....
Maximum likelihood estimation for integrated diffusion processes
DEFF Research Database (Denmark)
Baltazar-Larios, Fernando; Sørensen, Michael
We propose a method for obtaining maximum likelihood estimates of parameters in diffusion models when the data is a discrete time sample of the integral of the process, while no direct observations of the process itself are available. The data are, moreover, assumed to be contaminated...... EM-algorithm to obtain maximum likelihood estimates of the parameters in the diffusion model. As part of the algorithm, we use a recent simple method for approximate simulation of diffusion bridges. In simulation studies for the Ornstein-Uhlenbeck process and the CIR process the proposed method works...... by measurement errors. Integrated volatility is an example of this type of observations. Another example is ice-core data on oxygen isotopes used to investigate paleo-temperatures. The data can be viewed as incomplete observations of a model with a tractable likelihood function. Therefore we propose a simulated...
Dark matter CMB constraints and likelihoods for poor particle physicists
Energy Technology Data Exchange (ETDEWEB)
Cline, James M.; Scott, Pat, E-mail: jcline@physics.mcgill.ca, E-mail: patscott@physics.mcgill.ca [Department of Physics, McGill University, 3600 rue University, Montréal, QC, H3A 2T8 (Canada)
2013-03-01
The cosmic microwave background provides constraints on the annihilation and decay of light dark matter at redshifts between 100 and 1000, the strength of which depends upon the fraction of energy ending up in the form of electrons and photons. The resulting constraints are usually presented for a limited selection of annihilation and decay channels. Here we provide constraints on the annihilation cross section and decay rate, at discrete values of the dark matter mass m{sub χ}, for all the annihilation and decay channels whose secondary spectra have been computed using PYTHIA in arXiv:1012.4515 (''PPPC 4 DM ID: a poor particle physicist cookbook for dark matter indirect detection''), namely e, μ, τ, V → e, V → μ, V → τ, u, d s, c, b, t, γ, g, W, Z and h. By interpolating in mass, these can be used to find the CMB constraints and likelihood functions from WMAP7 and Planck for a wide range of dark matter models, including those with annihilation or decay into a linear combination of different channels.
Dark matter CMB constraints and likelihoods for poor particle physicists
International Nuclear Information System (INIS)
Cline, James M.; Scott, Pat
2013-01-01
The cosmic microwave background provides constraints on the annihilation and decay of light dark matter at redshifts between 100 and 1000, the strength of which depends upon the fraction of energy ending up in the form of electrons and photons. The resulting constraints are usually presented for a limited selection of annihilation and decay channels. Here we provide constraints on the annihilation cross section and decay rate, at discrete values of the dark matter mass m χ , for all the annihilation and decay channels whose secondary spectra have been computed using PYTHIA in arXiv:1012.4515 (''PPPC 4 DM ID: a poor particle physicist cookbook for dark matter indirect detection''), namely e, μ, τ, V → e, V → μ, V → τ, u, d s, c, b, t, γ, g, W, Z and h. By interpolating in mass, these can be used to find the CMB constraints and likelihood functions from WMAP7 and Planck for a wide range of dark matter models, including those with annihilation or decay into a linear combination of different channels
Likelihood devices in spatial statistics
Zwet, E.W. van
1999-01-01
One of the main themes of this thesis is the application to spatial data of modern semi- and nonparametric methods. Another, closely related theme is maximum likelihood estimation from spatial data. Maximum likelihood estimation is not common practice in spatial statistics. The method of moments
Spectrum of the Anomalous Microwave Emission in the North Celestial Pole with WMAP 7-Year Data
Directory of Open Access Journals (Sweden)
Anna Bonaldi
2012-01-01
Full Text Available We estimate the frequency spectrum of the diffuse anomalous microwave emission (AME on the North Celestial Pole (NCP region of the sky with the Correlated Component Analysis (CCA component separation method applied to WMAP 7-yr data. The NCP is a suitable region for this analysis because the AME is weakly contaminated by synchrotron and free-free emission. By modeling the AME component as a peaked spectrum we estimate the peak frequency to be 21.7±0.8 GHz, in agreement with previous analyses which favored νp < 23 GHz. The ability of our method to correctly recover the position of the peak is verified through simulations. We compare the estimated AME spectrum with theoretical spinning dust models to constrain the hydrogen density nH. The best results are obtained with densities around 0.2–0.3 cm−3, typical of warm ionised medium (WIM to warm neutral medium (WNM conditions. The degeneracy with the gas temperature prevents an accurate determination of nH, especially for low hydrogen ionization fractions, where densities of a few cm−3 are also allowed.
Neutrino cosmology after WMAP 7-year data and LHC first Z' bounds.
Anchordoqui, Luis Alfredo; Goldberg, Haim
2012-02-24
The gauge-extended U(1)(C)×SU(2)(L)×U(1)(I(R))×U(1)(L) model elevates the global symmetries of the standard model (baryon number B and lepton number L) to local gauge symmetries. The U(1)(L) symmetry leads to three superweakly interacting right-handed neutrinos. This also renders a B-L symmetry nonanomalous. The superweak interactions of these Dirac states permit ν(R) decoupling just above the QCD phase transition: 175 is < or approximately equal to T(ν(R))(dec)/MeV is < or approximately equal to 250. In this transitional region, the residual temperature ratio between ν(L) and ν(R) generates extra relativistic degrees of freedom at BBN and at the CMB epochs. Consistency with both WMAP 7-year data and recent estimates of the primordial 4He mass fraction is achieved for 3
Obtaining reliable Likelihood Ratio tests from simulated likelihood functions
DEFF Research Database (Denmark)
Andersen, Laura Mørch
It is standard practice by researchers and the default option in many statistical programs to base test statistics for mixed models on simulations using asymmetric draws (e.g. Halton draws). This paper shows that when the estimated likelihood functions depend on standard deviations of mixed param...
Ego involvement increases doping likelihood.
Ring, Christopher; Kavussanu, Maria
2018-08-01
Achievement goal theory provides a framework to help understand how individuals behave in achievement contexts, such as sport. Evidence concerning the role of motivation in the decision to use banned performance enhancing substances (i.e., doping) is equivocal on this issue. The extant literature shows that dispositional goal orientation has been weakly and inconsistently associated with doping intention and use. It is possible that goal involvement, which describes the situational motivational state, is a stronger determinant of doping intention. Accordingly, the current study used an experimental design to examine the effects of goal involvement, manipulated using direct instructions and reflective writing, on doping likelihood in hypothetical situations in college athletes. The ego-involving goal increased doping likelihood compared to no goal and a task-involving goal. The present findings provide the first evidence that ego involvement can sway the decision to use doping to improve athletic performance.
Maximum likelihood of phylogenetic networks.
Jin, Guohua; Nakhleh, Luay; Snir, Sagi; Tuller, Tamir
2006-11-01
Horizontal gene transfer (HGT) is believed to be ubiquitous among bacteria, and plays a major role in their genome diversification as well as their ability to develop resistance to antibiotics. In light of its evolutionary significance and implications for human health, developing accurate and efficient methods for detecting and reconstructing HGT is imperative. In this article we provide a new HGT-oriented likelihood framework for many problems that involve phylogeny-based HGT detection and reconstruction. Beside the formulation of various likelihood criteria, we show that most of these problems are NP-hard, and offer heuristics for efficient and accurate reconstruction of HGT under these criteria. We implemented our heuristics and used them to analyze biological as well as synthetic data. In both cases, our criteria and heuristics exhibited very good performance with respect to identifying the correct number of HGT events as well as inferring their correct location on the species tree. Implementation of the criteria as well as heuristics and hardness proofs are available from the authors upon request. Hardness proofs can also be downloaded at http://www.cs.tau.ac.il/~tamirtul/MLNET/Supp-ML.pdf
Incorporating Nuisance Parameters in Likelihoods for Multisource Spectra
Conway, J.S.
2011-01-01
We describe here the general mathematical approach to constructing likelihoods for fitting observed spectra in one or more dimensions with multiple sources, including the effects of systematic uncertainties represented as nuisance parameters, when the likelihood is to be maximized with respect to these parameters. We consider three types of nuisance parameters: simple multiplicative factors, source spectra "morphing" parameters, and parameters representing statistical uncertainties in the predicted source spectra.
International Nuclear Information System (INIS)
Benetti, Micol; Lattanzi, Massimiliano; Calabrese, Erminia; Melchiorri, Alessandro
2011-01-01
We update the constraints on possible features in the primordial inflationary density perturbation spectrum by using the latest data from the WMAP7 and ACT (Atacama Cosmology Telescope) cosmic microwave background experiments. The inclusion of new data significantly improves the constraints with respect to older work, especially to smaller angular scales. While we found no clear statistical evidence in the data for extensions to the simplest, featureless, inflationary model, models with a step provide a significantly better fit than standard featureless power-law spectra. We show that the possibility of a step in the inflationary potential like the one preferred by current data will soon be tested by the forthcoming temperature and polarization data from the Planck satellite mission.
A short proof that phylogenetic tree reconstruction by maximum likelihood is hard.
Roch, Sebastien
2006-01-01
Maximum likelihood is one of the most widely used techniques to infer evolutionary histories. Although it is thought to be intractable, a proof of its hardness has been lacking. Here, we give a short proof that computing the maximum likelihood tree is NP-hard by exploiting a connection between likelihood and parsimony observed by Tuffley and Steel.
A Short Proof that Phylogenetic Tree Reconstruction by Maximum Likelihood is Hard
Roch, S.
2005-01-01
Maximum likelihood is one of the most widely used techniques to infer evolutionary histories. Although it is thought to be intractable, a proof of its hardness has been lacking. Here, we give a short proof that computing the maximum likelihood tree is NP-hard by exploiting a connection between likelihood and parsimony observed by Tuffley and Steel.
Algorithms of maximum likelihood data clustering with applications
Giada, Lorenzo; Marsili, Matteo
2002-12-01
We address the problem of data clustering by introducing an unsupervised, parameter-free approach based on maximum likelihood principle. Starting from the observation that data sets belonging to the same cluster share a common information, we construct an expression for the likelihood of any possible cluster structure. The likelihood in turn depends only on the Pearson's coefficient of the data. We discuss clustering algorithms that provide a fast and reliable approximation to maximum likelihood configurations. Compared to standard clustering methods, our approach has the advantages that (i) it is parameter free, (ii) the number of clusters need not be fixed in advance and (iii) the interpretation of the results is transparent. In order to test our approach and compare it with standard clustering algorithms, we analyze two very different data sets: time series of financial market returns and gene expression data. We find that different maximization algorithms produce similar cluster structures whereas the outcome of standard algorithms has a much wider variability.
Dissociating response conflict and error likelihood in anterior cingulate cortex.
Yeung, Nick; Nieuwenhuis, Sander
2009-11-18
Neuroimaging studies consistently report activity in anterior cingulate cortex (ACC) in conditions of high cognitive demand, leading to the view that ACC plays a crucial role in the control of cognitive processes. According to one prominent theory, the sensitivity of ACC to task difficulty reflects its role in monitoring for the occurrence of competition, or "conflict," between responses to signal the need for increased cognitive control. However, a contrasting theory proposes that ACC is the recipient rather than source of monitoring signals, and that ACC activity observed in relation to task demand reflects the role of this region in learning about the likelihood of errors. Response conflict and error likelihood are typically confounded, making the theories difficult to distinguish empirically. The present research therefore used detailed computational simulations to derive contrasting predictions regarding ACC activity and error rate as a function of response speed. The simulations demonstrated a clear dissociation between conflict and error likelihood: fast response trials are associated with low conflict but high error likelihood, whereas slow response trials show the opposite pattern. Using the N2 component as an index of ACC activity, an EEG study demonstrated that when conflict and error likelihood are dissociated in this way, ACC activity tracks conflict and is negatively correlated with error likelihood. These findings support the conflict-monitoring theory and suggest that, in speeded decision tasks, ACC activity reflects current task demands rather than the retrospective coding of past performance.
A Predictive Likelihood Approach to Bayesian Averaging
Directory of Open Access Journals (Sweden)
Tomáš Jeřábek
2015-01-01
Full Text Available Multivariate time series forecasting is applied in a wide range of economic activities related to regional competitiveness and is the basis of almost all macroeconomic analysis. In this paper we combine multivariate density forecasts of GDP growth, inflation and real interest rates from four various models, two type of Bayesian vector autoregression (BVAR models, a New Keynesian dynamic stochastic general equilibrium (DSGE model of small open economy and DSGE-VAR model. The performance of models is identified using historical dates including domestic economy and foreign economy, which is represented by countries of the Eurozone. Because forecast accuracy of observed models are different, the weighting scheme based on the predictive likelihood, the trace of past MSE matrix, model ranks are used to combine the models. The equal-weight scheme is used as a simple combination scheme. The results show that optimally combined densities are comparable to the best individual models.
International Nuclear Information System (INIS)
Behbahani, Siavosh R.; Mirbabayi, Mehrdad; Senatore, Leonardo; Smith, Kendrick M.
2014-01-01
Given the fantastic experimental effort, it is important to thoroughly explore the signature space of inflationary models. The fact that higher derivative operators do not renormalize lower derivative ones allows us to find a large class of technically natural single-clock inflationary models where, in the context of the Effective Field Theory of Inflation, the leading interactions have many derivatives. We systematically explore the 3-point function induced by these models and their overlap with the standard equilateral and orthogonal templates. We find that in order to satisfactorily cover the signature space of these models, two new additional templates need to be included. We then perform the optimal analysis of the WMAP 9-year data for the resulting four templates, finding that the overall significance of a non-zero signal is between 2–2.5σ, depending on the choice of parameter space, partially driven by the preference for nonzero f NL orth in WMAP9
MXLKID: a maximum likelihood parameter identifier
International Nuclear Information System (INIS)
Gavel, D.T.
1980-07-01
MXLKID (MaXimum LiKelihood IDentifier) is a computer program designed to identify unknown parameters in a nonlinear dynamic system. Using noisy measurement data from the system, the maximum likelihood identifier computes a likelihood function (LF). Identification of system parameters is accomplished by maximizing the LF with respect to the parameters. The main body of this report briefly summarizes the maximum likelihood technique and gives instructions and examples for running the MXLKID program. MXLKID is implemented LRLTRAN on the CDC7600 computer at LLNL. A detailed mathematical description of the algorithm is given in the appendices. 24 figures, 6 tables
Modelling maximum likelihood estimation of availability
International Nuclear Information System (INIS)
Waller, R.A.; Tietjen, G.L.; Rock, G.W.
1975-01-01
Suppose the performance of a nuclear powered electrical generating power plant is continuously monitored to record the sequence of failure and repairs during sustained operation. The purpose of this study is to assess one method of estimating the performance of the power plant when the measure of performance is availability. That is, we determine the probability that the plant is operational at time t. To study the availability of a power plant, we first assume statistical models for the variables, X and Y, which denote the time-to-failure and the time-to-repair variables, respectively. Once those statistical models are specified, the availability, A(t), can be expressed as a function of some or all of their parameters. Usually those parameters are unknown in practice and so A(t) is unknown. This paper discusses the maximum likelihood estimator of A(t) when the time-to-failure model for X is an exponential density with parameter, lambda, and the time-to-repair model for Y is an exponential density with parameter, theta. Under the assumption of exponential models for X and Y, it follows that the instantaneous availability at time t is A(t)=lambda/(lambda+theta)+theta/(lambda+theta)exp[-[(1/lambda)+(1/theta)]t] with t>0. Also, the steady-state availability is A(infinity)=lambda/(lambda+theta). We use the observations from n failure-repair cycles of the power plant, say X 1 , X 2 , ..., Xsub(n), Y 1 , Y 2 , ..., Ysub(n) to present the maximum likelihood estimators of A(t) and A(infinity). The exact sampling distributions for those estimators and some statistical properties are discussed before a simulation model is used to determine 95% simulation intervals for A(t). The methodology is applied to two examples which approximate the operating history of two nuclear power plants. (author)
Essays on empirical likelihood in economics
Gao, Z.
2012-01-01
This thesis intends to exploit the roots of empirical likelihood and its related methods in mathematical programming and computation. The roots will be connected and the connections will induce new solutions for the problems of estimation, computation, and generalization of empirical likelihood.
Robust Gaussian Process Regression with a Student-t Likelihood
Jylänki, P.P.; Vanhatalo, J.; Vehtari, A.
2011-01-01
This paper considers the robust and efficient implementation of Gaussian process regression with a Student-t observation model, which has a non-log-concave likelihood. The challenge with the Student-t model is the analytically intractable inference which is why several approximative methods have
Likelihood Analysis of Supersymmetric SU(5) GUTs
Bagnaschi, E.
2017-01-01
We perform a likelihood analysis of the constraints from accelerator experiments and astrophysical observations on supersymmetric (SUSY) models with SU(5) boundary conditions on soft SUSY-breaking parameters at the GUT scale. The parameter space of the models studied has 7 parameters: a universal gaugino mass $m_{1/2}$, distinct masses for the scalar partners of matter fermions in five- and ten-dimensional representations of SU(5), $m_5$ and $m_{10}$, and for the $\\mathbf{5}$ and $\\mathbf{\\bar 5}$ Higgs representations $m_{H_u}$ and $m_{H_d}$, a universal trilinear soft SUSY-breaking parameter $A_0$, and the ratio of Higgs vevs $\\tan \\beta$. In addition to previous constraints from direct sparticle searches, low-energy and flavour observables, we incorporate constraints based on preliminary results from 13 TeV LHC searches for jets + MET events and long-lived particles, as well as the latest PandaX-II and LUX searches for direct Dark Matter detection. In addition to previously-identified mechanisms for bringi...
Profile-likelihood Confidence Intervals in Item Response Theory Models.
Chalmers, R Philip; Pek, Jolynn; Liu, Yang
2017-01-01
Confidence intervals (CIs) are fundamental inferential devices which quantify the sampling variability of parameter estimates. In item response theory, CIs have been primarily obtained from large-sample Wald-type approaches based on standard error estimates, derived from the observed or expected information matrix, after parameters have been estimated via maximum likelihood. An alternative approach to constructing CIs is to quantify sampling variability directly from the likelihood function with a technique known as profile-likelihood confidence intervals (PL CIs). In this article, we introduce PL CIs for item response theory models, compare PL CIs to classical large-sample Wald-type CIs, and demonstrate important distinctions among these CIs. CIs are then constructed for parameters directly estimated in the specified model and for transformed parameters which are often obtained post-estimation. Monte Carlo simulation results suggest that PL CIs perform consistently better than Wald-type CIs for both non-transformed and transformed parameters.
Pendeteksian Outlier pada Regresi Nonlinier dengan Metode statistik Likelihood Displacement
Directory of Open Access Journals (Sweden)
Siti Tabi'atul Hasanah
2012-11-01
Full Text Available Outlier is an observation that much different (extreme from the other observational data, or data can be interpreted that do not follow the general pattern of the model. Sometimes outliers provide information that can not be provided by other data. That's why outliers should not just be eliminated. Outliers can also be an influential observation. There are many methods that can be used to detect of outliers. In previous studies done on outlier detection of linear regression. Next will be developed detection of outliers in nonlinear regression. Nonlinear regression here is devoted to multiplicative nonlinear regression. To detect is use of statistical method likelihood displacement. Statistical methods abbreviated likelihood displacement (LD is a method to detect outliers by removing the suspected outlier data. To estimate the parameters are used to the maximum likelihood method, so we get the estimate of the maximum. By using LD method is obtained i.e likelihood displacement is thought to contain outliers. Further accuracy of LD method in detecting the outliers are shown by comparing the MSE of LD with the MSE from the regression in general. Statistic test used is Λ. Initial hypothesis was rejected when proved so is an outlier.
First observational tests of eternal inflation.
Feeney, Stephen M; Johnson, Matthew C; Mortlock, Daniel J; Peiris, Hiranya V
2011-08-12
The eternal inflation scenario predicts that our observable Universe resides inside a single bubble embedded in a vast inflating multiverse. We present the first observational tests of eternal inflation, performing a search for cosmological signatures of collisions with other bubble universes in cosmic microwave background data from the WMAP satellite. We conclude that the WMAP 7-year data do not warrant augmenting the cold dark matter model with a cosmological constant with bubble collisions, constraining the average number of detectable bubble collisions on the full sky N(s) < 1.6 at 68% C.L. Data from the Planck satellite can be used to more definitively test the bubble-collision hypothesis.
Asymptotic Likelihood Distribution for Correlated & Constrained Systems
Agarwal, Ujjwal
2016-01-01
It describes my work as summer student at CERN. The report discusses the asymptotic distribution of the likelihood ratio for total no. of parameters being h and 2 out of these being are constrained and correlated.
Maximum-Likelihood Detection Of Noncoherent CPM
Divsalar, Dariush; Simon, Marvin K.
1993-01-01
Simplified detectors proposed for use in maximum-likelihood-sequence detection of symbols in alphabet of size M transmitted by uncoded, full-response continuous phase modulation over radio channel with additive white Gaussian noise. Structures of receivers derived from particular interpretation of maximum-likelihood metrics. Receivers include front ends, structures of which depends only on M, analogous to those in receivers of coherent CPM. Parts of receivers following front ends have structures, complexity of which would depend on N.
Likelihood ratio sequential sampling models of recognition memory.
Osth, Adam F; Dennis, Simon; Heathcote, Andrew
2017-02-01
The mirror effect - a phenomenon whereby a manipulation produces opposite effects on hit and false alarm rates - is benchmark regularity of recognition memory. A likelihood ratio decision process, basing recognition on the relative likelihood that a stimulus is a target or a lure, naturally predicts the mirror effect, and so has been widely adopted in quantitative models of recognition memory. Glanzer, Hilford, and Maloney (2009) demonstrated that likelihood ratio models, assuming Gaussian memory strength, are also capable of explaining regularities observed in receiver-operating characteristics (ROCs), such as greater target than lure variance. Despite its central place in theorising about recognition memory, however, this class of models has not been tested using response time (RT) distributions. In this article, we develop a linear approximation to the likelihood ratio transformation, which we show predicts the same regularities as the exact transformation. This development enabled us to develop a tractable model of recognition-memory RT based on the diffusion decision model (DDM), with inputs (drift rates) provided by an approximate likelihood ratio transformation. We compared this "LR-DDM" to a standard DDM where all targets and lures receive their own drift rate parameters. Both were implemented as hierarchical Bayesian models and applied to four datasets. Model selection taking into account parsimony favored the LR-DDM, which requires fewer parameters than the standard DDM but still fits the data well. These results support log-likelihood based models as providing an elegant explanation of the regularities of recognition memory, not only in terms of choices made but also in terms of the times it takes to make them. Copyright © 2016 Elsevier Inc. All rights reserved.
Host, Ole; Lahav, Ofer; Abdalla, Filipe B.; Eitel, Klaus
2007-12-01
We present a showcase for deriving bounds on the neutrino masses from laboratory experiments and cosmological observations. We compare the frequentist and Bayesian bounds on the effective electron neutrino mass mβ which the KATRIN neutrino mass experiment is expected to obtain, using both an analytical likelihood function and Monte Carlo simulations of KATRIN. Assuming a uniform prior in mβ, we find that a null result yields an upper bound of about 0.17 eV at 90% confidence in the Bayesian analysis, to be compared with the frequentist KATRIN reference value of 0.20 eV. This is a significant difference when judged relative to the systematic and statistical uncertainties of the experiment. On the other hand, an input mβ=0.35eV, which is the KATRIN 5σ detection threshold, would be detected at virtually the same level. Finally, we combine the simulated KATRIN results with cosmological data in the form of present (post-WMAP) and future (simulated Planck) observations. If an input of mβ=0.2eV is assumed in our simulations, KATRIN alone excludes a zero neutrino mass at 2.2σ. Adding Planck data increases the probability of detection to a median 2.7σ. The analysis highlights the importance of combining cosmological and laboratory data on an equal footing.
International Nuclear Information System (INIS)
Host, Ole; Lahav, Ofer; Abdalla, Filipe B.; Eitel, Klaus
2007-01-01
We present a showcase for deriving bounds on the neutrino masses from laboratory experiments and cosmological observations. We compare the frequentist and Bayesian bounds on the effective electron neutrino mass m β which the KATRIN neutrino mass experiment is expected to obtain, using both an analytical likelihood function and Monte Carlo simulations of KATRIN. Assuming a uniform prior in m β , we find that a null result yields an upper bound of about 0.17 eV at 90% confidence in the Bayesian analysis, to be compared with the frequentist KATRIN reference value of 0.20 eV. This is a significant difference when judged relative to the systematic and statistical uncertainties of the experiment. On the other hand, an input m β =0.35 eV, which is the KATRIN 5σ detection threshold, would be detected at virtually the same level. Finally, we combine the simulated KATRIN results with cosmological data in the form of present (post-WMAP) and future (simulated Planck) observations. If an input of m β =0.2 eV is assumed in our simulations, KATRIN alone excludes a zero neutrino mass at 2.2σ. Adding Planck data increases the probability of detection to a median 2.7σ. The analysis highlights the importance of combining cosmological and laboratory data on an equal footing
Likelihood analysis of supersymmetric SU(5) GUTs
Energy Technology Data Exchange (ETDEWEB)
Bagnaschi, E.; Weiglein, G. [DESY, Hamburg (Germany); Costa, J.C.; Buchmueller, O.; Citron, M.; Richards, A.; De Vries, K.J. [Imperial College, High Energy Physics Group, Blackett Laboratory, London (United Kingdom); Sakurai, K. [University of Durham, Science Laboratories, Department of Physics, Institute for Particle Physics Phenomenology, Durham (United Kingdom); University of Warsaw, Faculty of Physics, Institute of Theoretical Physics, Warsaw (Poland); Borsato, M.; Chobanova, V.; Lucio, M.; Martinez Santos, D. [Universidade de Santiago de Compostela, Santiago de Compostela (Spain); Cavanaugh, R. [Fermi National Accelerator Laboratory, Batavia, IL (United States); University of Illinois at Chicago, Physics Department, Chicago, IL (United States); Roeck, A. de [CERN, Experimental Physics Department, Geneva (Switzerland); Antwerp University, Wilrijk (Belgium); Dolan, M.J. [University of Melbourne, ARC Centre of Excellence for Particle Physics at the Terascale, School of Physics, Parkville (Australia); Ellis, J.R. [King' s College London, Theoretical Particle Physics and Cosmology Group, Department of Physics, London (United Kingdom); Theoretical Physics Department, CERN, Geneva 23 (Switzerland); Flaecher, H. [University of Bristol, H.H. Wills Physics Laboratory, Bristol (United Kingdom); Heinemeyer, S. [Campus of International Excellence UAM+CSIC, Cantoblanco, Madrid (Spain); Instituto de Fisica Teorica UAM-CSIC, Madrid (Spain); Instituto de Fisica de Cantabria (CSIC-UC), Santander (Spain); Isidori, G. [Universitaet Zuerich, Physik-Institut, Zurich (Switzerland); Olive, K.A. [University of Minnesota, William I. Fine Theoretical Physics Institute, School of Physics and Astronomy, Minneapolis, MN (United States)
2017-02-15
We perform a likelihood analysis of the constraints from accelerator experiments and astrophysical observations on supersymmetric (SUSY) models with SU(5) boundary conditions on soft SUSY-breaking parameters at the GUT scale. The parameter space of the models studied has seven parameters: a universal gaugino mass m{sub 1/2}, distinct masses for the scalar partners of matter fermions in five- and ten-dimensional representations of SU(5), m{sub 5} and m{sub 10}, and for the 5 and anti 5 Higgs representations m{sub H{sub u}} and m{sub H{sub d}}, a universal trilinear soft SUSY-breaking parameter A{sub 0}, and the ratio of Higgs vevs tan β. In addition to previous constraints from direct sparticle searches, low-energy and flavour observables, we incorporate constraints based on preliminary results from 13 TeV LHC searches for jets + E{sub T} events and long-lived particles, as well as the latest PandaX-II and LUX searches for direct Dark Matter detection. In addition to previously identified mechanisms for bringing the supersymmetric relic density into the range allowed by cosmology, we identify a novel u{sub R}/c{sub R} - χ{sup 0}{sub 1} coannihilation mechanism that appears in the supersymmetric SU(5) GUT model and discuss the role of ν{sub τ} coannihilation. We find complementarity between the prospects for direct Dark Matter detection and SUSY searches at the LHC. (orig.)
Likelihood analysis of supersymmetric SU(5) GUTs
Energy Technology Data Exchange (ETDEWEB)
Bagnaschi, E. [DESY, Hamburg (Germany); Costa, J.C. [Imperial College, London (United Kingdom). Blackett Lab.; Sakurai, K. [Durham Univ. (United Kingdom). Inst. for Particle Physics Phenomonology; Warsaw Univ. (Poland). Inst. of Theoretical Physics; Collaboration: MasterCode Collaboration; and others
2016-10-15
We perform a likelihood analysis of the constraints from accelerator experiments and astrophysical observations on supersymmetric (SUSY) models with SU(5) boundary conditions on soft SUSY-breaking parameters at the GUT scale. The parameter space of the models studied has 7 parameters: a universal gaugino mass m{sub 1/2}, distinct masses for the scalar partners of matter fermions in five- and ten-dimensional representations of SU(5), m{sub 5} and m{sub 10}, and for the 5 and anti 5 Higgs representations m{sub H{sub u}} and m{sub H{sub d}}, a universal trilinear soft SUSY-breaking parameter A{sub 0}, and the ratio of Higgs vevs tan β. In addition to previous constraints from direct sparticle searches, low-energy and avour observables, we incorporate constraints based on preliminary results from 13 TeV LHC searches for jets+E{sub T} events and long-lived particles, as well as the latest PandaX-II and LUX searches for direct Dark Matter detection. In addition to previously-identified mechanisms for bringing the supersymmetric relic density into the range allowed by cosmology, we identify a novel u{sub R}/c{sub R}-χ{sup 0}{sub 1} coannihilation mechanism that appears in the supersymmetric SU(5) GUT model and discuss the role of ν{sub T} coannihilation. We find complementarity between the prospects for direct Dark Matter detection and SUSY searches at the LHC.
Gaussian copula as a likelihood function for environmental models
Wani, O.; Espadas, G.; Cecinati, F.; Rieckermann, J.
2017-12-01
Parameter estimation of environmental models always comes with uncertainty. To formally quantify this parametric uncertainty, a likelihood function needs to be formulated, which is defined as the probability of observations given fixed values of the parameter set. A likelihood function allows us to infer parameter values from observations using Bayes' theorem. The challenge is to formulate a likelihood function that reliably describes the error generating processes which lead to the observed monitoring data, such as rainfall and runoff. If the likelihood function is not representative of the error statistics, the parameter inference will give biased parameter values. Several uncertainty estimation methods that are currently being used employ Gaussian processes as a likelihood function, because of their favourable analytical properties. Box-Cox transformation is suggested to deal with non-symmetric and heteroscedastic errors e.g. for flow data which are typically more uncertain in high flows than in periods with low flows. Problem with transformations is that the results are conditional on hyper-parameters, for which it is difficult to formulate the analyst's belief a priori. In an attempt to address this problem, in this research work we suggest learning the nature of the error distribution from the errors made by the model in the "past" forecasts. We use a Gaussian copula to generate semiparametric error distributions . 1) We show that this copula can be then used as a likelihood function to infer parameters, breaking away from the practice of using multivariate normal distributions. Based on the results from a didactical example of predicting rainfall runoff, 2) we demonstrate that the copula captures the predictive uncertainty of the model. 3) Finally, we find that the properties of autocorrelation and heteroscedasticity of errors are captured well by the copula, eliminating the need to use transforms. In summary, our findings suggest that copulas are an
Maximum Likelihood and Restricted Likelihood Solutions in Multiple-Method Studies.
Rukhin, Andrew L
2011-01-01
A formulation of the problem of combining data from several sources is discussed in terms of random effects models. The unknown measurement precision is assumed not to be the same for all methods. We investigate maximum likelihood solutions in this model. By representing the likelihood equations as simultaneous polynomial equations, the exact form of the Groebner basis for their stationary points is derived when there are two methods. A parametrization of these solutions which allows their comparison is suggested. A numerical method for solving likelihood equations is outlined, and an alternative to the maximum likelihood method, the restricted maximum likelihood, is studied. In the situation when methods variances are considered to be known an upper bound on the between-method variance is obtained. The relationship between likelihood equations and moment-type equations is also discussed.
High-order Composite Likelihood Inference for Max-Stable Distributions and Processes
Castruccio, Stefano; Huser, Raphaë l; Genton, Marc G.
2015-01-01
In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of locations is a very challenging problem in computational statistics, and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely-used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.
High-order Composite Likelihood Inference for Max-Stable Distributions and Processes
Castruccio, Stefano
2015-09-29
In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of locations is a very challenging problem in computational statistics, and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely-used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.
Castruccio, Stefano; Huser, Raphaë l; Genton, Marc G.
2016-01-01
In multivariate or spatial extremes, inference for max-stable processes observed at a large collection of points is a very challenging problem and current approaches typically rely on less expensive composite likelihoods constructed from small subsets of data. In this work, we explore the limits of modern state-of-the-art computational facilities to perform full likelihood inference and to efficiently evaluate high-order composite likelihoods. With extensive simulations, we assess the loss of information of composite likelihood estimators with respect to a full likelihood approach for some widely used multivariate or spatial extreme models, we discuss how to choose composite likelihood truncation to improve the efficiency, and we also provide recommendations for practitioners. This article has supplementary material online.
Maximum Likelihood Compton Polarimetry with the Compton Spectrometer and Imager
Energy Technology Data Exchange (ETDEWEB)
Lowell, A. W.; Boggs, S. E; Chiu, C. L.; Kierans, C. A.; Sleator, C.; Tomsick, J. A.; Zoglauer, A. C. [Space Sciences Laboratory, University of California, Berkeley (United States); Chang, H.-K.; Tseng, C.-H.; Yang, C.-Y. [Institute of Astronomy, National Tsing Hua University, Taiwan (China); Jean, P.; Ballmoos, P. von [IRAP Toulouse (France); Lin, C.-H. [Institute of Physics, Academia Sinica, Taiwan (China); Amman, M. [Lawrence Berkeley National Laboratory (United States)
2017-10-20
Astrophysical polarization measurements in the soft gamma-ray band are becoming more feasible as detectors with high position and energy resolution are deployed. Previous work has shown that the minimum detectable polarization (MDP) of an ideal Compton polarimeter can be improved by ∼21% when an unbinned, maximum likelihood method (MLM) is used instead of the standard approach of fitting a sinusoid to a histogram of azimuthal scattering angles. Here we outline a procedure for implementing this maximum likelihood approach for real, nonideal polarimeters. As an example, we use the recent observation of GRB 160530A with the Compton Spectrometer and Imager. We find that the MDP for this observation is reduced by 20% when the MLM is used instead of the standard method.
Likelihood inference for unions of interacting discs
DEFF Research Database (Denmark)
Møller, Jesper; Helisová, Katarina
To the best of our knowledge, this is the first paper which discusses likelihood inference or a random set using a germ-grain model, where the individual grains are unobservable edge effects occur, and other complications appear. We consider the case where the grains form a disc process modelled...... is specified with respect to a given marked Poisson model (i.e. a Boolean model). We show how edge effects and other complications can be handled by considering a certain conditional likelihood. Our methodology is illustrated by analyzing Peter Diggle's heather dataset, where we discuss the results...... of simulation-based maximum likelihood inference and the effect of specifying different reference Poisson models....
Maintaining symmetry of simulated likelihood functions
DEFF Research Database (Denmark)
Andersen, Laura Mørch
This paper suggests solutions to two different types of simulation errors related to Quasi-Monte Carlo integration. Likelihood functions which depend on standard deviations of mixed parameters are symmetric in nature. This paper shows that antithetic draws preserve this symmetry and thereby...... improves precision substantially. Another source of error is that models testing away mixing dimensions must replicate the relevant dimensions of the quasi-random draws in the simulation of the restricted likelihood. These simulation errors are ignored in the standard estimation procedures used today...
Likelihood inference for unions of interacting discs
DEFF Research Database (Denmark)
Møller, Jesper; Helisova, K.
2010-01-01
This is probably the first paper which discusses likelihood inference for a random set using a germ-grain model, where the individual grains are unobservable, edge effects occur and other complications appear. We consider the case where the grains form a disc process modelled by a marked point...... process, where the germs are the centres and the marks are the associated radii of the discs. We propose to use a recent parametric class of interacting disc process models, where the minimal sufficient statistic depends on various geometric properties of the random set, and the density is specified......-based maximum likelihood inference and the effect of specifying different reference Poisson models....
Modeling gene expression measurement error: a quasi-likelihood approach
Directory of Open Access Journals (Sweden)
Strimmer Korbinian
2003-03-01
Full Text Available Abstract Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale. Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood. Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic variance structure of the data. As the quasi-likelihood behaves (almost like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also
Composite likelihood estimation of demographic parameters
Directory of Open Access Journals (Sweden)
Garrigan Daniel
2009-11-01
Full Text Available Abstract Background Most existing likelihood-based methods for fitting historical demographic models to DNA sequence polymorphism data to do not scale feasibly up to the level of whole-genome data sets. Computational economies can be achieved by incorporating two forms of pseudo-likelihood: composite and approximate likelihood methods. Composite likelihood enables scaling up to large data sets because it takes the product of marginal likelihoods as an estimator of the likelihood of the complete data set. This approach is especially useful when a large number of genomic regions constitutes the data set. Additionally, approximate likelihood methods can reduce the dimensionality of the data by summarizing the information in the original data by either a sufficient statistic, or a set of statistics. Both composite and approximate likelihood methods hold promise for analyzing large data sets or for use in situations where the underlying demographic model is complex and has many parameters. This paper considers a simple demographic model of allopatric divergence between two populations, in which one of the population is hypothesized to have experienced a founder event, or population bottleneck. A large resequencing data set from human populations is summarized by the joint frequency spectrum, which is a matrix of the genomic frequency spectrum of derived base frequencies in two populations. A Bayesian Metropolis-coupled Markov chain Monte Carlo (MCMCMC method for parameter estimation is developed that uses both composite and likelihood methods and is applied to the three different pairwise combinations of the human population resequence data. The accuracy of the method is also tested on data sets sampled from a simulated population model with known parameters. Results The Bayesian MCMCMC method also estimates the ratio of effective population size for the X chromosome versus that of the autosomes. The method is shown to estimate, with reasonable
Efficient Bit-to-Symbol Likelihood Mappings
Moision, Bruce E.; Nakashima, Michael A.
2010-01-01
This innovation is an efficient algorithm designed to perform bit-to-symbol and symbol-to-bit likelihood mappings that represent a significant portion of the complexity of an error-correction code decoder for high-order constellations. Recent implementation of the algorithm in hardware has yielded an 8- percent reduction in overall area relative to the prior design.
Likelihood-ratio-based biometric verification
Bazen, A.M.; Veldhuis, Raymond N.J.
2002-01-01
This paper presents results on optimal similarity measures for biometric verification based on fixed-length feature vectors. First, we show that the verification of a single user is equivalent to the detection problem, which implies that for single-user verification the likelihood ratio is optimal.
Likelihood Ratio-Based Biometric Verification
Bazen, A.M.; Veldhuis, Raymond N.J.
The paper presents results on optimal similarity measures for biometric verification based on fixed-length feature vectors. First, we show that the verification of a single user is equivalent to the detection problem, which implies that, for single-user verification, the likelihood ratio is optimal.
Phylogenetic analysis using parsimony and likelihood methods.
Yang, Z
1996-02-01
The assumptions underlying the maximum-parsimony (MP) method of phylogenetic tree reconstruction were intuitively examined by studying the way the method works. Computer simulations were performed to corroborate the intuitive examination. Parsimony appears to involve very stringent assumptions concerning the process of sequence evolution, such as constancy of substitution rates between nucleotides, constancy of rates across nucleotide sites, and equal branch lengths in the tree. For practical data analysis, the requirement of equal branch lengths means similar substitution rates among lineages (the existence of an approximate molecular clock), relatively long interior branches, and also few species in the data. However, a small amount of evolution is neither a necessary nor a sufficient requirement of the method. The difficulties involved in the application of current statistical estimation theory to tree reconstruction were discussed, and it was suggested that the approach proposed by Felsenstein (1981, J. Mol. Evol. 17: 368-376) for topology estimation, as well as its many variations and extensions, differs fundamentally from the maximum likelihood estimation of a conventional statistical parameter. Evidence was presented showing that the Felsenstein approach does not share the asymptotic efficiency of the maximum likelihood estimator of a statistical parameter. Computer simulations were performed to study the probability that MP recovers the true tree under a hierarchy of models of nucleotide substitution; its performance relative to the likelihood method was especially noted. The results appeared to support the intuitive examination of the assumptions underlying MP. When a simple model of nucleotide substitution was assumed to generate data, the probability that MP recovers the true topology could be as high as, or even higher than, that for the likelihood method. When the assumed model became more complex and realistic, e.g., when substitution rates were
Factors Associated with Young Adults’ Pregnancy Likelihood
Kitsantas, Panagiota; Lindley, Lisa L.; Wu, Huichuan
2014-01-01
OBJECTIVES While progress has been made to reduce adolescent pregnancies in the United States, rates of unplanned pregnancy among young adults (18–29 years) remain high. In this study, we assessed factors associated with perceived likelihood of pregnancy (likelihood of getting pregnant/getting partner pregnant in the next year) among sexually experienced young adults who were not trying to get pregnant and had ever used contraceptives. METHODS We conducted a secondary analysis of 660 young adults, 18–29 years old in the United States, from the cross-sectional National Survey of Reproductive and Contraceptive Knowledge. Logistic regression and classification tree analyses were conducted to generate profiles of young adults most likely to report anticipating a pregnancy in the next year. RESULTS Nearly one-third (32%) of young adults indicated they believed they had at least some likelihood of becoming pregnant in the next year. Young adults who believed that avoiding pregnancy was not very important were most likely to report pregnancy likelihood (odds ratio [OR], 5.21; 95% CI, 2.80–9.69), as were young adults for whom avoiding a pregnancy was important but not satisfied with their current contraceptive method (OR, 3.93; 95% CI, 1.67–9.24), attended religious services frequently (OR, 3.0; 95% CI, 1.52–5.94), were uninsured (OR, 2.63; 95% CI, 1.31–5.26), and were likely to have unprotected sex in the next three months (OR, 1.77; 95% CI, 1.04–3.01). DISCUSSION These results may help guide future research and the development of pregnancy prevention interventions targeting sexually experienced young adults. PMID:25782849
Review of Elaboration Likelihood Model of persuasion
藤原, 武弘; 神山, 貴弥
1989-01-01
This article mainly introduces Elaboration Likelihood Model (ELM), proposed by Petty & Cacioppo, that is, a general attitude change theory. ELM posturates two routes to persuasion; central and peripheral route. Attitude change by central route is viewed as resulting from a diligent consideration of the issue-relevant informations presented. On the other hand, attitude change by peripheral route is viewed as resulting from peripheral cues in the persuasion context. Secondly we compare these tw...
Approximate maximum likelihood estimation for population genetic inference.
Bertl, Johanna; Ewing, Gregory; Kosiol, Carolin; Futschik, Andreas
2017-11-27
In many population genetic problems, parameter estimation is obstructed by an intractable likelihood function. Therefore, approximate estimation methods have been developed, and with growing computational power, sampling-based methods became popular. However, these methods such as Approximate Bayesian Computation (ABC) can be inefficient in high-dimensional problems. This led to the development of more sophisticated iterative estimation methods like particle filters. Here, we propose an alternative approach that is based on stochastic approximation. By moving along a simulated gradient or ascent direction, the algorithm produces a sequence of estimates that eventually converges to the maximum likelihood estimate, given a set of observed summary statistics. This strategy does not sample much from low-likelihood regions of the parameter space, and is fast, even when many summary statistics are involved. We put considerable efforts into providing tuning guidelines that improve the robustness and lead to good performance on problems with high-dimensional summary statistics and a low signal-to-noise ratio. We then investigate the performance of our resulting approach and study its properties in simulations. Finally, we re-estimate parameters describing the demographic history of Bornean and Sumatran orang-utans.
Corporate governance effect on financial distress likelihood: Evidence from Spain
Directory of Open Access Journals (Sweden)
Montserrat Manzaneque
2016-01-01
Full Text Available The paper explores some mechanisms of corporate governance (ownership and board characteristics in Spanish listed companies and their impact on the likelihood of financial distress. An empirical study was conducted between 2007 and 2012 using a matched-pairs research design with 308 observations, with half of them classified as distressed and non-distressed. Based on the previous study by Pindado, Rodrigues, and De la Torre (2008, a broader concept of bankruptcy is used to define business failure. Employing several conditional logistic models, as well as to other previous studies on bankruptcy, the results confirm that in difficult situations prior to bankruptcy, the impact of board ownership and proportion of independent directors on business failure likelihood are similar to those exerted in more extreme situations. These results go one step further, to offer a negative relationship between board size and the likelihood of financial distress. This result is interpreted as a form of creating diversity and to improve the access to the information and resources, especially in contexts where the ownership is highly concentrated and large shareholders have a great power to influence the board structure. However, the results confirm that ownership concentration does not have a significant impact on financial distress likelihood in the Spanish context. It is argued that large shareholders are passive as regards an enhanced monitoring of management and, alternatively, they do not have enough incentives to hold back the financial distress. These findings have important implications in the Spanish context, where several changes in the regulatory listing requirements have been carried out with respect to corporate governance, and where there is no empirical evidence regarding this respect.
Empirical Likelihood in Nonignorable Covariate-Missing Data Problems.
Xie, Yanmei; Zhang, Biao
2017-04-20
Missing covariate data occurs often in regression analysis, which frequently arises in the health and social sciences as well as in survey sampling. We study methods for the analysis of a nonignorable covariate-missing data problem in an assumed conditional mean function when some covariates are completely observed but other covariates are missing for some subjects. We adopt the semiparametric perspective of Bartlett et al. (Improving upon the efficiency of complete case analysis when covariates are MNAR. Biostatistics 2014;15:719-30) on regression analyses with nonignorable missing covariates, in which they have introduced the use of two working models, the working probability model of missingness and the working conditional score model. In this paper, we study an empirical likelihood approach to nonignorable covariate-missing data problems with the objective of effectively utilizing the two working models in the analysis of covariate-missing data. We propose a unified approach to constructing a system of unbiased estimating equations, where there are more equations than unknown parameters of interest. One useful feature of these unbiased estimating equations is that they naturally incorporate the incomplete data into the data analysis, making it possible to seek efficient estimation of the parameter of interest even when the working regression function is not specified to be the optimal regression function. We apply the general methodology of empirical likelihood to optimally combine these unbiased estimating equations. We propose three maximum empirical likelihood estimators of the underlying regression parameters and compare their efficiencies with other existing competitors. We present a simulation study to compare the finite-sample performance of various methods with respect to bias, efficiency, and robustness to model misspecification. The proposed empirical likelihood method is also illustrated by an analysis of a data set from the US National Health and
Likelihood functions for the analysis of single-molecule binned photon sequences
Energy Technology Data Exchange (ETDEWEB)
Gopich, Irina V., E-mail: irinag@niddk.nih.gov [Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD 20892 (United States)
2012-03-02
Graphical abstract: Folding of a protein with attached fluorescent dyes, the underlying conformational trajectory of interest, and the observed binned photon trajectory. Highlights: Black-Right-Pointing-Pointer A sequence of photon counts can be analyzed using a likelihood function. Black-Right-Pointing-Pointer The exact likelihood function for a two-state kinetic model is provided. Black-Right-Pointing-Pointer Several approximations are considered for an arbitrary kinetic model. Black-Right-Pointing-Pointer Improved likelihood functions are obtained to treat sequences of FRET efficiencies. - Abstract: We consider the analysis of a class of experiments in which the number of photons in consecutive time intervals is recorded. Sequence of photon counts or, alternatively, of FRET efficiencies can be studied using likelihood-based methods. For a kinetic model of the conformational dynamics and state-dependent Poisson photon statistics, the formalism to calculate the exact likelihood that this model describes such sequences of photons or FRET efficiencies is developed. Explicit analytic expressions for the likelihood function for a two-state kinetic model are provided. The important special case when conformational dynamics are so slow that at most a single transition occurs in a time bin is considered. By making a series of approximations, we eventually recover the likelihood function used in hidden Markov models. In this way, not only is insight gained into the range of validity of this procedure, but also an improved likelihood function can be obtained.
Communicating likelihoods and probabilities in forecasts of volcanic eruptions
Doyle, Emma E. H.; McClure, John; Johnston, David M.; Paton, Douglas
2014-02-01
The issuing of forecasts and warnings of natural hazard events, such as volcanic eruptions, earthquake aftershock sequences and extreme weather often involves the use of probabilistic terms, particularly when communicated by scientific advisory groups to key decision-makers, who can differ greatly in relative expertise and function in the decision making process. Recipients may also differ in their perception of relative importance of political and economic influences on interpretation. Consequently, the interpretation of these probabilistic terms can vary greatly due to the framing of the statements, and whether verbal or numerical terms are used. We present a review from the psychology literature on how the framing of information influences communication of these probability terms. It is also unclear as to how people rate their perception of an event's likelihood throughout a time frame when a forecast time window is stated. Previous research has identified that, when presented with a 10-year time window forecast, participants viewed the likelihood of an event occurring ‘today’ as being of less than that in year 10. Here we show that this skew in perception also occurs for short-term time windows (under one week) that are of most relevance for emergency warnings. In addition, unlike the long-time window statements, the use of the phrasing “within the next…” instead of “in the next…” does not mitigate this skew, nor do we observe significant differences between the perceived likelihoods of scientists and non-scientists. This finding suggests that effects occurring due to the shorter time window may be ‘masking’ any differences in perception due to wording or career background observed for long-time window forecasts. These results have implications for scientific advice, warning forecasts, emergency management decision-making, and public information as any skew in perceived event likelihood towards the end of a forecast time window may result in
Dimension-Independent Likelihood-Informed MCMC
Cui, Tiangang; Law, Kody; Marzouk, Youssef
2015-01-01
Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters, which in principle can be described as functions. By exploiting low-dimensional structure in the change from prior to posterior [distributions], we introduce a suite of MCMC samplers that can adapt to the complex structure of the posterior distribution, yet are well-defined on function space. Posterior sampling in nonlinear inverse problems arising from various partial di erential equations and also a stochastic differential equation are used to demonstrate the e ciency of these dimension-independent likelihood-informed samplers.
Multi-Channel Maximum Likelihood Pitch Estimation
DEFF Research Database (Denmark)
Christensen, Mads Græsbøll
2012-01-01
In this paper, a method for multi-channel pitch estimation is proposed. The method is a maximum likelihood estimator and is based on a parametric model where the signals in the various channels share the same fundamental frequency but can have different amplitudes, phases, and noise characteristics....... This essentially means that the model allows for different conditions in the various channels, like different signal-to-noise ratios, microphone characteristics and reverberation. Moreover, the method does not assume that a certain array structure is used but rather relies on a more general model and is hence...
Dimension-Independent Likelihood-Informed MCMC
Cui, Tiangang
2015-01-07
Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters, which in principle can be described as functions. By exploiting low-dimensional structure in the change from prior to posterior [distributions], we introduce a suite of MCMC samplers that can adapt to the complex structure of the posterior distribution, yet are well-defined on function space. Posterior sampling in nonlinear inverse problems arising from various partial di erential equations and also a stochastic differential equation are used to demonstrate the e ciency of these dimension-independent likelihood-informed samplers.
Approximate maximum parsimony and ancestral maximum likelihood.
Alon, Noga; Chor, Benny; Pardi, Fabio; Rapoport, Anat
2010-01-01
We explore the maximum parsimony (MP) and ancestral maximum likelihood (AML) criteria in phylogenetic tree reconstruction. Both problems are NP-hard, so we seek approximate solutions. We formulate the two problems as Steiner tree problems under appropriate distances. The gist of our approach is the succinct characterization of Steiner trees for a small number of leaves for the two distances. This enables the use of known Steiner tree approximation algorithms. The approach leads to a 16/9 approximation ratio for AML and asymptotically to a 1.55 approximation ratio for MP.
Elemental composition of cosmic rays using a maximum likelihood method
International Nuclear Information System (INIS)
Ruddick, K.
1996-01-01
We present a progress report on our attempts to determine the composition of cosmic rays in the knee region of the energy spectrum. We have used three different devices to measure properties of the extensive air showers produced by primary cosmic rays: the Soudan 2 underground detector measures the muon flux deep underground, a proportional tube array samples shower density at the surface of the earth, and a Cherenkov array observes light produced high in the atmosphere. We have begun maximum likelihood fits to these measurements with the hope of determining the nuclear mass number A on an event by event basis. (orig.)
Improved Likelihood Function in Particle-based IR Eye Tracking
DEFF Research Database (Denmark)
Satria, R.; Sorensen, J.; Hammoud, R.
2005-01-01
In this paper we propose a log likelihood-ratio function of foreground and background models used in a particle filter to track the eye region in dark-bright pupil image sequences. This model fuses information from both dark and bright pupil images and their difference image into one model. Our...... enhanced tracker overcomes the issues of prior selection of static thresholds during the detection of feature observations in the bright-dark difference images. The auto-initialization process is performed using cascaded classifier trained using adaboost and adapted to IR eye images. Experiments show good...
Maximum Likelihood Reconstruction for Magnetic Resonance Fingerprinting.
Zhao, Bo; Setsompop, Kawin; Ye, Huihui; Cauley, Stephen F; Wald, Lawrence L
2016-08-01
This paper introduces a statistical estimation framework for magnetic resonance (MR) fingerprinting, a recently proposed quantitative imaging paradigm. Within this framework, we present a maximum likelihood (ML) formalism to estimate multiple MR tissue parameter maps directly from highly undersampled, noisy k-space data. A novel algorithm, based on variable splitting, the alternating direction method of multipliers, and the variable projection method, is developed to solve the resulting optimization problem. Representative results from both simulations and in vivo experiments demonstrate that the proposed approach yields significantly improved accuracy in parameter estimation, compared to the conventional MR fingerprinting reconstruction. Moreover, the proposed framework provides new theoretical insights into the conventional approach. We show analytically that the conventional approach is an approximation to the ML reconstruction; more precisely, it is exactly equivalent to the first iteration of the proposed algorithm for the ML reconstruction, provided that a gridding reconstruction is used as an initialization.
Subtracting and Fitting Histograms using Profile Likelihood
D'Almeida, F M L
2008-01-01
It is known that many interesting signals expected at LHC are of unknown shape and strongly contaminated by background events. These signals will be dif cult to detect during the rst years of LHC operation due to the initial low luminosity. In this work, one presents a method of subtracting histograms based on the pro le likelihood function when the background is previously estimated by Monte Carlo events and one has low statistics. Estimators for the signal in each bin of the histogram difference are calculated so as limits for the signals with 68.3% of Con dence Level in a low statistics case when one has a exponential background and a Gaussian signal. The method can also be used to t histograms when the signal shape is known. Our results show a good performance and avoid the problem of negative values when subtracting histograms.
A maximum likelihood framework for protein design
Directory of Open Access Journals (Sweden)
Philippe Hervé
2006-06-01
Full Text Available Abstract Background The aim of protein design is to predict amino-acid sequences compatible with a given target structure. Traditionally envisioned as a purely thermodynamic question, this problem can also be understood in a wider context, where additional constraints are captured by learning the sequence patterns displayed by natural proteins of known conformation. In this latter perspective, however, we still need a theoretical formalization of the question, leading to general and efficient learning methods, and allowing for the selection of fast and accurate objective functions quantifying sequence/structure compatibility. Results We propose a formulation of the protein design problem in terms of model-based statistical inference. Our framework uses the maximum likelihood principle to optimize the unknown parameters of a statistical potential, which we call an inverse potential to contrast with classical potentials used for structure prediction. We propose an implementation based on Markov chain Monte Carlo, in which the likelihood is maximized by gradient descent and is numerically estimated by thermodynamic integration. The fit of the models is evaluated by cross-validation. We apply this to a simple pairwise contact potential, supplemented with a solvent-accessibility term, and show that the resulting models have a better predictive power than currently available pairwise potentials. Furthermore, the model comparison method presented here allows one to measure the relative contribution of each component of the potential, and to choose the optimal number of accessibility classes, which turns out to be much higher than classically considered. Conclusion Altogether, this reformulation makes it possible to test a wide diversity of models, using different forms of potentials, or accounting for other factors than just the constraint of thermodynamic stability. Ultimately, such model-based statistical analyses may help to understand the forces
Zero-inflated Poisson model based likelihood ratio test for drug safety signal detection.
Huang, Lan; Zheng, Dan; Zalkikar, Jyoti; Tiwari, Ram
2017-02-01
In recent decades, numerous methods have been developed for data mining of large drug safety databases, such as Food and Drug Administration's (FDA's) Adverse Event Reporting System, where data matrices are formed by drugs such as columns and adverse events as rows. Often, a large number of cells in these data matrices have zero cell counts and some of them are "true zeros" indicating that the drug-adverse event pairs cannot occur, and these zero counts are distinguished from the other zero counts that are modeled zero counts and simply indicate that the drug-adverse event pairs have not occurred yet or have not been reported yet. In this paper, a zero-inflated Poisson model based likelihood ratio test method is proposed to identify drug-adverse event pairs that have disproportionately high reporting rates, which are also called signals. The maximum likelihood estimates of the model parameters of zero-inflated Poisson model based likelihood ratio test are obtained using the expectation and maximization algorithm. The zero-inflated Poisson model based likelihood ratio test is also modified to handle the stratified analyses for binary and categorical covariates (e.g. gender and age) in the data. The proposed zero-inflated Poisson model based likelihood ratio test method is shown to asymptotically control the type I error and false discovery rate, and its finite sample performance for signal detection is evaluated through a simulation study. The simulation results show that the zero-inflated Poisson model based likelihood ratio test method performs similar to Poisson model based likelihood ratio test method when the estimated percentage of true zeros in the database is small. Both the zero-inflated Poisson model based likelihood ratio test and likelihood ratio test methods are applied to six selected drugs, from the 2006 to 2011 Adverse Event Reporting System database, with varying percentages of observed zero-count cells.
Alsing, Justin; Wandelt, Benjamin; Feeney, Stephen
2018-03-01
Many statistical models in cosmology can be simulated forwards but have intractable likelihood functions. Likelihood-free inference methods allow us to perform Bayesian inference from these models using only forward simulations, free from any likelihood assumptions or approximations. Likelihood-free inference generically involves simulating mock data and comparing to the observed data; this comparison in data-space suffers from the curse of dimensionality and requires compression of the data to a small number of summary statistics to be tractable. In this paper we use massive asymptotically-optimal data compression to reduce the dimensionality of the data-space to just one number per parameter, providing a natural and optimal framework for summary statistic choice for likelihood-free inference. Secondly, we present the first cosmological application of Density Estimation Likelihood-Free Inference (DELFI), which learns a parameterized model for joint distribution of data and parameters, yielding both the parameter posterior and the model evidence. This approach is conceptually simple, requires less tuning than traditional Approximate Bayesian Computation approaches to likelihood-free inference and can give high-fidelity posteriors from orders of magnitude fewer forward simulations. As an additional bonus, it enables parameter inference and Bayesian model comparison simultaneously. We demonstrate Density Estimation Likelihood-Free Inference with massive data compression on an analysis of the joint light-curve analysis supernova data, as a simple validation case study. We show that high-fidelity posterior inference is possible for full-scale cosmological data analyses with as few as ˜104 simulations, with substantial scope for further improvement, demonstrating the scalability of likelihood-free inference to large and complex cosmological datasets.
Simulation-based marginal likelihood for cluster strong lensing cosmology
Killedar, M.; Borgani, S.; Fabjan, D.; Dolag, K.; Granato, G.; Meneghetti, M.; Planelles, S.; Ragone-Figueroa, C.
2018-01-01
Comparisons between observed and predicted strong lensing properties of galaxy clusters have been routinely used to claim either tension or consistency with Λ cold dark matter cosmology. However, standard approaches to such cosmological tests are unable to quantify the preference for one cosmology over another. We advocate approximating the relevant Bayes factor using a marginal likelihood that is based on the following summary statistic: the posterior probability distribution function for the parameters of the scaling relation between Einstein radii and cluster mass, α and β. We demonstrate, for the first time, a method of estimating the marginal likelihood using the X-ray selected z > 0.5 Massive Cluster Survey clusters as a case in point and employing both N-body and hydrodynamic simulations of clusters. We investigate the uncertainty in this estimate and consequential ability to compare competing cosmologies, which arises from incomplete descriptions of baryonic processes, discrepancies in cluster selection criteria, redshift distribution and dynamical state. The relation between triaxial cluster masses at various overdensities provides a promising alternative to the strong lensing test.
Likelihood analysis of the minimal AMSB model
Energy Technology Data Exchange (ETDEWEB)
Bagnaschi, E.; Weiglein, G. [DESY, Hamburg (Germany); Borsato, M.; Chobanova, V.; Lucio, M.; Santos, D.M. [Universidade de Santiago de Compostela, Santiago de Compostela (Spain); Sakurai, K. [Institute for Particle Physics Phenomenology, University of Durham, Science Laboratories, Department of Physics, Durham (United Kingdom); University of Warsaw, Faculty of Physics, Institute of Theoretical Physics, Warsaw (Poland); Buchmueller, O.; Citron, M.; Costa, J.C.; Richards, A. [Imperial College, High Energy Physics Group, Blackett Laboratory, London (United Kingdom); Cavanaugh, R. [Fermi National Accelerator Laboratory, Batavia, IL (United States); University of Illinois at Chicago, Physics Department, Chicago, IL (United States); De Roeck, A. [Experimental Physics Department, CERN, Geneva (Switzerland); Antwerp University, Wilrijk (Belgium); Dolan, M.J. [School of Physics, University of Melbourne, ARC Centre of Excellence for Particle Physics at the Terascale, Melbourne (Australia); Ellis, J.R. [King' s College London, Theoretical Particle Physics and Cosmology Group, Department of Physics, London (United Kingdom); CERN, Theoretical Physics Department, Geneva (Switzerland); Flaecher, H. [University of Bristol, H.H. Wills Physics Laboratory, Bristol (United Kingdom); Heinemeyer, S. [Campus of International Excellence UAM+CSIC, Madrid (Spain); Instituto de Fisica Teorica UAM-CSIC, Madrid (Spain); Instituto de Fisica de Cantabria (CSIC-UC), Cantabria (Spain); Isidori, G. [Physik-Institut, Universitaet Zuerich, Zurich (Switzerland); Luo, F. [Kavli IPMU (WPI), UTIAS, The University of Tokyo, Kashiwa, Chiba (Japan); Olive, K.A. [School of Physics and Astronomy, University of Minnesota, William I. Fine Theoretical Physics Institute, Minneapolis, MN (United States)
2017-04-15
We perform a likelihood analysis of the minimal anomaly-mediated supersymmetry-breaking (mAMSB) model using constraints from cosmology and accelerator experiments. We find that either a wino-like or a Higgsino-like neutralino LSP, χ{sup 0}{sub 1}, may provide the cold dark matter (DM), both with similar likelihoods. The upper limit on the DM density from Planck and other experiments enforces m{sub χ{sup 0}{sub 1}}
Dimension-independent likelihood-informed MCMC
Cui, Tiangang
2015-10-08
Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters that represent the discretization of an underlying function. This work introduces a family of Markov chain Monte Carlo (MCMC) samplers that can adapt to the particular structure of a posterior distribution over functions. Two distinct lines of research intersect in the methods developed here. First, we introduce a general class of operator-weighted proposal distributions that are well defined on function space, such that the performance of the resulting MCMC samplers is independent of the discretization of the function. Second, by exploiting local Hessian information and any associated low-dimensional structure in the change from prior to posterior distributions, we develop an inhomogeneous discretization scheme for the Langevin stochastic differential equation that yields operator-weighted proposals adapted to the non-Gaussian structure of the posterior. The resulting dimension-independent and likelihood-informed (DILI) MCMC samplers may be useful for a large class of high-dimensional problems where the target probability measure has a density with respect to a Gaussian reference measure. Two nonlinear inverse problems are used to demonstrate the efficiency of these DILI samplers: an elliptic PDE coefficient inverse problem and path reconstruction in a conditioned diffusion.
Reducing the likelihood of long tennis matches.
Barnett, Tristan; Alan, Brown; Pollard, Graham
2006-01-01
Long matches can cause problems for tournaments. For example, the starting times of subsequent matches can be substantially delayed causing inconvenience to players, spectators, officials and television scheduling. They can even be seen as unfair in the tournament setting when the winner of a very long match, who may have negative aftereffects from such a match, plays the winner of an average or shorter length match in the next round. Long matches can also lead to injuries to the participating players. One factor that can lead to long matches is the use of the advantage set as the fifth set, as in the Australian Open, the French Open and Wimbledon. Another factor is long rallies and a greater than average number of points per game. This tends to occur more frequently on the slower surfaces such as at the French Open. The mathematical method of generating functions is used to show that the likelihood of long matches can be substantially reduced by using the tiebreak game in the fifth set, or more effectively by using a new type of game, the 50-40 game, throughout the match. Key PointsThe cumulant generating function has nice properties for calculating the parameters of distributions in a tennis matchA final tiebreaker set reduces the length of matches as currently being used in the US OpenA new 50-40 game reduces the length of matches whilst maintaining comparable probabilities for the better player to win the match.
Dimension-independent likelihood-informed MCMC
Cui, Tiangang; Law, Kody; Marzouk, Youssef M.
2015-01-01
Many Bayesian inference problems require exploring the posterior distribution of high-dimensional parameters that represent the discretization of an underlying function. This work introduces a family of Markov chain Monte Carlo (MCMC) samplers that can adapt to the particular structure of a posterior distribution over functions. Two distinct lines of research intersect in the methods developed here. First, we introduce a general class of operator-weighted proposal distributions that are well defined on function space, such that the performance of the resulting MCMC samplers is independent of the discretization of the function. Second, by exploiting local Hessian information and any associated low-dimensional structure in the change from prior to posterior distributions, we develop an inhomogeneous discretization scheme for the Langevin stochastic differential equation that yields operator-weighted proposals adapted to the non-Gaussian structure of the posterior. The resulting dimension-independent and likelihood-informed (DILI) MCMC samplers may be useful for a large class of high-dimensional problems where the target probability measure has a density with respect to a Gaussian reference measure. Two nonlinear inverse problems are used to demonstrate the efficiency of these DILI samplers: an elliptic PDE coefficient inverse problem and path reconstruction in a conditioned diffusion.
Maximum likelihood window for time delay estimation
International Nuclear Information System (INIS)
Lee, Young Sup; Yoon, Dong Jin; Kim, Chi Yup
2004-01-01
Time delay estimation for the detection of leak location in underground pipelines is critically important. Because the exact leak location depends upon the precision of the time delay between sensor signals due to leak noise and the speed of elastic waves, the research on the estimation of time delay has been one of the key issues in leak lovating with the time arrival difference method. In this study, an optimal Maximum Likelihood window is considered to obtain a better estimation of the time delay. This method has been proved in experiments, which can provide much clearer and more precise peaks in cross-correlation functions of leak signals. The leak location error has been less than 1 % of the distance between sensors, for example the error was not greater than 3 m for 300 m long underground pipelines. Apart from the experiment, an intensive theoretical analysis in terms of signal processing has been described. The improved leak locating with the suggested method is due to the windowing effect in frequency domain, which offers a weighting in significant frequencies.
Maximum likelihood versus likelihood-free quantum system identification in the atom maser
International Nuclear Information System (INIS)
Catana, Catalin; Kypraios, Theodore; Guţă, Mădălin
2014-01-01
We consider the problem of estimating a dynamical parameter of a Markovian quantum open system (the atom maser), by performing continuous time measurements in the system's output (outgoing atoms). Two estimation methods are investigated and compared. Firstly, the maximum likelihood estimator (MLE) takes into account the full measurement data and is asymptotically optimal in terms of its mean square error. Secondly, the ‘likelihood-free’ method of approximate Bayesian computation (ABC) produces an approximation of the posterior distribution for a given set of summary statistics, by sampling trajectories at different parameter values and comparing them with the measurement data via chosen statistics. Building on previous results which showed that atom counts are poor statistics for certain values of the Rabi angle, we apply MLE to the full measurement data and estimate its Fisher information. We then select several correlation statistics such as waiting times, distribution of successive identical detections, and use them as input of the ABC algorithm. The resulting posterior distribution follows closely the data likelihood, showing that the selected statistics capture ‘most’ statistical information about the Rabi angle. (paper)
Ning, Jing; Chen, Yong; Piao, Jin
2017-07-01
Publication bias occurs when the published research results are systematically unrepresentative of the population of studies that have been conducted, and is a potential threat to meaningful meta-analysis. The Copas selection model provides a flexible framework for correcting estimates and offers considerable insight into the publication bias. However, maximizing the observed likelihood under the Copas selection model is challenging because the observed data contain very little information on the latent variable. In this article, we study a Copas-like selection model and propose an expectation-maximization (EM) algorithm for estimation based on the full likelihood. Empirical simulation studies show that the EM algorithm and its associated inferential procedure performs well and avoids the non-convergence problem when maximizing the observed likelihood. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Accelerated maximum likelihood parameter estimation for stochastic biochemical systems
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Daigle Bernie J
2012-05-01
Full Text Available Abstract Background A prerequisite for the mechanistic simulation of a biochemical system is detailed knowledge of its kinetic parameters. Despite recent experimental advances, the estimation of unknown parameter values from observed data is still a bottleneck for obtaining accurate simulation results. Many methods exist for parameter estimation in deterministic biochemical systems; methods for discrete stochastic systems are less well developed. Given the probabilistic nature of stochastic biochemical models, a natural approach is to choose parameter values that maximize the probability of the observed data with respect to the unknown parameters, a.k.a. the maximum likelihood parameter estimates (MLEs. MLE computation for all but the simplest models requires the simulation of many system trajectories that are consistent with experimental data. For models with unknown parameters, this presents a computational challenge, as the generation of consistent trajectories can be an extremely rare occurrence. Results We have developed Monte Carlo Expectation-Maximization with Modified Cross-Entropy Method (MCEM2: an accelerated method for calculating MLEs that combines advances in rare event simulation with a computationally efficient version of the Monte Carlo expectation-maximization (MCEM algorithm. Our method requires no prior knowledge regarding parameter values, and it automatically provides a multivariate parameter uncertainty estimate. We applied the method to five stochastic systems of increasing complexity, progressing from an analytically tractable pure-birth model to a computationally demanding model of yeast-polarization. Our results demonstrate that MCEM2 substantially accelerates MLE computation on all tested models when compared to a stand-alone version of MCEM. Additionally, we show how our method identifies parameter values for certain classes of models more accurately than two recently proposed computationally efficient methods
The behavior of the likelihood ratio test for testing missingness
Hens, Niel; Aerts, Marc; Molenberghs, Geert; Thijs, Herbert
2003-01-01
To asses the sensitivity of conclusions to model choices in the context of selection models for non-random dropout, one can oppose the different missing mechanisms to each other; e.g. by the likelihood ratio tests. The finite sample behavior of the null distribution and the power of the likelihood ratio test is studied under a variety of missingness mechanisms. missing data; sensitivity analysis; likelihood ratio test; missing mechanisms
Penalized Maximum Likelihood Estimation for univariate normal mixture distributions
International Nuclear Information System (INIS)
Ridolfi, A.; Idier, J.
2001-01-01
Due to singularities of the likelihood function, the maximum likelihood approach for the estimation of the parameters of normal mixture models is an acknowledged ill posed optimization problem. Ill posedness is solved by penalizing the likelihood function. In the Bayesian framework, it amounts to incorporating an inverted gamma prior in the likelihood function. A penalized version of the EM algorithm is derived, which is still explicit and which intrinsically assures that the estimates are not singular. Numerical evidence of the latter property is put forward with a test
Pan, Zhen; Anderes, Ethan; Knox, Lloyd
2018-05-01
One of the major targets for next-generation cosmic microwave background (CMB) experiments is the detection of the primordial B-mode signal. Planning is under way for Stage-IV experiments that are projected to have instrumental noise small enough to make lensing and foregrounds the dominant source of uncertainty for estimating the tensor-to-scalar ratio r from polarization maps. This makes delensing a crucial part of future CMB polarization science. In this paper we present a likelihood method for estimating the tensor-to-scalar ratio r from CMB polarization observations, which combines the benefits of a full-scale likelihood approach with the tractability of the quadratic delensing technique. This method is a pixel space, all order likelihood analysis of the quadratic delensed B modes, and it essentially builds upon the quadratic delenser by taking into account all order lensing and pixel space anomalies. Its tractability relies on a crucial factorization of the pixel space covariance matrix of the polarization observations which allows one to compute the full Gaussian approximate likelihood profile, as a function of r , at the same computational cost of a single likelihood evaluation.
Efficient Detection of Repeating Sites to Accelerate Phylogenetic Likelihood Calculations.
Kobert, K; Stamatakis, A; Flouri, T
2017-03-01
The phylogenetic likelihood function (PLF) is the major computational bottleneck in several applications of evolutionary biology such as phylogenetic inference, species delimitation, model selection, and divergence times estimation. Given the alignment, a tree and the evolutionary model parameters, the likelihood function computes the conditional likelihood vectors for every node of the tree. Vector entries for which all input data are identical result in redundant likelihood operations which, in turn, yield identical conditional values. Such operations can be omitted for improving run-time and, using appropriate data structures, reducing memory usage. We present a fast, novel method for identifying and omitting such redundant operations in phylogenetic likelihood calculations, and assess the performance improvement and memory savings attained by our method. Using empirical and simulated data sets, we show that a prototype implementation of our method yields up to 12-fold speedups and uses up to 78% less memory than one of the fastest and most highly tuned implementations of the PLF currently available. Our method is generic and can seamlessly be integrated into any phylogenetic likelihood implementation. [Algorithms; maximum likelihood; phylogenetic likelihood function; phylogenetics]. © The Author(s) 2016. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.
Planck intermediate results: XVI. Profile likelihoods for cosmological parameters
DEFF Research Database (Denmark)
Bartlett, J.G.; Cardoso, J.-F.; Delabrouille, J.
2014-01-01
We explore the 2013 Planck likelihood function with a high-precision multi-dimensional minimizer (Minuit). This allows a refinement of the CDM best-fit solution with respect to previously-released results, and the construction of frequentist confidence intervals using profile likelihoods. The agr...
Planck 2013 results. XV. CMB power spectra and likelihood
DEFF Research Database (Denmark)
Tauber, Jan; Bartlett, J.G.; Bucher, M.
2014-01-01
This paper presents the Planck 2013 likelihood, a complete statistical description of the two-point correlation function of the CMB temperature fluctuations that accounts for all known relevant uncertainties, both instrumental and astrophysical in nature. We use this likelihood to derive our best...
The modified signed likelihood statistic and saddlepoint approximations
DEFF Research Database (Denmark)
Jensen, Jens Ledet
1992-01-01
SUMMARY: For a number of tests in exponential families we show that the use of a normal approximation to the modified signed likelihood ratio statistic r * is equivalent to the use of a saddlepoint approximation. This is also true in a large deviation region where the signed likelihood ratio...... statistic r is of order √ n. © 1992 Biometrika Trust....
Likelihood analysis of parity violation in the compound nucleus
International Nuclear Information System (INIS)
Bowman, D.; Sharapov, E.
1993-01-01
We discuss the determination of the root mean-squared matrix element of the parity-violating interaction between compound-nuclear states using likelihood analysis. We briefly review the relevant features of the statistical model of the compound nucleus and the formalism of likelihood analysis. We then discuss the application of likelihood analysis to data on panty-violating longitudinal asymmetries. The reliability of the extracted value of the matrix element and errors assigned to the matrix element is stressed. We treat the situations where the spins of the p-wave resonances are not known and known using experimental data and Monte Carlo techniques. We conclude that likelihood analysis provides a reliable way to determine M and its confidence interval. We briefly discuss some problems associated with the normalization of the likelihood function
The Likelihood of Recent Record Warmth.
Mann, Michael E; Rahmstorf, Stefan; Steinman, Byron A; Tingley, Martin; Miller, Sonya K
2016-01-25
2014 was nominally the warmest year on record for both the globe and northern hemisphere based on historical records spanning the past one and a half centuries. It was the latest in a recent run of record temperatures spanning the past decade and a half. Press accounts reported odds as low as one-in-650 million that the observed run of global temperature records would be expected to occur in the absence of human-caused global warming. Press reports notwithstanding, the question of how likely observed temperature records may have have been both with and without human influence is interesting in its own right. Here we attempt to address that question using a semi-empirical approach that combines the latest (CMIP5) climate model simulations with observations of global and hemispheric mean temperature. We find that individual record years and the observed runs of record-setting temperatures were extremely unlikely to have occurred in the absence of human-caused climate change, though not nearly as unlikely as press reports have suggested. These same record temperatures were, by contrast, quite likely to have occurred in the presence of anthropogenic climate forcing.
Saavedra, Serguei; Rohr, Rudolf P; Fortuna, Miguel A; Selva, Nuria; Bascompte, Jordi
2016-04-01
Many of the observed species interactions embedded in ecological communities are not permanent, but are characterized by temporal changes that are observed along with abiotic and biotic variations. While work has been done describing and quantifying these changes, little is known about their consequences for species coexistence. Here, we investigate the extent to which changes of species composition impact the likelihood of persistence of the predator-prey community in the highly seasonal Białowieza Primeval Forest (northeast Poland), and the extent to which seasonal changes of species interactions (predator diet) modulate the expected impact. This likelihood is estimated extending recent developments on the study of structural stability in ecological communities. We find that the observed species turnover strongly varies the likelihood of community persistence between summer and winter. Importantly, we demonstrate that the observed seasonal interaction changes minimize the variation in the likelihood of persistence associated with species turnover across the year. We find that these community dynamics can be explained as the coupling of individual species to their environment by minimizing both the variation in persistence conditions and the interaction changes between seasons. Our results provide a homeostatic explanation for seasonal species interactions and suggest that monitoring the association of interactions changes with the level of variation in community dynamics can provide a good indicator of the response of species to environmental pressures.
Kuhnt, S.
2004-01-01
Observed cell counts in contingency tables are perceived as outliers if they have low probability under an anticipated loglinear Poisson model. New procedures for the identification of such outliers are derived using the classical maximum likelihood estimator and an estimator based on the L1 norm.
Cox regression with missing covariate data using a modified partial likelihood method
DEFF Research Database (Denmark)
Martinussen, Torben; Holst, Klaus K.; Scheike, Thomas H.
2016-01-01
Missing covariate values is a common problem in survival analysis. In this paper we propose a novel method for the Cox regression model that is close to maximum likelihood but avoids the use of the EM-algorithm. It exploits that the observed hazard function is multiplicative in the baseline hazard...
Efficient algorithms for maximum likelihood decoding in the surface code
Bravyi, Sergey; Suchara, Martin; Vargo, Alexander
2014-09-01
We describe two implementations of the optimal error correction algorithm known as the maximum likelihood decoder (MLD) for the two-dimensional surface code with a noiseless syndrome extraction. First, we show how to implement MLD exactly in time O (n2), where n is the number of code qubits. Our implementation uses a reduction from MLD to simulation of matchgate quantum circuits. This reduction however requires a special noise model with independent bit-flip and phase-flip errors. Secondly, we show how to implement MLD approximately for more general noise models using matrix product states (MPS). Our implementation has running time O (nχ3), where χ is a parameter that controls the approximation precision. The key step of our algorithm, borrowed from the density matrix renormalization-group method, is a subroutine for contracting a tensor network on the two-dimensional grid. The subroutine uses MPS with a bond dimension χ to approximate the sequence of tensors arising in the course of contraction. We benchmark the MPS-based decoder against the standard minimum weight matching decoder observing a significant reduction of the logical error probability for χ ≥4.
Maximum likelihood pedigree reconstruction using integer linear programming.
Cussens, James; Bartlett, Mark; Jones, Elinor M; Sheehan, Nuala A
2013-01-01
Large population biobanks of unrelated individuals have been highly successful in detecting common genetic variants affecting diseases of public health concern. However, they lack the statistical power to detect more modest gene-gene and gene-environment interaction effects or the effects of rare variants for which related individuals are ideally required. In reality, most large population studies will undoubtedly contain sets of undeclared relatives, or pedigrees. Although a crude measure of relatedness might sometimes suffice, having a good estimate of the true pedigree would be much more informative if this could be obtained efficiently. Relatives are more likely to share longer haplotypes around disease susceptibility loci and are hence biologically more informative for rare variants than unrelated cases and controls. Distant relatives are arguably more useful for detecting variants with small effects because they are less likely to share masking environmental effects. Moreover, the identification of relatives enables appropriate adjustments of statistical analyses that typically assume unrelatedness. We propose to exploit an integer linear programming optimisation approach to pedigree learning, which is adapted to find valid pedigrees by imposing appropriate constraints. Our method is not restricted to small pedigrees and is guaranteed to return a maximum likelihood pedigree. With additional constraints, we can also search for multiple high-probability pedigrees and thus account for the inherent uncertainty in any particular pedigree reconstruction. The true pedigree is found very quickly by comparison with other methods when all individuals are observed. Extensions to more complex problems seem feasible. © 2012 Wiley Periodicals, Inc.
Maximum likelihood approach for several stochastic volatility models
International Nuclear Information System (INIS)
Camprodon, Jordi; Perelló, Josep
2012-01-01
Volatility measures the amplitude of price fluctuations. Despite it being one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method which assumes that price and volatility follow a two-dimensional diffusion process where volatility is the stochastic diffusion coefficient of the log-price dynamics. We apply this method to the simplest versions of the expOU, the OU and the Heston stochastic volatility models and we study their performance in terms of the log-price probability, the volatility probability, and its Mean First-Passage Time. The approach has some predictive power on the future returns amplitude by only knowing the current volatility. The assumed models do not consider long-range volatility autocorrelation and the asymmetric return-volatility cross-correlation but the method still yields very naturally these two important stylized facts. We apply the method to different market indices and with a good performance in all cases. (paper)
Likelihood ratio model for classification of forensic evidence
Energy Technology Data Exchange (ETDEWEB)
Zadora, G., E-mail: gzadora@ies.krakow.pl [Institute of Forensic Research, Westerplatte 9, 31-033 Krakow (Poland); Neocleous, T., E-mail: tereza@stats.gla.ac.uk [University of Glasgow, Department of Statistics, 15 University Gardens, Glasgow G12 8QW (United Kingdom)
2009-05-29
One of the problems of analysis of forensic evidence such as glass fragments, is the determination of their use-type category, e.g. does a glass fragment originate from an unknown window or container? Very small glass fragments arise during various accidents and criminal offences, and could be carried on the clothes, shoes and hair of participants. It is therefore necessary to obtain information on their physicochemical composition in order to solve the classification problem. Scanning Electron Microscopy coupled with an Energy Dispersive X-ray Spectrometer and the Glass Refractive Index Measurement method are routinely used in many forensic institutes for the investigation of glass. A natural form of glass evidence evaluation for forensic purposes is the likelihood ratio-LR = p(E|H{sub 1})/p(E|H{sub 2}). The main aim of this paper was to study the performance of LR models for glass object classification which considered one or two sources of data variability, i.e. between-glass-object variability and(or) within-glass-object variability. Within the proposed model a multivariate kernel density approach was adopted for modelling the between-object distribution and a multivariate normal distribution was adopted for modelling within-object distributions. Moreover, a graphical method of estimating the dependence structure was employed to reduce the highly multivariate problem to several lower-dimensional problems. The performed analysis showed that the best likelihood model was the one which allows to include information about between and within-object variability, and with variables derived from elemental compositions measured by SEM-EDX, and refractive values determined before (RI{sub b}) and after (RI{sub a}) the annealing process, in the form of dRI = log{sub 10}|RI{sub a} - RI{sub b}|. This model gave better results than the model with only between-object variability considered. In addition, when dRI and variables derived from elemental compositions were used, this
Likelihood ratio model for classification of forensic evidence
International Nuclear Information System (INIS)
Zadora, G.; Neocleous, T.
2009-01-01
One of the problems of analysis of forensic evidence such as glass fragments, is the determination of their use-type category, e.g. does a glass fragment originate from an unknown window or container? Very small glass fragments arise during various accidents and criminal offences, and could be carried on the clothes, shoes and hair of participants. It is therefore necessary to obtain information on their physicochemical composition in order to solve the classification problem. Scanning Electron Microscopy coupled with an Energy Dispersive X-ray Spectrometer and the Glass Refractive Index Measurement method are routinely used in many forensic institutes for the investigation of glass. A natural form of glass evidence evaluation for forensic purposes is the likelihood ratio-LR = p(E|H 1 )/p(E|H 2 ). The main aim of this paper was to study the performance of LR models for glass object classification which considered one or two sources of data variability, i.e. between-glass-object variability and(or) within-glass-object variability. Within the proposed model a multivariate kernel density approach was adopted for modelling the between-object distribution and a multivariate normal distribution was adopted for modelling within-object distributions. Moreover, a graphical method of estimating the dependence structure was employed to reduce the highly multivariate problem to several lower-dimensional problems. The performed analysis showed that the best likelihood model was the one which allows to include information about between and within-object variability, and with variables derived from elemental compositions measured by SEM-EDX, and refractive values determined before (RI b ) and after (RI a ) the annealing process, in the form of dRI = log 10 |RI a - RI b |. This model gave better results than the model with only between-object variability considered. In addition, when dRI and variables derived from elemental compositions were used, this model outperformed two other
Posterior distributions for likelihood ratios in forensic science.
van den Hout, Ardo; Alberink, Ivo
2016-09-01
Evaluation of evidence in forensic science is discussed using posterior distributions for likelihood ratios. Instead of eliminating the uncertainty by integrating (Bayes factor) or by conditioning on parameter values, uncertainty in the likelihood ratio is retained by parameter uncertainty derived from posterior distributions. A posterior distribution for a likelihood ratio can be summarised by the median and credible intervals. Using the posterior mean of the distribution is not recommended. An analysis of forensic data for body height estimation is undertaken. The posterior likelihood approach has been criticised both theoretically and with respect to applicability. This paper addresses the latter and illustrates an interesting application area. Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.
Practical likelihood analysis for spatial generalized linear mixed models
DEFF Research Database (Denmark)
Bonat, W. H.; Ribeiro, Paulo Justiniano
2016-01-01
We investigate an algorithm for maximum likelihood estimation of spatial generalized linear mixed models based on the Laplace approximation. We compare our algorithm with a set of alternative approaches for two datasets from the literature. The Rhizoctonia root rot and the Rongelap are......, respectively, examples of binomial and count datasets modeled by spatial generalized linear mixed models. Our results show that the Laplace approximation provides similar estimates to Markov Chain Monte Carlo likelihood, Monte Carlo expectation maximization, and modified Laplace approximation. Some advantages...... of Laplace approximation include the computation of the maximized log-likelihood value, which can be used for model selection and tests, and the possibility to obtain realistic confidence intervals for model parameters based on profile likelihoods. The Laplace approximation also avoids the tuning...
Generalized empirical likelihood methods for analyzing longitudinal data
Wang, S.; Qian, L.; Carroll, R. J.
2010-01-01
Efficient estimation of parameters is a major objective in analyzing longitudinal data. We propose two generalized empirical likelihood based methods that take into consideration within-subject correlations. A nonparametric version of the Wilks
Maximum likelihood estimation of finite mixture model for economic data
Phoong, Seuk-Yen; Ismail, Mohd Tahir
2014-06-01
Finite mixture model is a mixture model with finite-dimension. This models are provides a natural representation of heterogeneity in a finite number of latent classes. In addition, finite mixture models also known as latent class models or unsupervised learning models. Recently, maximum likelihood estimation fitted finite mixture models has greatly drawn statistician's attention. The main reason is because maximum likelihood estimation is a powerful statistical method which provides consistent findings as the sample sizes increases to infinity. Thus, the application of maximum likelihood estimation is used to fit finite mixture model in the present paper in order to explore the relationship between nonlinear economic data. In this paper, a two-component normal mixture model is fitted by maximum likelihood estimation in order to investigate the relationship among stock market price and rubber price for sampled countries. Results described that there is a negative effect among rubber price and stock market price for Malaysia, Thailand, Philippines and Indonesia.
Attitude towards, and likelihood of, complaining in the banking ...
African Journals Online (AJOL)
aims to determine customers' attitudes towards complaining as well as their likelihood of voicing a .... is particularly powerful and impacts greatly on customer satisfaction and retention. ...... 'Cross-national analysis of hotel customers' attitudes ...
Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach
Sohail, Muhammad Sadiq; Al-Naffouri, Tareq Y.; Al-Ghadhban, Samir N.
2012-01-01
This paper presents a maximum likelihood (ML) approach to mitigate the effect of narrow band interference (NBI) in a zero padded orthogonal frequency division multiplexing (ZP-OFDM) system. The NBI is assumed to be time variant and asynchronous
Hill, J Colin; Ferraro, Simone; Battaglia, Nick; Liu, Jia; Spergel, David N
2016-07-29
The kinematic Sunyaev-Zel'dovich (KSZ) effect-the Doppler boosting of cosmic microwave background (CMB) photons due to Compton scattering off free electrons with nonzero bulk velocity-probes the abundance and the distribution of baryons in the Universe. All KSZ measurements to date have explicitly required spectroscopic redshifts. Here, we implement a novel estimator for the KSZ-large-scale structure cross-correlation based on projected fields: it does not require redshift estimates for individual objects, allowing KSZ measurements from large-scale imaging surveys. We apply this estimator to cleaned CMB temperature maps constructed from Planck and WMAP data and a galaxy sample from the Wide-field Infrared Survey Explorer (WISE). We measure the KSZ effect at 3.8σ-4.5σ significance, depending on the use of additional WISE galaxy bias constraints. We verify that our measurements are robust to possible dust emission from the WISE galaxies. Assuming the standard Λ cold dark matter cosmology, we directly constrain (f_{b}/0.158)(f_{free}/1.0)=1.48±0.19 (statistical error only) at redshift z≈0.4, where f_{b} is the fraction of matter in baryonic form and f_{free} is the free electron fraction. This is the tightest KSZ-derived constraint reported to date on these parameters. Astronomers have long known that baryons do not trace dark matter on ∼ kiloparsec scales and there has been strong evidence that galaxies are baryon poor. The consistency between the f_{b} value found here and the values inferred from analyses of the primordial CMB and big bang nucleosynthesis verifies that baryons approximately trace the dark matter distribution down to ∼ megaparsec scales. While our projected-field estimator is already competitive with other KSZ approaches when applied to current data sets (because we are able to use the full-sky WISE photometric survey), it will yield enormous signal-to-noise ratios when applied to upcoming high-resolution, multifrequency CMB surveys.
On the likelihood function of Gaussian max-stable processes
Genton, M. G.; Ma, Y.; Sang, H.
2011-01-01
We derive a closed form expression for the likelihood function of a Gaussian max-stable process indexed by ℝd at p≤d+1 sites, d≥1. We demonstrate the gain in efficiency in the maximum composite likelihood estimators of the covariance matrix from p=2 to p=3 sites in ℝ2 by means of a Monte Carlo simulation study. © 2011 Biometrika Trust.
On the likelihood function of Gaussian max-stable processes
Genton, M. G.
2011-05-24
We derive a closed form expression for the likelihood function of a Gaussian max-stable process indexed by ℝd at p≤d+1 sites, d≥1. We demonstrate the gain in efficiency in the maximum composite likelihood estimators of the covariance matrix from p=2 to p=3 sites in ℝ2 by means of a Monte Carlo simulation study. © 2011 Biometrika Trust.
Tapered composite likelihood for spatial max-stable models
Sang, Huiyan
2014-05-01
Spatial extreme value analysis is useful to environmental studies, in which extreme value phenomena are of interest and meaningful spatial patterns can be discerned. Max-stable process models are able to describe such phenomena. This class of models is asymptotically justified to characterize the spatial dependence among extremes. However, likelihood inference is challenging for such models because their corresponding joint likelihood is unavailable and only bivariate or trivariate distributions are known. In this paper, we propose a tapered composite likelihood approach by utilizing lower dimensional marginal likelihoods for inference on parameters of various max-stable process models. We consider a weighting strategy based on a "taper range" to exclude distant pairs or triples. The "optimal taper range" is selected to maximize various measures of the Godambe information associated with the tapered composite likelihood function. This method substantially reduces the computational cost and improves the efficiency over equally weighted composite likelihood estimators. We illustrate its utility with simulation experiments and an analysis of rainfall data in Switzerland.
Tapered composite likelihood for spatial max-stable models
Sang, Huiyan; Genton, Marc G.
2014-01-01
Spatial extreme value analysis is useful to environmental studies, in which extreme value phenomena are of interest and meaningful spatial patterns can be discerned. Max-stable process models are able to describe such phenomena. This class of models is asymptotically justified to characterize the spatial dependence among extremes. However, likelihood inference is challenging for such models because their corresponding joint likelihood is unavailable and only bivariate or trivariate distributions are known. In this paper, we propose a tapered composite likelihood approach by utilizing lower dimensional marginal likelihoods for inference on parameters of various max-stable process models. We consider a weighting strategy based on a "taper range" to exclude distant pairs or triples. The "optimal taper range" is selected to maximize various measures of the Godambe information associated with the tapered composite likelihood function. This method substantially reduces the computational cost and improves the efficiency over equally weighted composite likelihood estimators. We illustrate its utility with simulation experiments and an analysis of rainfall data in Switzerland.
Deconvolution map-making for cosmic microwave background observations
International Nuclear Information System (INIS)
Armitage, Charmaine; Wandelt, Benjamin D.
2004-01-01
We describe a new map-making code for cosmic microwave background observations. It implements fast algorithms for convolution and transpose convolution of two functions on the sphere [B. Wandelt and K. Gorski, Phys. Rev. D 63, 123002 (2001)]. Our code can account for arbitrary beam asymmetries and can be applied to any scanning strategy. We demonstrate the method using simulated time-ordered data for three beam models and two scanning patterns, including a coarsened version of the WMAP strategy. We quantitatively compare our results with a standard map-making method and demonstrate that the true sky is recovered with high accuracy using deconvolution map-making
ldr: An R Software Package for Likelihood-Based Su?cient Dimension Reduction
Directory of Open Access Journals (Sweden)
Kofi Placid Adragni
2014-11-01
Full Text Available In regression settings, a su?cient dimension reduction (SDR method seeks the core information in a p-vector predictor that completely captures its relationship with a response. The reduced predictor may reside in a lower dimension d < p, improving ability to visualize data and predict future observations, and mitigating dimensionality issues when carrying out further analysis. We introduce ldr, a new R software package that implements three recently proposed likelihood-based methods for SDR: covariance reduction, likelihood acquired directions, and principal fitted components. All three methods reduce the dimensionality of the data by pro jection into lower dimensional subspaces. The package also implements a variable screening method built upon principal ?tted components which makes use of ?exible basis functions to capture the dependencies between the predictors and the response. Examples are given to demonstrate likelihood-based SDR analyses using ldr, including estimation of the dimension of reduction subspaces and selection of basis functions. The ldr package provides a framework that we hope to grow into a comprehensive library of likelihood-based SDR methodologies.
A Game Theoretical Approach to Hacktivism: Is Attack Likelihood a Product of Risks and Payoffs?
Bodford, Jessica E; Kwan, Virginia S Y
2018-02-01
The current study examines hacktivism (i.e., hacking to convey a moral, ethical, or social justice message) through a general game theoretic framework-that is, as a product of costs and benefits. Given the inherent risk of carrying out a hacktivist attack (e.g., legal action, imprisonment), it would be rational for the user to weigh these risks against perceived benefits of carrying out the attack. As such, we examined computer science students' estimations of risks, payoffs, and attack likelihood through a game theoretic design. Furthermore, this study aims at constructing a descriptive profile of potential hacktivists, exploring two predicted covariates of attack decision making, namely, peer prevalence of hacking and sex differences. Contrary to expectations, results suggest that participants' estimations of attack likelihood stemmed solely from expected payoffs, rather than subjective risks. Peer prevalence significantly predicted increased payoffs and attack likelihood, suggesting an underlying descriptive norm in social networks. Notably, we observed no sex differences in the decision to attack, nor in the factors predicting attack likelihood. Implications for policymakers and the understanding and prevention of hacktivism are discussed, as are the possible ramifications of widely communicated payoffs over potential risks in hacking communities.
Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood
Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim
2017-04-01
Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models
Constraint likelihood analysis for a network of gravitational wave detectors
International Nuclear Information System (INIS)
Klimenko, S.; Rakhmanov, M.; Mitselmakher, G.; Mohanty, S.
2005-01-01
We propose a coherent method for detection and reconstruction of gravitational wave signals with a network of interferometric detectors. The method is derived by using the likelihood ratio functional for unknown signal waveforms. In the likelihood analysis, the global maximum of the likelihood ratio over the space of waveforms is used as the detection statistic. We identify a problem with this approach. In the case of an aligned pair of detectors, the detection statistic depends on the cross correlation between the detectors as expected, but this dependence disappears even for infinitesimally small misalignments. We solve the problem by applying constraints on the likelihood functional and obtain a new class of statistics. The resulting method can be applied to data from a network consisting of any number of detectors with arbitrary detector orientations. The method allows us reconstruction of the source coordinates and the waveforms of two polarization components of a gravitational wave. We study the performance of the method with numerical simulations and find the reconstruction of the source coordinates to be more accurate than in the standard likelihood method
Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics
Energy Technology Data Exchange (ETDEWEB)
Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc [Department of Mathematics and Statistics, University of Massachusetts, Amherst, Massachusetts 01003 (United States)
2016-03-14
We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.
Generalized empirical likelihood methods for analyzing longitudinal data
Wang, S.
2010-02-16
Efficient estimation of parameters is a major objective in analyzing longitudinal data. We propose two generalized empirical likelihood based methods that take into consideration within-subject correlations. A nonparametric version of the Wilks theorem for the limiting distributions of the empirical likelihood ratios is derived. It is shown that one of the proposed methods is locally efficient among a class of within-subject variance-covariance matrices. A simulation study is conducted to investigate the finite sample properties of the proposed methods and compare them with the block empirical likelihood method by You et al. (2006) and the normal approximation with a correctly estimated variance-covariance. The results suggest that the proposed methods are generally more efficient than existing methods which ignore the correlation structure, and better in coverage compared to the normal approximation with correctly specified within-subject correlation. An application illustrating our methods and supporting the simulation study results is also presented.
Framing the frame: How task goals determine the likelihood and direction of framing effects
Todd McElroy; John J. Seta
2007-01-01
We examined how the goal of a decision task influences the perceived positive, negative valence of the alternatives and thereby the likelihood and direction of framing effects. In Study 1 we manipulated the goal to increase, decrease or maintain the commodity in question and found that when the goal of the task was to increase the commodity, a framing effect consistent with those typically observed in the literature was found. When the goal was to decrease, a framing effect opposite to the ty...
Preliminary application of maximum likelihood method in HL-2A Thomson scattering system
International Nuclear Information System (INIS)
Yao Ke; Huang Yuan; Feng Zhen; Liu Chunhua; Li Enping; Nie Lin
2010-01-01
Maximum likelihood method to process the data of HL-2A Thomson scattering system is presented. Using mathematical statistics, this method maximizes the possibility of the likeness between the theoretical data and the observed data, so that we could get more accurate result. It has been proved to be applicable in comparison with that of the ratios method, and some of the drawbacks in ratios method do not exist in this new one. (authors)
Unbinned likelihood maximisation framework for neutrino clustering in Python
Energy Technology Data Exchange (ETDEWEB)
Coenders, Stefan [Technische Universitaet Muenchen, Boltzmannstr. 2, 85748 Garching (Germany)
2016-07-01
Albeit having detected an astrophysical neutrino flux with IceCube, sources of astrophysical neutrinos remain hidden up to now. A detection of a neutrino point source is a smoking gun for hadronic processes and acceleration of cosmic rays. The search for neutrino sources has many degrees of freedom, for example steady versus transient, point-like versus extended sources, et cetera. Here, we introduce a Python framework designed for unbinned likelihood maximisations as used in searches for neutrino point sources by IceCube. Implementing source scenarios in a modular way, likelihood searches on various kinds can be implemented in a user-friendly way, without sacrificing speed and memory management.
Nearly Efficient Likelihood Ratio Tests of the Unit Root Hypothesis
DEFF Research Database (Denmark)
Jansson, Michael; Nielsen, Morten Ørregaard
Seemingly absent from the arsenal of currently available "nearly efficient" testing procedures for the unit root hypothesis, i.e. tests whose local asymptotic power functions are indistinguishable from the Gaussian power envelope, is a test admitting a (quasi-)likelihood ratio interpretation. We...... show that the likelihood ratio unit root test derived in a Gaussian AR(1) model with standard normal innovations is nearly efficient in that model. Moreover, these desirable properties carry over to more complicated models allowing for serially correlated and/or non-Gaussian innovations....
A note on estimating errors from the likelihood function
International Nuclear Information System (INIS)
Barlow, Roger
2005-01-01
The points at which the log likelihood falls by 12 from its maximum value are often used to give the 'errors' on a result, i.e. the 68% central confidence interval. The validity of this is examined for two simple cases: a lifetime measurement and a Poisson measurement. Results are compared with the exact Neyman construction and with the simple Bartlett approximation. It is shown that the accuracy of the log likelihood method is poor, and the Bartlett construction explains why it is flawed
Nearly Efficient Likelihood Ratio Tests for Seasonal Unit Roots
DEFF Research Database (Denmark)
Jansson, Michael; Nielsen, Morten Ørregaard
In an important generalization of zero frequency autore- gressive unit root tests, Hylleberg, Engle, Granger, and Yoo (1990) developed regression-based tests for unit roots at the seasonal frequencies in quarterly time series. We develop likelihood ratio tests for seasonal unit roots and show...... that these tests are "nearly efficient" in the sense of Elliott, Rothenberg, and Stock (1996), i.e. that their local asymptotic power functions are indistinguishable from the Gaussian power envelope. Currently available nearly efficient testing procedures for seasonal unit roots are regression-based and require...... the choice of a GLS detrending parameter, which our likelihood ratio tests do not....
LDR: A Package for Likelihood-Based Sufficient Dimension Reduction
Directory of Open Access Journals (Sweden)
R. Dennis Cook
2011-03-01
Full Text Available We introduce a new mlab software package that implements several recently proposed likelihood-based methods for sufficient dimension reduction. Current capabilities include estimation of reduced subspaces with a fixed dimension d, as well as estimation of d by use of likelihood-ratio testing, permutation testing and information criteria. The methods are suitable for preprocessing data for both regression and classification. Implementations of related estimators are also available. Although the software is more oriented to command-line operation, a graphical user interface is also provided for prototype computations.
Likelihood ratio decisions in memory: three implied regularities.
Glanzer, Murray; Hilford, Andrew; Maloney, Laurence T
2009-06-01
We analyze four general signal detection models for recognition memory that differ in their distributional assumptions. Our analyses show that a basic assumption of signal detection theory, the likelihood ratio decision axis, implies three regularities in recognition memory: (1) the mirror effect, (2) the variance effect, and (3) the z-ROC length effect. For each model, we present the equations that produce the three regularities and show, in computed examples, how they do so. We then show that the regularities appear in data from a range of recognition studies. The analyses and data in our study support the following generalization: Individuals make efficient recognition decisions on the basis of likelihood ratios.
Analysis of Minute Features in Speckled Imagery with Maximum Likelihood Estimation
Directory of Open Access Journals (Sweden)
Alejandro C. Frery
2004-12-01
Full Text Available This paper deals with numerical problems arising when performing maximum likelihood parameter estimation in speckled imagery using small samples. The noise that appears in images obtained with coherent illumination, as is the case of sonar, laser, ultrasound-B, and synthetic aperture radar, is called speckle, and it can neither be assumed Gaussian nor additive. The properties of speckle noise are well described by the multiplicative model, a statistical framework from which stem several important distributions. Amongst these distributions, one is regarded as the universal model for speckled data, namely, the Ã°ÂÂ’Â¢0 law. This paper deals with amplitude data, so the Ã°ÂÂ’Â¢A0 distribution will be used. The literature reports that techniques for obtaining estimates (maximum likelihood, based on moments and on order statistics of the parameters of the Ã°ÂÂ’Â¢A0 distribution require samples of hundreds, even thousands, of observations in order to obtain sensible values. This is verified for maximum likelihood estimation, and a proposal based on alternate optimization is made to alleviate this situation. The proposal is assessed with real and simulated data, showing that the convergence problems are no longer present. A Monte Carlo experiment is devised to estimate the quality of maximum likelihood estimators in small samples, and real data is successfully analyzed with the proposed alternated procedure. Stylized empirical influence functions are computed and used to choose a strategy for computing maximum likelihood estimates that is resistant to outliers.
Yan, Yuan
2017-07-13
Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.
Yan, Yuan; Genton, Marc G.
2017-01-01
Gaussian likelihood inference has been studied and used extensively in both statistical theory and applications due to its simplicity. However, in practice, the assumption of Gaussianity is rarely met in the analysis of spatial data. In this paper, we study the effect of non-Gaussianity on Gaussian likelihood inference for the parameters of the Matérn covariance model. By using Monte Carlo simulations, we generate spatial data from a Tukey g-and-h random field, a flexible trans-Gaussian random field, with the Matérn covariance function, where g controls skewness and h controls tail heaviness. We use maximum likelihood based on the multivariate Gaussian distribution to estimate the parameters of the Matérn covariance function. We illustrate the effects of non-Gaussianity of the data on the estimated covariance function by means of functional boxplots. Thanks to our tailored simulation design, a comparison of the maximum likelihood estimator under both the increasing and fixed domain asymptotics for spatial data is performed. We find that the maximum likelihood estimator based on Gaussian likelihood is overall satisfying and preferable than the non-distribution-based weighted least squares estimator for data from the Tukey g-and-h random field. We also present the result for Gaussian kriging based on Matérn covariance estimates with data from the Tukey g-and-h random field and observe an overall satisfactory performance.
Understanding the properties of diagnostic tests - Part 2: Likelihood ratios.
Ranganathan, Priya; Aggarwal, Rakesh
2018-01-01
Diagnostic tests are used to identify subjects with and without disease. In a previous article in this series, we examined some attributes of diagnostic tests - sensitivity, specificity, and predictive values. In this second article, we look at likelihood ratios, which are useful for the interpretation of diagnostic test results in everyday clinical practice.
Comparison of likelihood testing procedures for parallel systems with covariances
International Nuclear Information System (INIS)
Ayman Baklizi; Isa Daud; Noor Akma Ibrahim
1998-01-01
In this paper we considered investigating and comparing the behavior of the likelihood ratio, the Rao's and the Wald's statistics for testing hypotheses on the parameters of the simple linear regression model based on parallel systems with covariances. These statistics are asymptotically equivalent (Barndorff-Nielsen and Cox, 1994). However, their relative performances in finite samples are generally known. A Monte Carlo experiment is conducted to stimulate the sizes and the powers of these statistics for complete samples and in the presence of time censoring. Comparisons of the statistics are made according to the attainment of assumed size of the test and their powers at various points in the parameter space. The results show that the likelihood ratio statistics appears to have the best performance in terms of the attainment of the assumed size of the test. Power comparisons show that the Rao statistic has some advantage over the Wald statistic in almost all of the space of alternatives while likelihood ratio statistic occupies either the first or the last position in term of power. Overall, the likelihood ratio statistic appears to be more appropriate to the model under study, especially for small sample sizes
Maximum likelihood estimation of the attenuated ultrasound pulse
DEFF Research Database (Denmark)
Rasmussen, Klaus Bolding
1994-01-01
The attenuated ultrasound pulse is divided into two parts: a stationary basic pulse and a nonstationary attenuation pulse. A standard ARMA model is used for the basic pulse, and a nonstandard ARMA model is derived for the attenuation pulse. The maximum likelihood estimator of the attenuated...
Planck 2013 results. XV. CMB power spectra and likelihood
Ade, P.A.R.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A.J.; Barreiro, R.B.; Bartlett, J.G.; Battaner, E.; Benabed, K.; Benoit, A.; Benoit-Levy, A.; Bernard, J.P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bock, J.J.; Bonaldi, A.; Bonavera, L.; Bond, J.R.; Borrill, J.; Bouchet, F.R.; Boulanger, F.; Bridges, M.; Bucher, M.; Burigana, C.; Butler, R.C.; Calabrese, E.; Cardoso, J.F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chiang, L.Y.; Chiang, H.C.; Christensen, P.R.; Church, S.; Clements, D.L.; Colombi, S.; Colombo, L.P.L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B.P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R.D.; Davis, R.J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.M.; Desert, F.X.; Dickinson, C.; Diego, J.M.; Dole, H.; Donzelli, S.; Dore, O.; Douspis, M.; Dunkley, J.; Dupac, X.; Efstathiou, G.; Elsner, F.; Ensslin, T.A.; Eriksen, H.K.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A.A.; Franceschi, E.; Gaier, T.C.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giardino, G.; Giraud-Heraud, Y.; Gjerlow, E.; Gonzalez-Nuevo, J.; Gorski, K.M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J.E.; Hansen, F.K.; Hanson, D.; Harrison, D.; Helou, G.; Henrot-Versille, S.; Hernandez-Monteagudo, C.; Herranz, D.; Hildebrandt, S.R.; Hivon, E.; Hobson, M.; Holmes, W.A.; Hornstrup, A.; Hovest, W.; Huffenberger, K.M.; Hurier, G.; Jaffe, T.R.; Jaffe, A.H.; Jewell, J.; Jones, W.C.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Kiiveri, K.; Kisner, T.S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lahteenmaki, A.; Lamarre, J.M.; Lasenby, A.; Lattanzi, M.; Laureijs, R.J.; Lawrence, C.R.; Le Jeune, M.; Leach, S.; Leahy, J.P.; Leonardi, R.; Leon-Tavares, J.; Lesgourgues, J.; Liguori, M.; Lilje, P.B.; Lindholm, V.; Linden-Vornle, M.; Lopez-Caniego, M.; Lubin, P.M.; Macias-Perez, J.F.; Maffei, B.; Maino, D.; Mandolesi, N.; Marinucci, D.; Maris, M.; Marshall, D.J.; Martin, P.G.; Martinez-Gonzalez, E.; Masi, S.; Matarrese, S.; Matthai, F.; Mazzotta, P.; Meinhold, P.R.; Melchiorri, A.; Mendes, L.; Menegoni, E.; Mennella, A.; Migliaccio, M.; Millea, M.; Mitra, S.; Miville-Deschenes, M.A.; Molinari, D.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C.B.; Norgaard-Nielsen, H.U.; Noviello, F.; Novikov, D.; Novikov, I.; O'Dwyer, I.J.; Orieux, F.; Osborne, S.; Oxborrow, C.A.; Paci, F.; Pagano, L.; Pajot, F.; Paladini, R.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Paykari, P.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G.W.; Prezeau, G.; Prunet, S.; Puget, J.L.; Rachen, J.P.; Rahlin, A.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ringeval, C.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rowan-Robinson, M.; Rubino-Martin, J.A.; Rusholme, B.; Sandri, M.; Sanselme, L.; Santos, D.; Savini, G.; Scott, D.; Seiffert, M.D.; Shellard, E.P.S.; Spencer, L.D.; Starck, J.L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sureau, F.; Sutton, D.; Suur-Uski, A.S.; Sygnet, J.F.; Tauber, J.A.; Tavagnacco, D.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Turler, M.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Varis, J.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L.A.; Wandelt, B.D.; Wehus, I.K.; White, M.; White, S.D.M.; Yvon, D.; Zacchei, A.; Zonca, A.
2014-01-01
We present the Planck likelihood, a complete statistical description of the two-point correlation function of the CMB temperature fluctuations. We use this likelihood to derive the Planck CMB power spectrum over three decades in l, covering 2 = 50, we employ a correlated Gaussian likelihood approximation based on angular cross-spectra derived from the 100, 143 and 217 GHz channels. We validate our likelihood through an extensive suite of consistency tests, and assess the impact of residual foreground and instrumental uncertainties on cosmological parameters. We find good internal agreement among the high-l cross-spectra with residuals of a few uK^2 at l <= 1000. We compare our results with foreground-cleaned CMB maps, and with cross-spectra derived from the 70 GHz Planck map, and find broad agreement in terms of spectrum residuals and cosmological parameters. The best-fit LCDM cosmology is in excellent agreement with preliminary Planck polarisation spectra. The standard LCDM cosmology is well constrained b...
MAXIMUM-LIKELIHOOD-ESTIMATION OF THE ENTROPY OF AN ATTRACTOR
SCHOUTEN, JC; TAKENS, F; VANDENBLEEK, CM
In this paper, a maximum-likelihood estimate of the (Kolmogorov) entropy of an attractor is proposed that can be obtained directly from a time series. Also, the relative standard deviation of the entropy estimate is derived; it is dependent on the entropy and on the number of samples used in the
A simplification of the likelihood ratio test statistic for testing ...
African Journals Online (AJOL)
The traditional likelihood ratio test statistic for testing hypothesis about goodness of fit of multinomial probabilities in one, two and multi – dimensional contingency table was simplified. Advantageously, using the simplified version of the statistic to test the null hypothesis is easier and faster because calculating the expected ...
Adaptive Unscented Kalman Filter using Maximum Likelihood Estimation
DEFF Research Database (Denmark)
Mahmoudi, Zeinab; Poulsen, Niels Kjølstad; Madsen, Henrik
2017-01-01
The purpose of this study is to develop an adaptive unscented Kalman filter (UKF) by tuning the measurement noise covariance. We use the maximum likelihood estimation (MLE) and the covariance matching (CM) method to estimate the noise covariance. The multi-step prediction errors generated...
LIKELIHOOD ESTIMATION OF PARAMETERS USING SIMULTANEOUSLY MONITORED PROCESSES
DEFF Research Database (Denmark)
Friis-Hansen, Peter; Ditlevsen, Ove Dalager
2004-01-01
The topic is maximum likelihood inference from several simultaneously monitored response processes of a structure to obtain knowledge about the parameters of other not monitored but important response processes when the structure is subject to some Gaussian load field in space and time. The consi....... The considered example is a ship sailing with a given speed through a Gaussian wave field....
Likelihood-based inference for clustered line transect data
DEFF Research Database (Denmark)
Waagepetersen, Rasmus; Schweder, Tore
2006-01-01
The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference...
Likelihood-based Dynamic Factor Analysis for Measurement and Forecasting
Jungbacker, B.M.J.P.; Koopman, S.J.
2015-01-01
We present new results for the likelihood-based analysis of the dynamic factor model. The latent factors are modelled by linear dynamic stochastic processes. The idiosyncratic disturbance series are specified as autoregressive processes with mutually correlated innovations. The new results lead to
Likelihood-based inference for clustered line transect data
DEFF Research Database (Denmark)
Waagepetersen, Rasmus Plenge; Schweder, Tore
The uncertainty in estimation of spatial animal density from line transect surveys depends on the degree of spatial clustering in the animal population. To quantify the clustering we model line transect data as independent thinnings of spatial shot-noise Cox processes. Likelihood-based inference...
Composite likelihood and two-stage estimation in family studies
DEFF Research Database (Denmark)
Andersen, Elisabeth Anne Wreford
2004-01-01
In this paper register based family studies provide the motivation for linking a two-stage estimation procedure in copula models for multivariate failure time data with a composite likelihood approach. The asymptotic properties of the estimators in both parametric and semi-parametric models are d...
Reconceptualizing Social Influence in Counseling: The Elaboration Likelihood Model.
McNeill, Brian W.; Stoltenberg, Cal D.
1989-01-01
Presents Elaboration Likelihood Model (ELM) of persuasion (a reconceptualization of the social influence process) as alternative model of attitude change. Contends ELM unifies conflicting social psychology results and can potentially account for inconsistent research findings in counseling psychology. Provides guidelines on integrating…
Counseling Pretreatment and the Elaboration Likelihood Model of Attitude Change.
Heesacker, Martin
1986-01-01
Results of the application of the Elaboration Likelihood Model (ELM) to a counseling context revealed that more favorable attitudes toward counseling occurred as subjects' ego involvement increased and as intervention quality improved. Counselor credibility affected the degree to which subjects' attitudes reflected argument quality differences.…
Cases in which ancestral maximum likelihood will be confusingly misleading.
Handelman, Tomer; Chor, Benny
2017-05-07
Ancestral maximum likelihood (AML) is a phylogenetic tree reconstruction criteria that "lies between" maximum parsimony (MP) and maximum likelihood (ML). ML has long been known to be statistically consistent. On the other hand, Felsenstein (1978) showed that MP is statistically inconsistent, and even positively misleading: There are cases where the parsimony criteria, applied to data generated according to one tree topology, will be optimized on a different tree topology. The question of weather AML is statistically consistent or not has been open for a long time. Mossel et al. (2009) have shown that AML can "shrink" short tree edges, resulting in a star tree with no internal resolution, which yields a better AML score than the original (resolved) model. This result implies that AML is statistically inconsistent, but not that it is positively misleading, because the star tree is compatible with any other topology. We show that AML is confusingly misleading: For some simple, four taxa (resolved) tree, the ancestral likelihood optimization criteria is maximized on an incorrect (resolved) tree topology, as well as on a star tree (both with specific edge lengths), while the tree with the original, correct topology, has strictly lower ancestral likelihood. Interestingly, the two short edges in the incorrect, resolved tree topology are of length zero, and are not adjacent, so this resolved tree is in fact a simple path. While for MP, the underlying phenomenon can be described as long edge attraction, it turns out that here we have long edge repulsion. Copyright © 2017. Published by Elsevier Ltd.
Multilevel maximum likelihood estimation with application to covariance matrices
Czech Academy of Sciences Publication Activity Database
Turčičová, Marie; Mandel, J.; Eben, Kryštof
Published online: 23 January ( 2018 ) ISSN 0361-0926 R&D Projects: GA ČR GA13-34856S Institutional support: RVO:67985807 Keywords : Fisher information * High dimension * Hierarchical maximum likelihood * Nested parameter spaces * Spectral diagonal covariance model * Sparse inverse covariance model Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.311, year: 2016
Exclusion probabilities and likelihood ratios with applications to mixtures.
Slooten, Klaas-Jan; Egeland, Thore
2016-01-01
The statistical evidence obtained from mixed DNA profiles can be summarised in several ways in forensic casework including the likelihood ratio (LR) and the Random Man Not Excluded (RMNE) probability. The literature has seen a discussion of the advantages and disadvantages of likelihood ratios and exclusion probabilities, and part of our aim is to bring some clarification to this debate. In a previous paper, we proved that there is a general mathematical relationship between these statistics: RMNE can be expressed as a certain average of the LR, implying that the expected value of the LR, when applied to an actual contributor to the mixture, is at least equal to the inverse of the RMNE. While the mentioned paper presented applications for kinship problems, the current paper demonstrates the relevance for mixture cases, and for this purpose, we prove some new general properties. We also demonstrate how to use the distribution of the likelihood ratio for donors of a mixture, to obtain estimates for exceedance probabilities of the LR for non-donors, of which the RMNE is a special case corresponding to L R>0. In order to derive these results, we need to view the likelihood ratio as a random variable. In this paper, we describe how such a randomization can be achieved. The RMNE is usually invoked only for mixtures without dropout. In mixtures, artefacts like dropout and drop-in are commonly encountered and we address this situation too, illustrating our results with a basic but widely implemented model, a so-called binary model. The precise definitions, modelling and interpretation of the required concepts of dropout and drop-in are not entirely obvious, and we attempt to clarify them here in a general likelihood framework for a binary model.
Maximum likelihood fitting of FROC curves under an initial-detection-and-candidate-analysis model
International Nuclear Information System (INIS)
Edwards, Darrin C.; Kupinski, Matthew A.; Metz, Charles E.; Nishikawa, Robert M.
2002-01-01
We have developed a model for FROC curve fitting that relates the observer's FROC performance not to the ROC performance that would be obtained if the observer's responses were scored on a per image basis, but rather to a hypothesized ROC performance that the observer would obtain in the task of classifying a set of 'candidate detections' as positive or negative. We adopt the assumptions of the Bunch FROC model, namely that the observer's detections are all mutually independent, as well as assumptions qualitatively similar to, but different in nature from, those made by Chakraborty in his AFROC scoring methodology. Under the assumptions of our model, we show that the observer's FROC performance is a linearly scaled version of the candidate analysis ROC curve, where the scaling factors are just given by the FROC operating point coordinates for detecting initial candidates. Further, we show that the likelihood function of the model parameters given observational data takes on a simple form, and we develop a maximum likelihood method for fitting a FROC curve to this data. FROC and AFROC curves are produced for computer vision observer datasets and compared with the results of the AFROC scoring method. Although developed primarily with computer vision schemes in mind, we hope that the methodology presented here will prove worthy of further study in other applications as well
Ribeiro, Angela dos Santos Bersot; Pereira, João Santos
2005-01-01
Vestibular system is the absolute referential for the maintenance of balance. Functional deficit with aging can result in balance disturbance and in increase of likelihood of falls. To verify whether specific therapeutic approach of the system can promote motor learning and can contribute to the improvement of balance and to decrease of likelihood of falls. Clinical prospective. Fifteen women, aged 60 to 69, mean = 64.8 years old (+/- 2.95), resident in Barra Mansa-RJ, were submitted to Cawthorne and Cooksey exercises during three months, three times a week, during sixty minutes. They were evaluated with Berg Balance Scale (BBS), whose scores determine the possibility of fall (PQ). Comparing the data obtained before and after intervention, we observed significant difference (pelderly people.
International Nuclear Information System (INIS)
Qi, Jinyi; Klein, Gregory J.; Huesman, Ronald H.
2000-01-01
A positron emission mammography scanner is under development at our Laboratory. The tomograph has a rectangular geometry consisting of four banks of detector modules. For each detector, the system can measure the depth of interaction information inside the crystal. The rectangular geometry leads to irregular radial and angular sampling and spatially variant sensitivity that are different from conventional PET systems. Therefore, it is of importance to study the image properties of the reconstructions. We adapted the theoretical analysis that we had developed for conventional PET systems to the list mode likelihood reconstruction for this tomograph. The local impulse response and covariance of the reconstruction can be easily computed using FFT. These theoretical results are also used with computer observer models to compute the signal-to-noise ratio for lesion detection. The analysis reveals the spatially variant resolution and noise properties of the list mode likelihood reconstruction. The theoretical predictions are in good agreement with Monte Carlo results
A composite likelihood approach for spatially correlated survival data
Paik, Jane; Ying, Zhiliang
2013-01-01
The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory. PMID:24223450
A composite likelihood approach for spatially correlated survival data.
Paik, Jane; Ying, Zhiliang
2013-01-01
The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory.
Secondary Analysis under Cohort Sampling Designs Using Conditional Likelihood
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Olli Saarela
2012-01-01
Full Text Available Under cohort sampling designs, additional covariate data are collected on cases of a specific type and a randomly selected subset of noncases, primarily for the purpose of studying associations with a time-to-event response of interest. With such data available, an interest may arise to reuse them for studying associations between the additional covariate data and a secondary non-time-to-event response variable, usually collected for the whole study cohort at the outset of the study. Following earlier literature, we refer to such a situation as secondary analysis. We outline a general conditional likelihood approach for secondary analysis under cohort sampling designs and discuss the specific situations of case-cohort and nested case-control designs. We also review alternative methods based on full likelihood and inverse probability weighting. We compare the alternative methods for secondary analysis in two simulated settings and apply them in a real-data example.
GENERALIZATION OF RAYLEIGH MAXIMUM LIKELIHOOD DESPECKLING FILTER USING QUADRILATERAL KERNELS
Directory of Open Access Journals (Sweden)
S. Sridevi
2013-02-01
Full Text Available Speckle noise is the most prevalent noise in clinical ultrasound images. It visibly looks like light and dark spots and deduce the pixel intensity as murkiest. Gazing at fetal ultrasound images, the impact of edge and local fine details are more palpable for obstetricians and gynecologists to carry out prenatal diagnosis of congenital heart disease. A robust despeckling filter has to be contrived to proficiently suppress speckle noise and simultaneously preserve the features. The proposed filter is the generalization of Rayleigh maximum likelihood filter by the exploitation of statistical tools as tuning parameters and use different shapes of quadrilateral kernels to estimate the noise free pixel from neighborhood. The performance of various filters namely Median, Kuwahura, Frost, Homogenous mask filter and Rayleigh maximum likelihood filter are compared with the proposed filter in terms PSNR and image profile. Comparatively the proposed filters surpass the conventional filters.
Likelihood inference for a nonstationary fractional autoregressive model
DEFF Research Database (Denmark)
Johansen, Søren; Ørregård Nielsen, Morten
2010-01-01
This paper discusses model-based inference in an autoregressive model for fractional processes which allows the process to be fractional of order d or d-b. Fractional differencing involves infinitely many past values and because we are interested in nonstationary processes we model the data X1......,...,X_{T} given the initial values X_{-n}, n=0,1,..., as is usually done. The initial values are not modeled but assumed to be bounded. This represents a considerable generalization relative to all previous work where it is assumed that initial values are zero. For the statistical analysis we assume...... the conditional Gaussian likelihood and for the probability analysis we also condition on initial values but assume that the errors in the autoregressive model are i.i.d. with suitable moment conditions. We analyze the conditional likelihood and its derivatives as stochastic processes in the parameters, including...
Physical constraints on the likelihood of life on exoplanets
Lingam, Manasvi; Loeb, Abraham
2018-04-01
One of the most fundamental questions in exoplanetology is to determine whether a given planet is habitable. We estimate the relative likelihood of a planet's propensity towards habitability by considering key physical characteristics such as the role of temperature on ecological and evolutionary processes, and atmospheric losses via hydrodynamic escape and stellar wind erosion. From our analysis, we demonstrate that Earth-sized exoplanets in the habitable zone around M-dwarfs seemingly display much lower prospects of being habitable relative to Earth, owing to the higher incident ultraviolet fluxes and closer distances to the host star. We illustrate our results by specifically computing the likelihood (of supporting life) for the recently discovered exoplanets, Proxima b and TRAPPIST-1e, which we find to be several orders of magnitude smaller than that of Earth.
THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures.
Theobald, Douglas L; Wuttke, Deborah S
2006-09-01
THESEUS is a command line program for performing maximum likelihood (ML) superpositions and analysis of macromolecular structures. While conventional superpositioning methods use ordinary least-squares (LS) as the optimization criterion, ML superpositions provide substantially improved accuracy by down-weighting variable structural regions and by correcting for correlations among atoms. ML superpositioning is robust and insensitive to the specific atoms included in the analysis, and thus it does not require subjective pruning of selected variable atomic coordinates. Output includes both likelihood-based and frequentist statistics for accurate evaluation of the adequacy of a superposition and for reliable analysis of structural similarities and differences. THESEUS performs principal components analysis for analyzing the complex correlations found among atoms within a structural ensemble. ANSI C source code and selected binaries for various computing platforms are available under the GNU open source license from http://monkshood.colorado.edu/theseus/ or http://www.theseus3d.org.
Deformation of log-likelihood loss function for multiclass boosting.
Kanamori, Takafumi
2010-09-01
The purpose of this paper is to study loss functions in multiclass classification. In classification problems, the decision function is estimated by minimizing an empirical loss function, and then, the output label is predicted by using the estimated decision function. We propose a class of loss functions which is obtained by a deformation of the log-likelihood loss function. There are four main reasons why we focus on the deformed log-likelihood loss function: (1) this is a class of loss functions which has not been deeply investigated so far, (2) in terms of computation, a boosting algorithm with a pseudo-loss is available to minimize the proposed loss function, (3) the proposed loss functions provide a clear correspondence between the decision functions and conditional probabilities of output labels, (4) the proposed loss functions satisfy the statistical consistency of the classification error rate which is a desirable property in classification problems. Based on (3), we show that the deformed log-likelihood loss provides a model of mislabeling which is useful as a statistical model of medical diagnostics. We also propose a robust loss function against outliers in multiclass classification based on our approach. The robust loss function is a natural extension of the existing robust loss function for binary classification. A model of mislabeling and a robust loss function are useful to cope with noisy data. Some numerical studies are presented to show the robustness of the proposed loss function. A mathematical characterization of the deformed log-likelihood loss function is also presented. Copyright 2010 Elsevier Ltd. All rights reserved.
Bayesian interpretation of Generalized empirical likelihood by maximum entropy
Rochet , Paul
2011-01-01
We study a parametric estimation problem related to moment condition models. As an alternative to the generalized empirical likelihood (GEL) and the generalized method of moments (GMM), a Bayesian approach to the problem can be adopted, extending the MEM procedure to parametric moment conditions. We show in particular that a large number of GEL estimators can be interpreted as a maximum entropy solution. Moreover, we provide a more general field of applications by proving the method to be rob...
Menyoal Elaboration Likelihood Model (ELM) dan Teori Retorika
Yudi Perbawaningsih
2012-01-01
Abstract: Persuasion is a communication process to establish or change attitudes, which can be understood through theory of Rhetoric and theory of Elaboration Likelihood Model (ELM). This study elaborates these theories in a Public Lecture series which to persuade the students in choosing their concentration of study. The result shows that in term of persuasion effectiveness it is not quite relevant to separate the message and its source. The quality of source is determined by the quality of ...
Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation
Rajiv D. Banker
1993-01-01
This paper provides a formal statistical basis for the efficiency evaluation techniques of data envelopment analysis (DEA). DEA estimators of the best practice monotone increasing and concave production function are shown to be also maximum likelihood estimators if the deviation of actual output from the efficient output is regarded as a stochastic variable with a monotone decreasing probability density function. While the best practice frontier estimator is biased below the theoretical front...
Multiple Improvements of Multiple Imputation Likelihood Ratio Tests
Chan, Kin Wai; Meng, Xiao-Li
2017-01-01
Multiple imputation (MI) inference handles missing data by first properly imputing the missing values $m$ times, and then combining the $m$ analysis results from applying a complete-data procedure to each of the completed datasets. However, the existing method for combining likelihood ratio tests has multiple defects: (i) the combined test statistic can be negative in practice when the reference null distribution is a standard $F$ distribution; (ii) it is not invariant to re-parametrization; ...
Maximum likelihood convolutional decoding (MCD) performance due to system losses
Webster, L.
1976-01-01
A model for predicting the computational performance of a maximum likelihood convolutional decoder (MCD) operating in a noisy carrier reference environment is described. This model is used to develop a subroutine that will be utilized by the Telemetry Analysis Program to compute the MCD bit error rate. When this computational model is averaged over noisy reference phase errors using a high-rate interpolation scheme, the results are found to agree quite favorably with experimental measurements.
Menyoal Elaboration Likelihood Model (ELM) Dan Teori Retorika
Perbawaningsih, Yudi
2012-01-01
: Persuasion is a communication process to establish or change attitudes, which can be understood through theory of Rhetoric and theory of Elaboration Likelihood Model (ELM). This study elaborates these theories in a Public Lecture series which to persuade the students in choosing their concentration of study. The result shows that in term of persuasion effectiveness it is not quite relevant to separate the message and its source. The quality of source is determined by the quality of the mess...
Penggunaan Elaboration Likelihood Model dalam Menganalisis Penerimaan Teknologi Informasi
vitrian, vitrian2
2010-01-01
This article discusses some technology acceptance models in an organization. Thorough analysis of how technology is acceptable help managers make any planning to implement new teachnology and make sure that new technology could enhance organization's performance. Elaboration Likelihood Model (ELM) is the one which sheds light on some behavioral factors in acceptance of information technology. The basic tenet of ELM states that human behavior in principle can be influenced through central r...
Statistical Bias in Maximum Likelihood Estimators of Item Parameters.
1982-04-01
34 a> E r’r~e r ,C Ie I# ne,..,.rVi rnd Id.,flfv b1 - bindk numb.r) I; ,t-i i-cd I ’ tiie bias in the maximum likelihood ,st i- i;, ’ t iIeiIrs in...NTC, IL 60088 Psychometric Laboratory University of North Carolina I ERIC Facility-Acquisitions Davie Hall 013A 4833 Rugby Avenue Chapel Hill, NC
Democracy, Autocracy and the Likelihood of International Conflict
Tangerås, Thomas
2008-01-01
This is a game-theoretic analysis of the link between regime type and international conflict. The democratic electorate can credibly punish the leader for bad conflict outcomes, whereas the autocratic selectorate cannot. For the fear of being thrown out of office, democratic leaders are (i) more selective about the wars they initiate and (ii) on average win more of the wars they start. Foreign policy behaviour is found to display strategic complementarities. The likelihood of interstate war, ...
Moment Conditions Selection Based on Adaptive Penalized Empirical Likelihood
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Yunquan Song
2014-01-01
Full Text Available Empirical likelihood is a very popular method and has been widely used in the fields of artificial intelligence (AI and data mining as tablets and mobile application and social media dominate the technology landscape. This paper proposes an empirical likelihood shrinkage method to efficiently estimate unknown parameters and select correct moment conditions simultaneously, when the model is defined by moment restrictions in which some are possibly misspecified. We show that our method enjoys oracle-like properties; that is, it consistently selects the correct moment conditions and at the same time its estimator is as efficient as the empirical likelihood estimator obtained by all correct moment conditions. Moreover, unlike the GMM, our proposed method allows us to carry out confidence regions for the parameters included in the model without estimating the covariances of the estimators. For empirical implementation, we provide some data-driven procedures for selecting the tuning parameter of the penalty function. The simulation results show that the method works remarkably well in terms of correct moment selection and the finite sample properties of the estimators. Also, a real-life example is carried out to illustrate the new methodology.
Caching and interpolated likelihoods: accelerating cosmological Monte Carlo Markov chains
Energy Technology Data Exchange (ETDEWEB)
Bouland, Adam; Easther, Richard; Rosenfeld, Katherine, E-mail: adam.bouland@aya.yale.edu, E-mail: richard.easther@yale.edu, E-mail: krosenfeld@cfa.harvard.edu [Department of Physics, Yale University, New Haven CT 06520 (United States)
2011-05-01
We describe a novel approach to accelerating Monte Carlo Markov Chains. Our focus is cosmological parameter estimation, but the algorithm is applicable to any problem for which the likelihood surface is a smooth function of the free parameters and computationally expensive to evaluate. We generate a high-order interpolating polynomial for the log-likelihood using the first points gathered by the Markov chains as a training set. This polynomial then accurately computes the majority of the likelihoods needed in the latter parts of the chains. We implement a simple version of this algorithm as a patch (InterpMC) to CosmoMC and show that it accelerates parameter estimatation by a factor of between two and four for well-converged chains. The current code is primarily intended as a ''proof of concept'', and we argue that there is considerable room for further performance gains. Unlike other approaches to accelerating parameter fits, we make no use of precomputed training sets or special choices of variables, and InterpMC is almost entirely transparent to the user.
Caching and interpolated likelihoods: accelerating cosmological Monte Carlo Markov chains
International Nuclear Information System (INIS)
Bouland, Adam; Easther, Richard; Rosenfeld, Katherine
2011-01-01
We describe a novel approach to accelerating Monte Carlo Markov Chains. Our focus is cosmological parameter estimation, but the algorithm is applicable to any problem for which the likelihood surface is a smooth function of the free parameters and computationally expensive to evaluate. We generate a high-order interpolating polynomial for the log-likelihood using the first points gathered by the Markov chains as a training set. This polynomial then accurately computes the majority of the likelihoods needed in the latter parts of the chains. We implement a simple version of this algorithm as a patch (InterpMC) to CosmoMC and show that it accelerates parameter estimatation by a factor of between two and four for well-converged chains. The current code is primarily intended as a ''proof of concept'', and we argue that there is considerable room for further performance gains. Unlike other approaches to accelerating parameter fits, we make no use of precomputed training sets or special choices of variables, and InterpMC is almost entirely transparent to the user
Maximum likelihood as a common computational framework in tomotherapy
International Nuclear Information System (INIS)
Olivera, G.H.; Shepard, D.M.; Reckwerdt, P.J.; Ruchala, K.; Zachman, J.; Fitchard, E.E.; Mackie, T.R.
1998-01-01
Tomotherapy is a dose delivery technique using helical or axial intensity modulated beams. One of the strengths of the tomotherapy concept is that it can incorporate a number of processes into a single piece of equipment. These processes include treatment optimization planning, dose reconstruction and kilovoltage/megavoltage image reconstruction. A common computational technique that could be used for all of these processes would be very appealing. The maximum likelihood estimator, originally developed for emission tomography, can serve as a useful tool in imaging and radiotherapy. We believe that this approach can play an important role in the processes of optimization planning, dose reconstruction and kilovoltage and/or megavoltage image reconstruction. These processes involve computations that require comparable physical methods. They are also based on equivalent assumptions, and they have similar mathematical solutions. As a result, the maximum likelihood approach is able to provide a common framework for all three of these computational problems. We will demonstrate how maximum likelihood methods can be applied to optimization planning, dose reconstruction and megavoltage image reconstruction in tomotherapy. Results for planning optimization, dose reconstruction and megavoltage image reconstruction will be presented. Strengths and weaknesses of the methodology are analysed. Future directions for this work are also suggested. (author)
Directory of Open Access Journals (Sweden)
Dongming Li
2017-04-01
Full Text Available An adaptive optics (AO system provides real-time compensation for atmospheric turbulence. However, an AO image is usually of poor contrast because of the nature of the imaging process, meaning that the image contains information coming from both out-of-focus and in-focus planes of the object, which also brings about a loss in quality. In this paper, we present a robust multi-frame adaptive optics image restoration algorithm via maximum likelihood estimation. Our proposed algorithm uses a maximum likelihood method with image regularization as the basic principle, and constructs the joint log likelihood function for multi-frame AO images based on a Poisson distribution model. To begin with, a frame selection method based on image variance is applied to the observed multi-frame AO images to select images with better quality to improve the convergence of a blind deconvolution algorithm. Then, by combining the imaging conditions and the AO system properties, a point spread function estimation model is built. Finally, we develop our iterative solutions for AO image restoration addressing the joint deconvolution issue. We conduct a number of experiments to evaluate the performances of our proposed algorithm. Experimental results show that our algorithm produces accurate AO image restoration results and outperforms the current state-of-the-art blind deconvolution methods.
Lei, Ning; Chiang, Kwo-Fu; Oudrari, Hassan; Xiong, Xiaoxiong
2011-01-01
Optical sensors aboard Earth orbiting satellites such as the next generation Visible/Infrared Imager/Radiometer Suite (VIIRS) assume that the sensors radiometric response in the Reflective Solar Bands (RSB) is described by a quadratic polynomial, in relating the aperture spectral radiance to the sensor Digital Number (DN) readout. For VIIRS Flight Unit 1, the coefficients are to be determined before launch by an attenuation method, although the linear coefficient will be further determined on-orbit through observing the Solar Diffuser. In determining the quadratic polynomial coefficients by the attenuation method, a Maximum Likelihood approach is applied in carrying out the least-squares procedure. Crucial to the Maximum Likelihood least-squares procedure is the computation of the weight. The weight not only has a contribution from the noise of the sensor s digital count, with an important contribution from digitization error, but also is affected heavily by the mathematical expression used to predict the value of the dependent variable, because both the independent and the dependent variables contain random noise. In addition, model errors have a major impact on the uncertainties of the coefficients. The Maximum Likelihood approach demonstrates the inadequacy of the attenuation method model with a quadratic polynomial for the retrieved spectral radiance. We show that using the inadequate model dramatically increases the uncertainties of the coefficients. We compute the coefficient values and their uncertainties, considering both measurement and model errors.
Zhou, Xiaofan; Shen, Xing-Xing; Hittinger, Chris Todd
2018-01-01
Abstract The sizes of the data matrices assembled to resolve branches of the tree of life have increased dramatically, motivating the development of programs for fast, yet accurate, inference. For example, several different fast programs have been developed in the very popular maximum likelihood framework, including RAxML/ExaML, PhyML, IQ-TREE, and FastTree. Although these programs are widely used, a systematic evaluation and comparison of their performance using empirical genome-scale data matrices has so far been lacking. To address this question, we evaluated these four programs on 19 empirical phylogenomic data sets with hundreds to thousands of genes and up to 200 taxa with respect to likelihood maximization, tree topology, and computational speed. For single-gene tree inference, we found that the more exhaustive and slower strategies (ten searches per alignment) outperformed faster strategies (one tree search per alignment) using RAxML, PhyML, or IQ-TREE. Interestingly, single-gene trees inferred by the three programs yielded comparable coalescent-based species tree estimations. For concatenation-based species tree inference, IQ-TREE consistently achieved the best-observed likelihoods for all data sets, and RAxML/ExaML was a close second. In contrast, PhyML often failed to complete concatenation-based analyses, whereas FastTree was the fastest but generated lower likelihood values and more dissimilar tree topologies in both types of analyses. Finally, data matrix properties, such as the number of taxa and the strength of phylogenetic signal, sometimes substantially influenced the programs’ relative performance. Our results provide real-world gene and species tree phylogenetic inference benchmarks to inform the design and execution of large-scale phylogenomic data analyses. PMID:29177474
Comparisons of likelihood and machine learning methods of individual classification
Guinand, B.; Topchy, A.; Page, K.S.; Burnham-Curtis, M. K.; Punch, W.F.; Scribner, K.T.
2002-01-01
Classification methods used in machine learning (e.g., artificial neural networks, decision trees, and k-nearest neighbor clustering) are rarely used with population genetic data. We compare different nonparametric machine learning techniques with parametric likelihood estimations commonly employed in population genetics for purposes of assigning individuals to their population of origin (“assignment tests”). Classifier accuracy was compared across simulated data sets representing different levels of population differentiation (low and high FST), number of loci surveyed (5 and 10), and allelic diversity (average of three or eight alleles per locus). Empirical data for the lake trout (Salvelinus namaycush) exhibiting levels of population differentiation comparable to those used in simulations were examined to further evaluate and compare classification methods. Classification error rates associated with artificial neural networks and likelihood estimators were lower for simulated data sets compared to k-nearest neighbor and decision tree classifiers over the entire range of parameters considered. Artificial neural networks only marginally outperformed the likelihood method for simulated data (0–2.8% lower error rates). The relative performance of each machine learning classifier improved relative likelihood estimators for empirical data sets, suggesting an ability to “learn” and utilize properties of empirical genotypic arrays intrinsic to each population. Likelihood-based estimation methods provide a more accessible option for reliable assignment of individuals to the population of origin due to the intricacies in development and evaluation of artificial neural networks. In recent years, characterization of highly polymorphic molecular markers such as mini- and microsatellites and development of novel methods of analysis have enabled researchers to extend investigations of ecological and evolutionary processes below the population level to the level of
Applying exclusion likelihoods from LHC searches to extended Higgs sectors
International Nuclear Information System (INIS)
Bechtle, Philip; Heinemeyer, Sven; Staal, Oscar; Stefaniak, Tim; Weiglein, Georg
2015-01-01
LHC searches for non-standard Higgs bosons decaying into tau lepton pairs constitute a sensitive experimental probe for physics beyond the Standard Model (BSM), such as supersymmetry (SUSY). Recently, the limits obtained from these searches have been presented by the CMS collaboration in a nearly model-independent fashion - as a narrow resonance model - based on the full 8 TeV dataset. In addition to publishing a 95 % C.L. exclusion limit, the full likelihood information for the narrowresonance model has been released. This provides valuable information that can be incorporated into global BSM fits. We present a simple algorithm that maps an arbitrary model with multiple neutral Higgs bosons onto the narrow resonance model and derives the corresponding value for the exclusion likelihood from the CMS search. This procedure has been implemented into the public computer code HiggsBounds (version 4.2.0 and higher). We validate our implementation by cross-checking against the official CMS exclusion contours in three Higgs benchmark scenarios in the Minimal Supersymmetric Standard Model (MSSM), and find very good agreement. Going beyond validation, we discuss the combined constraints of the ττ search and the rate measurements of the SM-like Higgs at 125 GeV in a recently proposed MSSM benchmark scenario, where the lightest Higgs boson obtains SM-like couplings independently of the decoupling of the heavier Higgs states. Technical details for how to access the likelihood information within HiggsBounds are given in the appendix. The program is available at http:// higgsbounds.hepforge.org. (orig.)
Australian food life style segments and elaboration likelihood differences
DEFF Research Database (Denmark)
Brunsø, Karen; Reid, Mike
As the global food marketing environment becomes more competitive, the international and comparative perspective of consumers' attitudes and behaviours becomes more important for both practitioners and academics. This research employs the Food-Related Life Style (FRL) instrument in Australia...... in order to 1) determine Australian Life Style Segments and compare these with their European counterparts, and to 2) explore differences in elaboration likelihood among the Australian segments, e.g. consumers' interest and motivation to perceive product related communication. The results provide new...
Maximum-likelihood method for numerical inversion of Mellin transform
International Nuclear Information System (INIS)
Iqbal, M.
1997-01-01
A method is described for inverting the Mellin transform which uses an expansion in Laguerre polynomials and converts the Mellin transform to Laplace transform, then the maximum-likelihood regularization method is used to recover the original function of the Mellin transform. The performance of the method is illustrated by the inversion of the test functions available in the literature (J. Inst. Math. Appl., 20 (1977) 73; Math. Comput., 53 (1989) 589). Effectiveness of the method is shown by results obtained through demonstration by means of tables and diagrams
How to Improve the Likelihood of CDM Approval?
DEFF Research Database (Denmark)
Brandt, Urs Steiner; Svendsen, Gert Tinggaard
2014-01-01
How can the likelihood of Clean Development Mechanism (CDM) approval be improved in the face of institutional shortcomings? To answer this question, we focus on the three institutional shortcomings of income sharing, risk sharing and corruption prevention concerning afforestation/reforestation (A....../R). Furthermore, three main stakeholders are identified, namely investors, governments and agents in a principal-agent model regarding monitoring and enforcement capacity. Developing countries such as West Africa have, despite huge potentials, not been integrated in A/R CDM projects yet. Remote sensing, however...
Maximum Likelihood and Bayes Estimation in Randomly Censored Geometric Distribution
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Hare Krishna
2017-01-01
Full Text Available In this article, we study the geometric distribution under randomly censored data. Maximum likelihood estimators and confidence intervals based on Fisher information matrix are derived for the unknown parameters with randomly censored data. Bayes estimators are also developed using beta priors under generalized entropy and LINEX loss functions. Also, Bayesian credible and highest posterior density (HPD credible intervals are obtained for the parameters. Expected time on test and reliability characteristics are also analyzed in this article. To compare various estimates developed in the article, a Monte Carlo simulation study is carried out. Finally, for illustration purpose, a randomly censored real data set is discussed.
Likelihood-Based Inference in Nonlinear Error-Correction Models
DEFF Research Database (Denmark)
Kristensen, Dennis; Rahbæk, Anders
We consider a class of vector nonlinear error correction models where the transfer function (or loadings) of the stationary relation- ships is nonlinear. This includes in particular the smooth transition models. A general representation theorem is given which establishes the dynamic properties...... and a linear trend in general. Gaussian likelihood-based estimators are considered for the long- run cointegration parameters, and the short-run parameters. Asymp- totic theory is provided for these and it is discussed to what extend asymptotic normality and mixed normaity can be found. A simulation study...
Process criticality accident likelihoods, consequences and emergency planning
International Nuclear Information System (INIS)
McLaughlin, T.P.
1992-01-01
Evaluation of criticality accident risks in the processing of significant quantities of fissile materials is both complex and subjective, largely due to the lack of accident statistics. Thus, complying with national and international standards and regulations which require an evaluation of the net benefit of a criticality accident alarm system, is also subjective. A review of guidance found in the literature on potential accident magnitudes is presented for different material forms and arrangements. Reasoned arguments are also presented concerning accident prevention and accident likelihoods for these material forms and arrangements. (Author)
Likelihood Estimation of Gamma Ray Bursts Duration Distribution
Horvath, Istvan
2005-01-01
Two classes of Gamma Ray Bursts have been identified so far, characterized by T90 durations shorter and longer than approximately 2 seconds. It was shown that the BATSE 3B data allow a good fit with three Gaussian distributions in log T90. In the same Volume in ApJ. another paper suggested that the third class of GRBs is may exist. Using the full BATSE catalog here we present the maximum likelihood estimation, which gives us 0.5% probability to having only two subclasses. The MC simulation co...
Process criticality accident likelihoods, consequences, and emergency planning
Energy Technology Data Exchange (ETDEWEB)
McLaughlin, T.P.
1991-01-01
Evaluation of criticality accident risks in the processing of significant quantities of fissile materials is both complex and subjective, largely due to the lack of accident statistics. Thus, complying with standards such as ISO 7753 which mandates that the need for an alarm system be evaluated, is also subjective. A review of guidance found in the literature on potential accident magnitudes is presented for different material forms and arrangements. Reasoned arguments are also presented concerning accident prevention and accident likelihoods for these material forms and arrangements. 13 refs., 1 fig., 1 tab.
Estimating likelihood of future crashes for crash-prone drivers
Subasish Das; Xiaoduan Sun; Fan Wang; Charles Leboeuf
2015-01-01
At-fault crash-prone drivers are usually considered as the high risk group for possible future incidents or crashes. In Louisiana, 34% of crashes are repeatedly committed by the at-fault crash-prone drivers who represent only 5% of the total licensed drivers in the state. This research has conducted an exploratory data analysis based on the driver faultiness and proneness. The objective of this study is to develop a crash prediction model to estimate the likelihood of future crashes for the a...
Similar tests and the standardized log likelihood ratio statistic
DEFF Research Database (Denmark)
Jensen, Jens Ledet
1986-01-01
When testing an affine hypothesis in an exponential family the 'ideal' procedure is to calculate the exact similar test, or an approximation to this, based on the conditional distribution given the minimal sufficient statistic under the null hypothesis. By contrast to this there is a 'primitive......' approach in which the marginal distribution of a test statistic considered and any nuisance parameter appearing in the test statistic is replaced by an estimate. We show here that when using standardized likelihood ratio statistics the 'primitive' procedure is in fact an 'ideal' procedure to order O(n -3...
Maximum Likelihood Joint Tracking and Association in Strong Clutter
Directory of Open Access Journals (Sweden)
Leonid I. Perlovsky
2013-01-01
Full Text Available We have developed a maximum likelihood formulation for a joint detection, tracking and association problem. An efficient non-combinatorial algorithm for this problem is developed in case of strong clutter for radar data. By using an iterative procedure of the dynamic logic process “from vague-to-crisp” explained in the paper, the new tracker overcomes the combinatorial complexity of tracking in highly-cluttered scenarios and results in an orders-of-magnitude improvement in signal-to-clutter ratio.
Application of the method of maximum likelihood to the determination of cepheid radii
International Nuclear Information System (INIS)
Balona, L.A.
1977-01-01
A method is described whereby the radius of any pulsating star can be obtained by applying the Principle of Maximum Likelihood. The relative merits of this method and of the usual Baade-Wesselink method are discussed in an Appendix. The new method is applied to 54 well-observed cepheids which include a number of spectroscopic binaries and two W Vir stars. An empirical period-radius relation is constructed and discussed in terms of two recent period-luminosity-colour calibrations. It is shown that the new method gives radii with an error of no more than 10 per cent. (author)
Analytic confidence level calculations using the likelihood ratio and fourier transform
International Nuclear Information System (INIS)
Hu Hongbo; Nielsen, J.
2000-01-01
The interpretation of new particle search results involves a confidence level calculation on either the discovery hypothesis or the background-only ('null') hypothesis. A typical approach uses toy Monte Carlo experiments to build an expected experiment estimator distribution against which an observed experiment's estimator may be compared. In this note, a new approach is presented which calculates analytically the experiment estimator distribution via a Fourier transform, using the likelihood ratio as an ordering estimator. The analytic approach enjoys an enormous speed advantage over the toy Monte Carlo method, making it possible to quickly and precisely calculate confidence level results
Likelihood Approximation With Parallel Hierarchical Matrices For Large Spatial Datasets
Litvinenko, Alexander
2017-11-01
The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Matérn covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\\\H$-) matrix format with computational cost $\\\\mathcal{O}(k^2n \\\\log^2 n/p)$ and storage $\\\\mathcal{O}(kn \\\\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.
Likelihood Approximation With Parallel Hierarchical Matrices For Large Spatial Datasets
Litvinenko, Alexander; Sun, Ying; Genton, Marc G.; Keyes, David E.
2017-01-01
The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Matérn covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\H$-) matrix format with computational cost $\\mathcal{O}(k^2n \\log^2 n/p)$ and storage $\\mathcal{O}(kn \\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.
Superfast maximum-likelihood reconstruction for quantum tomography
Shang, Jiangwei; Zhang, Zhengyun; Ng, Hui Khoon
2017-06-01
Conventional methods for computing maximum-likelihood estimators (MLE) often converge slowly in practical situations, leading to a search for simplifying methods that rely on additional assumptions for their validity. In this work, we provide a fast and reliable algorithm for maximum-likelihood reconstruction that avoids this slow convergence. Our method utilizes the state-of-the-art convex optimization scheme, an accelerated projected-gradient method, that allows one to accommodate the quantum nature of the problem in a different way than in the standard methods. We demonstrate the power of our approach by comparing its performance with other algorithms for n -qubit state tomography. In particular, an eight-qubit situation that purportedly took weeks of computation time in 2005 can now be completed in under a minute for a single set of data, with far higher accuracy than previously possible. This refutes the common claim that MLE reconstruction is slow and reduces the need for alternative methods that often come with difficult-to-verify assumptions. In fact, recent methods assuming Gaussian statistics or relying on compressed sensing ideas are demonstrably inapplicable for the situation under consideration here. Our algorithm can be applied to general optimization problems over the quantum state space; the philosophy of projected gradients can further be utilized for optimization contexts with general constraints.
Likelihood inference for a fractionally cointegrated vector autoregressive model
DEFF Research Database (Denmark)
Johansen, Søren; Ørregård Nielsen, Morten
2012-01-01
such that the process X_{t} is fractional of order d and cofractional of order d-b; that is, there exist vectors ß for which ß'X_{t} is fractional of order d-b, and no other fractionality order is possible. We define the statistical model by 0inference when the true values satisfy b0¿1/2 and d0-b0......We consider model based inference in a fractionally cointegrated (or cofractional) vector autoregressive model with a restricted constant term, ¿, based on the Gaussian likelihood conditional on initial values. The model nests the I(d) VAR model. We give conditions on the parameters...... process in the parameters when errors are i.i.d. with suitable moment conditions and initial values are bounded. When the limit is deterministic this implies uniform convergence in probability of the conditional likelihood function. If the true value b0>1/2, we prove that the limit distribution of (ß...
Likelihood-Based Inference of B Cell Clonal Families.
Directory of Open Access Journals (Sweden)
Duncan K Ralph
2016-10-01
Full Text Available The human immune system depends on a highly diverse collection of antibody-making B cells. B cell receptor sequence diversity is generated by a random recombination process called "rearrangement" forming progenitor B cells, then a Darwinian process of lineage diversification and selection called "affinity maturation." The resulting receptors can be sequenced in high throughput for research and diagnostics. Such a collection of sequences contains a mixture of various lineages, each of which may be quite numerous, or may consist of only a single member. As a step to understanding the process and result of this diversification, one may wish to reconstruct lineage membership, i.e. to cluster sampled sequences according to which came from the same rearrangement events. We call this clustering problem "clonal family inference." In this paper we describe and validate a likelihood-based framework for clonal family inference based on a multi-hidden Markov Model (multi-HMM framework for B cell receptor sequences. We describe an agglomerative algorithm to find a maximum likelihood clustering, two approximate algorithms with various trade-offs of speed versus accuracy, and a third, fast algorithm for finding specific lineages. We show that under simulation these algorithms greatly improve upon existing clonal family inference methods, and that they also give significantly different clusters than previous methods when applied to two real data sets.
Risk factors and likelihood of Campylobacter colonization in broiler flocks
Directory of Open Access Journals (Sweden)
SL Kuana
2007-09-01
Full Text Available Campylobacter was investigated in cecal droppings, feces, and cloacal swabs of 22 flocks of 3 to 5 week-old broilers. Risk factors and the likelihood of the presence of this agent in these flocks were determined. Management practices, such as cleaning and disinfection, feeding, drinkers, and litter treatments, were assessed. Results were evaluated using Odds Ratio (OR test, and their significance was tested by Fisher's test (p<0.05. A Campylobacter prevalence of 81.8% was found in the broiler flocks (18/22, and within positive flocks, it varied between 85 and 100%. Campylobacter incidence among sample types was homogenous, being 81.8% in cecal droppings, 80.9% in feces, and 80.4% in cloacal swabs (230. Flocks fed by automatic feeding systems presented higher incidence of Campylobacter as compared to those fed by tube feeders. Litter was reused in 63.6% of the farm, and, despite the lack of statistical significance, there was higher likelihood of Campylobacter incidence when litter was reused. Foot bath was not used in 45.5% of the flocks, whereas the use of foot bath associated to deficient lime management increased the number of positive flocks, although with no statiscal significance. The evaluated parameters were not significantly associated with Campylobacter colonization in the assessed broiler flocks.
Menyoal Elaboration Likelihood Model (ELM dan Teori Retorika
Directory of Open Access Journals (Sweden)
Yudi Perbawaningsih
2012-06-01
Full Text Available Abstract: Persuasion is a communication process to establish or change attitudes, which can be understood through theory of Rhetoric and theory of Elaboration Likelihood Model (ELM. This study elaborates these theories in a Public Lecture series which to persuade the students in choosing their concentration of study. The result shows that in term of persuasion effectiveness it is not quite relevant to separate the message and its source. The quality of source is determined by the quality of the message, and vice versa. Separating the two routes of the persuasion process as described in the ELM theory would not be relevant. Abstrak: Persuasi adalah proses komunikasi untuk membentuk atau mengubah sikap, yang dapat dipahami dengan teori Retorika dan teori Elaboration Likelihood Model (ELM. Penelitian ini mengelaborasi teori tersebut dalam Kuliah Umum sebagai sarana mempersuasi mahasiswa untuk memilih konsentrasi studi studi yang didasarkan pada proses pengolahan informasi. Menggunakan metode survey, didapatkan hasil yaitu tidaklah cukup relevan memisahkan pesan dan narasumber dalam melihat efektivitas persuasi. Keduanya menyatu yang berarti bahwa kualitas narasumber ditentukan oleh kualitas pesan yang disampaikannya, dan sebaliknya. Memisahkan proses persuasi dalam dua lajur seperti yang dijelaskan dalam ELM teori menjadi tidak relevan.
Corporate brand extensions based on the purchase likelihood: governance implications
Directory of Open Access Journals (Sweden)
Spyridon Goumas
2018-03-01
Full Text Available This paper is examining the purchase likelihood of hypothetical service brand extensions from product companies focusing on consumer electronics based on sector categorization and perceptions of fit between the existing product category and image of the company. Prior research has recognized that levels of brand knowledge eases the transference of associations and affect to the new products. Similarity to the existing products of the parent company and perceived image also influence the success of brand extensions. However, sector categorization may interfere with this relationship. The purpose of this study is to examine Greek consumers’ attitudes towards hypothetical brand extensions, and how these are affected by consumers’ existing knowledge about the brand, sector categorization and perceptions of image and category fit of cross-sector extensions. This aim is examined in the context of technological categories, where less-known companies exhibited significance in purchase likelihood, and contradictory with the existing literature, service companies did not perform as positively as expected. Additional insights to the existing literature about sector categorization are provided. The effect of both image and category fit is also examined and predictions regarding the effect of each are made.
Gauging the likelihood of stable cavitation from ultrasound contrast agents.
Bader, Kenneth B; Holland, Christy K
2013-01-07
The mechanical index (MI) was formulated to gauge the likelihood of adverse bioeffects from inertial cavitation. However, the MI formulation did not consider bubble activity from stable cavitation. This type of bubble activity can be readily nucleated from ultrasound contrast agents (UCAs) and has the potential to promote beneficial bioeffects. Here, the presence of stable cavitation is determined numerically by tracking the onset of subharmonic oscillations within a population of bubbles for frequencies up to 7 MHz and peak rarefactional pressures up to 3 MPa. In addition, the acoustic pressure rupture threshold of an UCA population was determined using the Marmottant model. The threshold for subharmonic emissions of optimally sized bubbles was found to be lower than the inertial cavitation threshold for all frequencies studied. The rupture thresholds of optimally sized UCAs were found to be lower than the threshold for subharmonic emissions for either single cycle or steady state acoustic excitations. Because the thresholds of both subharmonic emissions and UCA rupture are linearly dependent on frequency, an index of the form I(CAV) = P(r)/f (where P(r) is the peak rarefactional pressure in MPa and f is the frequency in MHz) was derived to gauge the likelihood of subharmonic emissions due to stable cavitation activity nucleated from UCAs.
Safe semi-supervised learning based on weighted likelihood.
Kawakita, Masanori; Takeuchi, Jun'ichi
2014-05-01
We are interested in developing a safe semi-supervised learning that works in any situation. Semi-supervised learning postulates that n(') unlabeled data are available in addition to n labeled data. However, almost all of the previous semi-supervised methods require additional assumptions (not only unlabeled data) to make improvements on supervised learning. If such assumptions are not met, then the methods possibly perform worse than supervised learning. Sokolovska, Cappé, and Yvon (2008) proposed a semi-supervised method based on a weighted likelihood approach. They proved that this method asymptotically never performs worse than supervised learning (i.e., it is safe) without any assumption. Their method is attractive because it is easy to implement and is potentially general. Moreover, it is deeply related to a certain statistical paradox. However, the method of Sokolovska et al. (2008) assumes a very limited situation, i.e., classification, discrete covariates, n(')→∞ and a maximum likelihood estimator. In this paper, we extend their method by modifying the weight. We prove that our proposal is safe in a significantly wide range of situations as long as n≤n('). Further, we give a geometrical interpretation of the proof of safety through the relationship with the above-mentioned statistical paradox. Finally, we show that the above proposal is asymptotically safe even when n(')
Primordial helium abundance from CMB: A constraint from recent observations and a forecast
International Nuclear Information System (INIS)
Ichikawa, Kazuhide; Sekiguchi, Toyokazu; Takahashi, Tomo
2008-01-01
We studied a constraint on the primordial helium abundance Y p from current and future observations of CMB. Using the currently available data from WMAP, ACBAR, CBI, and BOOMERANG, we obtained the constraint as Y p =0.25 -0.07 +0.10 at 68% confidence level. We also provide a forecast for the Planck experiment using the Markov chain Monte Carlo approach. In addition to forecasting the constraint on Y p , we investigate how assumptions for Y p affect constraints on the other cosmological parameters.
de Queiroz, Kevin; Poe, Steven
2003-06-01
single body of data; however, both classes of methods can be used to perform severe tests. The assumption of descent with modification is insufficient background knowledge to justify cladistic parsimony as a method for assessing degree of corroboration. Invoking equivalency between parsimony methods and likelihood models that assume no common mechanism emphasizes the necessity of additional assumptions, at least some of which are probabilistic in nature. Incongruent characters do not qualify as falsifiers of phylogenetic hypotheses except under extremely unrealistic evolutionary models; therefore, justifications of parsimony methods as falsificationist based on the idea that they minimize the ad hoc dismissal of falsifiers are questionable. Probabilistic concepts such as degree of corroboration and likelihood provide a more appropriate framework for understanding how phylogenetics conforms with Popper's philosophy of science. Likelihood ratio tests do not assume what is at issue but instead are methods for testing hypotheses according to an accepted standard of statistical significance and for incorporating considerations about test severity. These tests are fundamentally similar to Popper's degree of corroboration in being based on the relationship between the probability of the evidence e in the presence versus absence of the hypothesis h, i.e., between p(e|hb) and p(e|b), where b is the background knowledge. Both parsimony and likelihood methods are inductive in that their inferences (particular trees) contain more information than (and therefore do not follow necessarily from) the observations upon which they are based; however, both are deductive in that their conclusions (tree lengths and likelihoods) follow necessarily from their premises (particular trees, observed character state distributions, and evolutionary models). For these and other reasons, phylogenetic likelihood methods are highly compatible with Karl Popper's philosophy of science and offer several
Silverman, Merav H.; Jedd, Kelly; Luciana, Monica
2015-01-01
Behavioral responses to, and the neural processing of, rewards change dramatically during adolescence and may contribute to observed increases in risk-taking during this developmental period. Functional MRI (fMRI) studies suggest differences between adolescents and adults in neural activation during reward processing, but findings are contradictory, and effects have been found in non-predicted directions. The current study uses an activation likelihood estimation (ALE) approach for quantitative meta-analysis of functional neuroimaging studies to: 1) confirm the network of brain regions involved in adolescents’ reward processing, 2) identify regions involved in specific stages (anticipation, outcome) and valence (positive, negative) of reward processing, and 3) identify differences in activation likelihood between adolescent and adult reward-related brain activation. Results reveal a subcortical network of brain regions involved in adolescent reward processing similar to that found in adults with major hubs including the ventral and dorsal striatum, insula, and posterior cingulate cortex (PCC). Contrast analyses find that adolescents exhibit greater likelihood of activation in the insula while processing anticipation relative to outcome and greater likelihood of activation in the putamen and amygdala during outcome relative to anticipation. While processing positive compared to negative valence, adolescents show increased likelihood for activation in the posterior cingulate cortex (PCC) and ventral striatum. Contrasting adolescent reward processing with the existing ALE of adult reward processing (Liu et al., 2011) reveals increased likelihood for activation in limbic, frontolimbic, and striatal regions in adolescents compared with adults. Unlike adolescents, adults also activate executive control regions of the frontal and parietal lobes. These findings support hypothesized elevations in motivated activity during adolescence. PMID:26254587
Maximum likelihood positioning algorithm for high-resolution PET scanners
International Nuclear Information System (INIS)
Gross-Weege, Nicolas; Schug, David; Hallen, Patrick; Schulz, Volkmar
2016-01-01
Purpose: In high-resolution positron emission tomography (PET), lightsharing elements are incorporated into typical detector stacks to read out scintillator arrays in which one scintillator element (crystal) is smaller than the size of the readout channel. In order to identify the hit crystal by means of the measured light distribution, a positioning algorithm is required. One commonly applied positioning algorithm uses the center of gravity (COG) of the measured light distribution. The COG algorithm is limited in spatial resolution by noise and intercrystal Compton scatter. The purpose of this work is to develop a positioning algorithm which overcomes this limitation. Methods: The authors present a maximum likelihood (ML) algorithm which compares a set of expected light distributions given by probability density functions (PDFs) with the measured light distribution. Instead of modeling the PDFs by using an analytical model, the PDFs of the proposed ML algorithm are generated assuming a single-gamma-interaction model from measured data. The algorithm was evaluated with a hot-rod phantom measurement acquired with the preclinical HYPERION II D PET scanner. In order to assess the performance with respect to sensitivity, energy resolution, and image quality, the ML algorithm was compared to a COG algorithm which calculates the COG from a restricted set of channels. The authors studied the energy resolution of the ML and the COG algorithm regarding incomplete light distributions (missing channel information caused by detector dead time). Furthermore, the authors investigated the effects of using a filter based on the likelihood values on sensitivity, energy resolution, and image quality. Results: A sensitivity gain of up to 19% was demonstrated in comparison to the COG algorithm for the selected operation parameters. Energy resolution and image quality were on a similar level for both algorithms. Additionally, the authors demonstrated that the performance of the ML
Extending the Applicability of the Generalized Likelihood Function for Zero-Inflated Data Series
Oliveira, Debora Y.; Chaffe, Pedro L. B.; Sá, João. H. M.
2018-03-01
Proper uncertainty estimation for data series with a high proportion of zero and near zero observations has been a challenge in hydrologic studies. This technical note proposes a modification to the Generalized Likelihood function that accounts for zero inflation of the error distribution (ZI-GL). We compare the performance of the proposed ZI-GL with the original Generalized Likelihood function using the entire data series (GL) and by simply suppressing zero observations (GLy>0). These approaches were applied to two interception modeling examples characterized by data series with a significant number of zeros. The ZI-GL produced better uncertainty ranges than the GL as measured by the precision, reliability and volumetric bias metrics. The comparison between ZI-GL and GLy>0 highlights the need for further improvement in the treatment of residuals from near zero simulations when a linear heteroscedastic error model is considered. Aside from the interception modeling examples illustrated herein, the proposed ZI-GL may be useful for other hydrologic studies, such as for the modeling of the runoff generation in hillslopes and ephemeral catchments.
Maximum likelihood-based analysis of photon arrival trajectories in single-molecule FRET
Energy Technology Data Exchange (ETDEWEB)
Waligorska, Marta [Adam Mickiewicz University, Faculty of Chemistry, Grunwaldzka 6, 60-780 Poznan (Poland); Molski, Andrzej, E-mail: amolski@amu.edu.pl [Adam Mickiewicz University, Faculty of Chemistry, Grunwaldzka 6, 60-780 Poznan (Poland)
2012-07-25
Highlights: Black-Right-Pointing-Pointer We study model selection and parameter recovery from single-molecule FRET experiments. Black-Right-Pointing-Pointer We examine the maximum likelihood-based analysis of two-color photon trajectories. Black-Right-Pointing-Pointer The number of observed photons determines the performance of the method. Black-Right-Pointing-Pointer For long trajectories, one can extract mean dwell times that are comparable to inter-photon times. -- Abstract: When two fluorophores (donor and acceptor) are attached to an immobilized biomolecule, anti-correlated fluctuations of the donor and acceptor fluorescence caused by Foerster resonance energy transfer (FRET) report on the conformational kinetics of the molecule. Here we assess the maximum likelihood-based analysis of donor and acceptor photon arrival trajectories as a method for extracting the conformational kinetics. Using computer generated data we quantify the accuracy and precision of parameter estimates and the efficiency of the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) in selecting the true kinetic model. We find that the number of observed photons is the key parameter determining parameter estimation and model selection. For long trajectories, one can extract mean dwell times that are comparable to inter-photon times.
CSIR Research Space (South Africa)
Kok, S
2012-07-01
Full Text Available continuously as the correlation function hyper-parameters approach zero. Since the global minimizer of the maximum likelihood function is an asymptote in this case, it is unclear if maximum likelihood estimation (MLE) remains valid. Numerical ill...
Transfer Entropy as a Log-Likelihood Ratio
Barnett, Lionel; Bossomaier, Terry
2012-09-01
Transfer entropy, an information-theoretic measure of time-directed information transfer between joint processes, has steadily gained popularity in the analysis of complex stochastic dynamics in diverse fields, including the neurosciences, ecology, climatology, and econometrics. We show that for a broad class of predictive models, the log-likelihood ratio test statistic for the null hypothesis of zero transfer entropy is a consistent estimator for the transfer entropy itself. For finite Markov chains, furthermore, no explicit model is required. In the general case, an asymptotic χ2 distribution is established for the transfer entropy estimator. The result generalizes the equivalence in the Gaussian case of transfer entropy and Granger causality, a statistical notion of causal influence based on prediction via vector autoregression, and establishes a fundamental connection between directed information transfer and causality in the Wiener-Granger sense.
A Non-standard Empirical Likelihood for Time Series
DEFF Research Database (Denmark)
Nordman, Daniel J.; Bunzel, Helle; Lahiri, Soumendra N.
Standard blockwise empirical likelihood (BEL) for stationary, weakly dependent time series requires specifying a fixed block length as a tuning parameter for setting confidence regions. This aspect can be difficult and impacts coverage accuracy. As an alternative, this paper proposes a new version...... of BEL based on a simple, though non-standard, data-blocking rule which uses a data block of every possible length. Consequently, the method involves no block selection and is also anticipated to exhibit better coverage performance. Its non-standard blocking scheme, however, induces non......-standard asymptotics and requires a significantly different development compared to standard BEL. We establish the large-sample distribution of log-ratio statistics from the new BEL method for calibrating confidence regions for mean or smooth function parameters of time series. This limit law is not the usual chi...
Neutron spectra unfolding with maximum entropy and maximum likelihood
International Nuclear Information System (INIS)
Itoh, Shikoh; Tsunoda, Toshiharu
1989-01-01
A new unfolding theory has been established on the basis of the maximum entropy principle and the maximum likelihood method. This theory correctly embodies the Poisson statistics of neutron detection, and always brings a positive solution over the whole energy range. Moreover, the theory unifies both problems of overdetermined and of underdetermined. For the latter, the ambiguity in assigning a prior probability, i.e. the initial guess in the Bayesian sense, has become extinct by virtue of the principle. An approximate expression of the covariance matrix for the resultant spectra is also presented. An efficient algorithm to solve the nonlinear system, which appears in the present study, has been established. Results of computer simulation showed the effectiveness of the present theory. (author)
Narrow band interference cancelation in OFDM: Astructured maximum likelihood approach
Sohail, Muhammad Sadiq
2012-06-01
This paper presents a maximum likelihood (ML) approach to mitigate the effect of narrow band interference (NBI) in a zero padded orthogonal frequency division multiplexing (ZP-OFDM) system. The NBI is assumed to be time variant and asynchronous with the frequency grid of the ZP-OFDM system. The proposed structure based technique uses the fact that the NBI signal is sparse as compared to the ZP-OFDM signal in the frequency domain. The structure is also useful in reducing the computational complexity of the proposed method. The paper also presents a data aided approach for improved NBI estimation. The suitability of the proposed method is demonstrated through simulations. © 2012 IEEE.
Calibration of two complex ecosystem models with different likelihood functions
Hidy, Dóra; Haszpra, László; Pintér, Krisztina; Nagy, Zoltán; Barcza, Zoltán
2014-05-01
The biosphere is a sensitive carbon reservoir. Terrestrial ecosystems were approximately carbon neutral during the past centuries, but they became net carbon sinks due to climate change induced environmental change and associated CO2 fertilization effect of the atmosphere. Model studies and measurements indicate that the biospheric carbon sink can saturate in the future due to ongoing climate change which can act as a positive feedback. Robustness of carbon cycle models is a key issue when trying to choose the appropriate model for decision support. The input parameters of the process-based models are decisive regarding the model output. At the same time there are several input parameters for which accurate values are hard to obtain directly from experiments or no local measurements are available. Due to the uncertainty associated with the unknown model parameters significant bias can be experienced if the model is used to simulate the carbon and nitrogen cycle components of different ecosystems. In order to improve model performance the unknown model parameters has to be estimated. We developed a multi-objective, two-step calibration method based on Bayesian approach in order to estimate the unknown parameters of PaSim and Biome-BGC models. Biome-BGC and PaSim are a widely used biogeochemical models that simulate the storage and flux of water, carbon, and nitrogen between the ecosystem and the atmosphere, and within the components of the terrestrial ecosystems (in this research the developed version of Biome-BGC is used which is referred as BBGC MuSo). Both models were calibrated regardless the simulated processes and type of model parameters. The calibration procedure is based on the comparison of measured data with simulated results via calculating a likelihood function (degree of goodness-of-fit between simulated and measured data). In our research different likelihood function formulations were used in order to examine the effect of the different model
Preliminary attempt on maximum likelihood tomosynthesis reconstruction of DEI data
International Nuclear Information System (INIS)
Wang Zhentian; Huang Zhifeng; Zhang Li; Kang Kejun; Chen Zhiqiang; Zhu Peiping
2009-01-01
Tomosynthesis is a three-dimension reconstruction method that can remove the effect of superimposition with limited angle projections. It is especially promising in mammography where radiation dose is concerned. In this paper, we propose a maximum likelihood tomosynthesis reconstruction algorithm (ML-TS) on the apparent absorption data of diffraction enhanced imaging (DEI). The motivation of this contribution is to develop a tomosynthesis algorithm in low-dose or noisy circumstances and make DEI get closer to clinic application. The theoretical statistical models of DEI data in physics are analyzed and the proposed algorithm is validated with the experimental data at the Beijing Synchrotron Radiation Facility (BSRF). The results of ML-TS have better contrast compared with the well known 'shift-and-add' algorithm and FBP algorithm. (authors)
H.264 SVC Complexity Reduction Based on Likelihood Mode Decision
Directory of Open Access Journals (Sweden)
L. Balaji
2015-01-01
Full Text Available H.264 Advanced Video Coding (AVC was prolonged to Scalable Video Coding (SVC. SVC executes in different electronics gadgets such as personal computer, HDTV, SDTV, IPTV, and full-HDTV in which user demands various scaling of the same content. The various scaling is resolution, frame rate, quality, heterogeneous networks, bandwidth, and so forth. Scaling consumes more encoding time and computational complexity during mode selection. In this paper, to reduce encoding time and computational complexity, a fast mode decision algorithm based on likelihood mode decision (LMD is proposed. LMD is evaluated in both temporal and spatial scaling. From the results, we conclude that LMD performs well, when compared to the previous fast mode decision algorithms. The comparison parameters are time, PSNR, and bit rate. LMD achieve time saving of 66.65% with 0.05% detriment in PSNR and 0.17% increment in bit rate compared with the full search method.
H.264 SVC Complexity Reduction Based on Likelihood Mode Decision.
Balaji, L; Thyagharajan, K K
2015-01-01
H.264 Advanced Video Coding (AVC) was prolonged to Scalable Video Coding (SVC). SVC executes in different electronics gadgets such as personal computer, HDTV, SDTV, IPTV, and full-HDTV in which user demands various scaling of the same content. The various scaling is resolution, frame rate, quality, heterogeneous networks, bandwidth, and so forth. Scaling consumes more encoding time and computational complexity during mode selection. In this paper, to reduce encoding time and computational complexity, a fast mode decision algorithm based on likelihood mode decision (LMD) is proposed. LMD is evaluated in both temporal and spatial scaling. From the results, we conclude that LMD performs well, when compared to the previous fast mode decision algorithms. The comparison parameters are time, PSNR, and bit rate. LMD achieve time saving of 66.65% with 0.05% detriment in PSNR and 0.17% increment in bit rate compared with the full search method.
Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets
Litvinenko, Alexander
2017-09-03
We use available measurements to estimate the unknown parameters (variance, smoothness parameter, and covariance length) of a covariance function by maximizing the joint Gaussian log-likelihood function. To overcome cubic complexity in the linear algebra, we approximate the discretized covariance function in the hierarchical (H-) matrix format. The H-matrix format has a log-linear computational cost and storage O(kn log n), where the rank k is a small integer and n is the number of locations. The H-matrix technique allows us to work with general covariance matrices in an efficient way, since H-matrices can approximate inhomogeneous covariance functions, with a fairly general mesh that is not necessarily axes-parallel, and neither the covariance matrix itself nor its inverse have to be sparse. We demonstrate our method with Monte Carlo simulations and an application to soil moisture data. The C, C++ codes and data are freely available.
Music genre classification via likelihood fusion from multiple feature models
Shiu, Yu; Kuo, C.-C. J.
2005-01-01
Music genre provides an efficient way to index songs in a music database, and can be used as an effective means to retrieval music of a similar type, i.e. content-based music retrieval. A new two-stage scheme for music genre classification is proposed in this work. At the first stage, we examine a couple of different features, construct their corresponding parametric models (e.g. GMM and HMM) and compute their likelihood functions to yield soft classification results. In particular, the timbre, rhythm and temporal variation features are considered. Then, at the second stage, these soft classification results are integrated to result in a hard decision for final music genre classification. Experimental results are given to demonstrate the performance of the proposed scheme.
Marginal Maximum Likelihood Estimation of Item Response Models in R
Directory of Open Access Journals (Sweden)
Matthew S. Johnson
2007-02-01
Full Text Available Item response theory (IRT models are a class of statistical models used by researchers to describe the response behaviors of individuals to a set of categorically scored items. The most common IRT models can be classified as generalized linear fixed- and/or mixed-effect models. Although IRT models appear most often in the psychological testing literature, researchers in other fields have successfully utilized IRT-like models in a wide variety of applications. This paper discusses the three major methods of estimation in IRT and develops R functions utilizing the built-in capabilities of the R environment to find the marginal maximum likelihood estimates of the generalized partial credit model. The currently available R packages ltm is also discussed.
Maximum likelihood estimation of phase-type distributions
DEFF Research Database (Denmark)
Esparza, Luz Judith R
for both univariate and multivariate cases. Methods like the EM algorithm and Markov chain Monte Carlo are applied for this purpose. Furthermore, this thesis provides explicit formulae for computing the Fisher information matrix for discrete and continuous phase-type distributions, which is needed to find......This work is concerned with the statistical inference of phase-type distributions and the analysis of distributions with rational Laplace transform, known as matrix-exponential distributions. The thesis is focused on the estimation of the maximum likelihood parameters of phase-type distributions...... confidence regions for their estimated parameters. Finally, a new general class of distributions, called bilateral matrix-exponential distributions, is defined. These distributions have the entire real line as domain and can be used, for instance, for modelling. In addition, this class of distributions...
The elaboration likelihood model and communication about food risks.
Frewer, L J; Howard, C; Hedderley, D; Shepherd, R
1997-12-01
Factors such as hazard type and source credibility have been identified as important in the establishment of effective strategies for risk communication. The elaboration likelihood model was adapted to investigate the potential impact of hazard type, information source, and persuasive content of information on individual engagement in elaborative, or thoughtful, cognitions about risk messages. One hundred sixty respondents were allocated to one of eight experimental groups, and the effects of source credibility, persuasive content of information and hazard type were systematically varied. The impact of the different factors on beliefs about the information and elaborative processing examined. Low credibility was particularly important in reducing risk perceptions, although persuasive content and hazard type were also influential in determining whether elaborative processing occurred.
Maximum Likelihood Blood Velocity Estimator Incorporating Properties of Flow Physics
DEFF Research Database (Denmark)
Schlaikjer, Malene; Jensen, Jørgen Arendt
2004-01-01
)-data under investigation. The flow physic properties are exploited in the second term, as the range of velocity values investigated in the cross-correlation analysis are compared to the velocity estimates in the temporal and spatial neighborhood of the signal segment under investigation. The new estimator...... has been compared to the cross-correlation (CC) estimator and the previously developed maximum likelihood estimator (MLE). The results show that the CMLE can handle a larger velocity search range and is capable of estimating even low velocity levels from tissue motion. The CC and the MLE produce...... for the CC and the MLE. When the velocity search range is set to twice the limit of the CC and the MLE, the number of incorrect velocity estimates are 0, 19.1, and 7.2% for the CMLE, CC, and MLE, respectively. The ability to handle a larger search range and estimating low velocity levels was confirmed...
CONSTRUCTING A FLEXIBLE LIKELIHOOD FUNCTION FOR SPECTROSCOPIC INFERENCE
International Nuclear Information System (INIS)
Czekala, Ian; Andrews, Sean M.; Mandel, Kaisey S.; Green, Gregory M.; Hogg, David W.
2015-01-01
We present a modular, extensible likelihood framework for spectroscopic inference based on synthetic model spectra. The subtraction of an imperfect model from a continuously sampled spectrum introduces covariance between adjacent datapoints (pixels) into the residual spectrum. For the high signal-to-noise data with large spectral range that is commonly employed in stellar astrophysics, that covariant structure can lead to dramatically underestimated parameter uncertainties (and, in some cases, biases). We construct a likelihood function that accounts for the structure of the covariance matrix, utilizing the machinery of Gaussian process kernels. This framework specifically addresses the common problem of mismatches in model spectral line strengths (with respect to data) due to intrinsic model imperfections (e.g., in the atomic/molecular databases or opacity prescriptions) by developing a novel local covariance kernel formalism that identifies and self-consistently downweights pathological spectral line “outliers.” By fitting many spectra in a hierarchical manner, these local kernels provide a mechanism to learn about and build data-driven corrections to synthetic spectral libraries. An open-source software implementation of this approach is available at http://iancze.github.io/Starfish, including a sophisticated probabilistic scheme for spectral interpolation when using model libraries that are sparsely sampled in the stellar parameters. We demonstrate some salient features of the framework by fitting the high-resolution V-band spectrum of WASP-14, an F5 dwarf with a transiting exoplanet, and the moderate-resolution K-band spectrum of Gliese 51, an M5 field dwarf
Likelihood of illegal alcohol sales at professional sport stadiums.
Toomey, Traci L; Erickson, Darin J; Lenk, Kathleen M; Kilian, Gunna R
2008-11-01
Several studies have assessed the propensity for illegal alcohol sales at licensed alcohol establishments and community festivals, but no previous studies examined the propensity for these sales at professional sport stadiums. In this study, we assessed the likelihood of alcohol sales to both underage youth and obviously intoxicated patrons at professional sports stadiums across the United States, and assessed the factors related to likelihood of both types of alcohol sales. We conducted pseudo-underage (i.e., persons age 21 or older who appear under 21) and pseudo-intoxicated (i.e., persons feigning intoxication) alcohol purchase attempts at stadiums that house professional hockey, basketball, baseball, and football teams. We conducted the purchase attempts at 16 sport stadiums located in 5 states. We measured 2 outcome variables: pseudo-underage sale (yes, no) and pseudo-intoxicated sale (yes, no), and 3 types of independent variables: (1) seller characteristics, (2) purchase attempt characteristics, and (3) event characteristics. Following univariate and bivariate analyses, we a separate series of logistic generalized mixed regression models for each outcome variable. The overall sales rates to the pseudo-underage and pseudo-intoxicated buyers were 18% and 74%, respectively. In the multivariate logistic analyses, we found that the odds of a sale to a pseudo-underage buyer in the stands was 2.9 as large as the odds of a sale at the concession booths (30% vs. 13%; p = 0.01). The odds of a sale to an obviously intoxicated buyer in the stands was 2.9 as large as the odds of a sale at the concession booths (89% vs. 73%; p = 0.02). Similar to studies assessing illegal alcohol sales at licensed alcohol establishments and community festivals, findings from this study shows the need for interventions specifically focused on illegal alcohol sales at professional sporting events.
Targeted maximum likelihood estimation for a binary treatment: A tutorial.
Luque-Fernandez, Miguel Angel; Schomaker, Michael; Rachet, Bernard; Schnitzer, Mireille E
2018-04-23
When estimating the average effect of a binary treatment (or exposure) on an outcome, methods that incorporate propensity scores, the G-formula, or targeted maximum likelihood estimation (TMLE) are preferred over naïve regression approaches, which are biased under misspecification of a parametric outcome model. In contrast propensity score methods require the correct specification of an exposure model. Double-robust methods only require correct specification of either the outcome or the exposure model. Targeted maximum likelihood estimation is a semiparametric double-robust method that improves the chances of correct model specification by allowing for flexible estimation using (nonparametric) machine-learning methods. It therefore requires weaker assumptions than its competitors. We provide a step-by-step guided implementation of TMLE and illustrate it in a realistic scenario based on cancer epidemiology where assumptions about correct model specification and positivity (ie, when a study participant had 0 probability of receiving the treatment) are nearly violated. This article provides a concise and reproducible educational introduction to TMLE for a binary outcome and exposure. The reader should gain sufficient understanding of TMLE from this introductory tutorial to be able to apply the method in practice. Extensive R-code is provided in easy-to-read boxes throughout the article for replicability. Stata users will find a testing implementation of TMLE and additional material in the Appendix S1 and at the following GitHub repository: https://github.com/migariane/SIM-TMLE-tutorial. © 2018 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
Searching for degenerate Higgs bosons using a profile likelihood ratio method
Heikkilä, Jaana
ATLAS and CMS collaborations at the Large Hadron Collider have observed a new resonance con- sistent with the standard model Higgs boson. However, it has been suggested that the observed signal could also be produced by multiple nearly mass-degenerate states that couple differently to the standard model particles. In this work, a method to discriminate between the hypothesis of a single Higgs boson and that of multiple mass-degenerate Higgs bosons was developed. Using the matrix of measured signal strengths in different production and decay modes, parametrizations for the two hypotheses were constructed as a general rank 1 matrix and the most general $5 \\times 4$ matrix, respectively. The test statistic was defined as a ratio of profile likelihoods for the two hypotheses. The method was applied to the CMS measurements. The expected test statistic distribution was estimated twice by generating pseudo-experiments according to both the standard model hypothesis and the single Higgs boson hypothesis best fitting...
Brief Communication: Likelihood of societal preparedness for global change: trend detection
Directory of Open Access Journals (Sweden)
R. M. Vogel
2013-07-01
Full Text Available Anthropogenic influences on earth system processes are now pervasive, resulting in trends in river discharge, pollution levels, ocean levels, precipitation, temperature, wind, landslides, bird and plant populations and a myriad of other important natural hazards relating to earth system state variables. Thousands of trend detection studies have been published which report the statistical significance of observed trends. Unfortunately, such studies only concentrate on the null hypothesis of "no trend". Little or no attention is given to the power of such statistical trend tests, which would quantify the likelihood that we might ignore a trend if it really existed. The probability of missing the trend, if it exists, known as the type II error, informs us about the likelihood of whether or not society is prepared to accommodate and respond to such trends. We describe how the power or probability of detecting a trend if it exists, depends critically on our ability to develop improved multivariate deterministic and statistical methods for predicting future trends in earth system processes. Several other research and policy implications for improving our understanding of trend detection and our societal response to those trends are discussed.
Maximum-likelihood fitting of data dominated by Poisson statistical uncertainties
International Nuclear Information System (INIS)
Stoneking, M.R.; Den Hartog, D.J.
1996-06-01
The fitting of data by χ 2 -minimization is valid only when the uncertainties in the data are normally distributed. When analyzing spectroscopic or particle counting data at very low signal level (e.g., a Thomson scattering diagnostic), the uncertainties are distributed with a Poisson distribution. The authors have developed a maximum-likelihood method for fitting data that correctly treats the Poisson statistical character of the uncertainties. This method maximizes the total probability that the observed data are drawn from the assumed fit function using the Poisson probability function to determine the probability for each data point. The algorithm also returns uncertainty estimates for the fit parameters. They compare this method with a χ 2 -minimization routine applied to both simulated and real data. Differences in the returned fits are greater at low signal level (less than ∼20 counts per measurement). the maximum-likelihood method is found to be more accurate and robust, returning a narrower distribution of values for the fit parameters with fewer outliers
Planck 2013 results. XV. CMB power spectra and likelihood
Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Armitage-Caplan, C.; Arnaud, M.; Ashdown, M.; Atrio-Barandela, F.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bobin, J.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bridges, M.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chiang, H. C.; Chiang, L.-Y.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Delouis, J.-M.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Dunkley, J.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Gaier, T. C.; Galeotta, S.; Galli, S.; Ganga, K.; Giard, M.; Giardino, G.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D.; Helou, G.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jewell, J.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kiiveri, K.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Laureijs, R. J.; Lawrence, C. R.; Le Jeune, M.; Leach, S.; Leahy, J. P.; Leonardi, R.; León-Tavares, J.; Lesgourgues, J.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; Lindholm, V.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Maino, D.; Mandolesi, N.; Marinucci, D.; Maris, M.; Marshall, D. J.; Martin, P. G.; Martínez-González, E.; Masi, S.; Massardi, M.; Matarrese, S.; Matthai, F.; Mazzotta, P.; Meinhold, P. R.; Melchiorri, A.; Mendes, L.; Menegoni, E.; Mennella, A.; Migliaccio, M.; Millea, M.; Mitra, S.; Miville-Deschênes, M.-A.; Molinari, D.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; O'Dwyer, I. J.; Orieux, F.; Osborne, S.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paladini, R.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Paykari, P.; Perdereau, O.; Perotto, L.; Perrotta, F.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Popa, L.; Poutanen, T.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Rahlin, A.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Ricciardi, S.; Riller, T.; Ringeval, C.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Roudier, G.; Rowan-Robinson, M.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Sanselme, L.; Santos, D.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Spencer, L. D.; Starck, J.-L.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sureau, F.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Tavagnacco, D.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Tuovinen, J.; Türler, M.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Varis, J.; Vielva, P.; Villa, F.; Vittorio, N.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; White, M.; White, S. D. M.; Yvon, D.; Zacchei, A.; Zonca, A.
2014-11-01
This paper presents the Planck 2013 likelihood, a complete statistical description of the two-point correlation function of the CMB temperature fluctuations that accounts for all known relevant uncertainties, both instrumental and astrophysical in nature. We use this likelihood to derive our best estimate of the CMB angular power spectrum from Planck over three decades in multipole moment, ℓ, covering 2 ≤ ℓ ≤ 2500. The main source of uncertainty at ℓ ≲ 1500 is cosmic variance. Uncertainties in small-scale foreground modelling and instrumental noise dominate the error budget at higher ℓs. For ℓ impact of residual foreground and instrumental uncertainties on the final cosmological parameters. We find good internal agreement among the high-ℓ cross-spectra with residuals below a few μK2 at ℓ ≲ 1000, in agreement with estimated calibration uncertainties. We compare our results with foreground-cleaned CMB maps derived from all Planck frequencies, as well as with cross-spectra derived from the 70 GHz Planck map, and find broad agreement in terms of spectrum residuals and cosmological parameters. We further show that the best-fit ΛCDM cosmology is in excellent agreement with preliminary PlanckEE and TE polarisation spectra. We find that the standard ΛCDM cosmology is well constrained by Planck from the measurements at ℓ ≲ 1500. One specific example is the spectral index of scalar perturbations, for which we report a 5.4σ deviation from scale invariance, ns = 1. Increasing the multipole range beyond ℓ ≃ 1500 does not increase our accuracy for the ΛCDM parameters, but instead allows us to study extensions beyond the standard model. We find no indication of significant departures from the ΛCDM framework. Finally, we report a tension between the Planck best-fit ΛCDM model and the low-ℓ spectrum in the form of a power deficit of 5-10% at ℓ ≲ 40, with a statistical significance of 2.5-3σ. Without a theoretically motivated model for
What do parameterized Om(z) diagnostics tell us in light of recent observations?
Qi, Jing-Zhao; Cao, Shuo; Biesiada, Marek; Xu, Teng-Peng; Wu, Yan; Zhang, Si-Xuan; Zhu, Zong-Hong
2018-06-01
In this paper, we propose a new parametrization for Om(z) diagnostics and show how the most recent and significantly improved observations concerning the H(z) and SN Ia measurements can be used to probe the consistency or tension between the ΛCDM model and observations. Our results demonstrate that H 0 plays a very important role in the consistency test of ΛCDM with H(z) data. Adopting the Hubble constant priors from Planck 2013 and Riess, one finds considerable tension between the current H(z) data and ΛCDM model and confirms the conclusions obtained previously by others. However, with the Hubble constant prior taken from WMAP9, the discrepancy between H(z) data and ΛCDM disappears, i.e., the current H(z) observations still support the cosmological constant scenario. This conclusion is also supported by the results derived from the Joint Light-curve Analysis (JLA) SN Ia sample. The best-fit Hubble constant from the combination of H(z)+JLA ({H}0={68.81}-1.49+1.50 km s‑1 Mpc‑1) is very consistent with results derived both by Planck 2013 and WMAP9, but is significantly different from the recent local measurement by Riess.
A simulation study of likelihood inference procedures in rayleigh distribution with censored data
International Nuclear Information System (INIS)
Baklizi, S. A.; Baker, H. M.
2001-01-01
Inference procedures based on the likelihood function are considered for the one parameter Rayleigh distribution with type1 and type 2 censored data. Using simulation techniques, the finite sample performances of the maximum likelihood estimator and the large sample likelihood interval estimation procedures based on the Wald, the Rao, and the likelihood ratio statistics are investigated. It appears that the maximum likelihood estimator is unbiased. The approximate variance estimates obtained from the asymptotic normal distribution of the maximum likelihood estimator are accurate under type 2 censored data while they tend to be smaller than the actual variances when considering type1 censored data of small size. It appears also that interval estimation based on the Wald and Rao statistics need much more sample size than interval estimation based on the likelihood ratio statistic to attain reasonable accuracy. (authors). 15 refs., 4 tabs
Malle, Bertram F; Holbrook, Jess
2012-04-01
People interpret behavior by making inferences about agents' intentionality, mind, and personality. Past research studied such inferences 1 at a time; in real life, people make these inferences simultaneously. The present studies therefore examined whether 4 major inferences (intentionality, desire, belief, and personality), elicited simultaneously in response to an observed behavior, might be ordered in a hierarchy of likelihood and speed. To achieve generalizability, the studies included a wide range of stimulus behaviors, presented them verbally and as dynamic videos, and assessed inferences both in a retrieval paradigm (measuring the likelihood and speed of accessing inferences immediately after they were made) and in an online processing paradigm (measuring the speed of forming inferences during behavior observation). Five studies provide evidence for a hierarchy of social inferences-from intentionality and desire to belief to personality-that is stable across verbal and visual presentations and that parallels the order found in developmental and primate research. (c) 2012 APA, all rights reserved.
Maximum likelihood sequence estimation for optical complex direct modulation.
Che, Di; Yuan, Feng; Shieh, William
2017-04-17
Semiconductor lasers are versatile optical transmitters in nature. Through the direct modulation (DM), the intensity modulation is realized by the linear mapping between the injection current and the light power, while various angle modulations are enabled by the frequency chirp. Limited by the direct detection, DM lasers used to be exploited only as 1-D (intensity or angle) transmitters by suppressing or simply ignoring the other modulation. Nevertheless, through the digital coherent detection, simultaneous intensity and angle modulations (namely, 2-D complex DM, CDM) can be realized by a single laser diode. The crucial technique of CDM is the joint demodulation of intensity and differential phase with the maximum likelihood sequence estimation (MLSE), supported by a closed-form discrete signal approximation of frequency chirp to characterize the MLSE transition probability. This paper proposes a statistical method for the transition probability to significantly enhance the accuracy of the chirp model. Using the statistical estimation, we demonstrate the first single-channel 100-Gb/s PAM-4 transmission over 1600-km fiber with only 10G-class DM lasers.
Maximum likelihood estimation for cytogenetic dose-response curves
International Nuclear Information System (INIS)
Frome, E.L; DuFrain, R.J.
1983-10-01
In vitro dose-response curves are used to describe the relation between the yield of dicentric chromosome aberrations and radiation dose for human lymphocytes. The dicentric yields follow the Poisson distribution, and the expected yield depends on both the magnitude and the temporal distribution of the dose for low LET radiation. A general dose-response model that describes this relation has been obtained by Kellerer and Rossi using the theory of dual radiation action. The yield of elementary lesions is kappa[γd + g(t, tau)d 2 ], where t is the time and d is dose. The coefficient of the d 2 term is determined by the recovery function and the temporal mode of irradiation. Two special cases of practical interest are split-dose and continuous exposure experiments, and the resulting models are intrinsically nonlinear in the parameters. A general purpose maximum likelihood estimation procedure is described and illustrated with numerical examples from both experimental designs. Poisson regression analysis is used for estimation, hypothesis testing, and regression diagnostics. Results are discussed in the context of exposure assessment procedures for both acute and chronic human radiation exposure
Ringing Artefact Reduction By An Efficient Likelihood Improvement Method
Fuderer, Miha
1989-10-01
In MR imaging, the extent of the acquired spatial frequencies of the object is necessarily finite. The resulting image shows artefacts caused by "truncation" of its Fourier components. These are known as Gibbs artefacts or ringing artefacts. These artefacts are particularly. visible when the time-saving reduced acquisition method is used, say, when scanning only the lowest 70% of the 256 data lines. Filtering the data results in loss of resolution. A method is described that estimates the high frequency data from the low-frequency data lines, with the likelihood of the image as criterion. It is a computationally very efficient method, since it requires practically only two extra Fourier transforms, in addition to the normal. reconstruction. The results of this method on MR images of human subjects are promising. Evaluations on a 70% acquisition image show about 20% decrease of the error energy after processing. "Error energy" is defined as the total power of the difference to a 256-data-lines reference image. The elimination of ringing artefacts then appears almost complete..
Scale invariant for one-sided multivariate likelihood ratio tests
Directory of Open Access Journals (Sweden)
Samruam Chongcharoen
2010-07-01
Full Text Available Suppose 1 2 , ,..., n X X X is a random sample from Np ( ,V distribution. Consider 0 1 2 : ... 0 p H and1 : 0 for 1, 2,..., i H i p , let 1 0 H H denote the hypothesis that 1 H holds but 0 H does not, and let ~ 0 H denote thehypothesis that 0 H does not hold. Because the likelihood ratio test (LRT of 0 H versus 1 0 H H is complicated, severalad hoc tests have been proposed. Tang, Gnecco and Geller (1989 proposed an approximate LRT, Follmann (1996 suggestedrejecting 0 H if the usual test of 0 H versus ~ 0 H rejects 0 H with significance level 2 and a weighted sum of the samplemeans is positive, and Chongcharoen, Singh and Wright (2002 modified Follmann’s test to include information about thecorrelation structure in the sum of the sample means. Chongcharoen and Wright (2007, 2006 give versions of the Tang-Gnecco-Geller tests and Follmann-type tests, respectively, with invariance properties. With LRT’s scale invariant desiredproperty, we investigate its powers by using Monte Carlo techniques and compare them with the tests which we recommendin Chongcharoen and Wright (2007, 2006.
Maximum-likelihood estimation of recent shared ancestry (ERSA).
Huff, Chad D; Witherspoon, David J; Simonson, Tatum S; Xing, Jinchuan; Watkins, W Scott; Zhang, Yuhua; Tuohy, Therese M; Neklason, Deborah W; Burt, Randall W; Guthery, Stephen L; Woodward, Scott R; Jorde, Lynn B
2011-05-01
Accurate estimation of recent shared ancestry is important for genetics, evolution, medicine, conservation biology, and forensics. Established methods estimate kinship accurately for first-degree through third-degree relatives. We demonstrate that chromosomal segments shared by two individuals due to identity by descent (IBD) provide much additional information about shared ancestry. We developed a maximum-likelihood method for the estimation of recent shared ancestry (ERSA) from the number and lengths of IBD segments derived from high-density SNP or whole-genome sequence data. We used ERSA to estimate relationships from SNP genotypes in 169 individuals from three large, well-defined human pedigrees. ERSA is accurate to within one degree of relationship for 97% of first-degree through fifth-degree relatives and 80% of sixth-degree and seventh-degree relatives. We demonstrate that ERSA's statistical power approaches the maximum theoretical limit imposed by the fact that distant relatives frequently share no DNA through a common ancestor. ERSA greatly expands the range of relationships that can be estimated from genetic data and is implemented in a freely available software package.
Quantifying uncertainty, variability and likelihood for ordinary differential equation models
LENUS (Irish Health Repository)
Weisse, Andrea Y
2010-10-28
Abstract Background In many applications, ordinary differential equation (ODE) models are subject to uncertainty or variability in initial conditions and parameters. Both, uncertainty and variability can be quantified in terms of a probability density function on the state and parameter space. Results The partial differential equation that describes the evolution of this probability density function has a form that is particularly amenable to application of the well-known method of characteristics. The value of the density at some point in time is directly accessible by the solution of the original ODE extended by a single extra dimension (for the value of the density). This leads to simple methods for studying uncertainty, variability and likelihood, with significant advantages over more traditional Monte Carlo and related approaches especially when studying regions with low probability. Conclusions While such approaches based on the method of characteristics are common practice in other disciplines, their advantages for the study of biological systems have so far remained unrecognized. Several examples illustrate performance and accuracy of the approach and its limitations.
Affective mapping: An activation likelihood estimation (ALE) meta-analysis.
Kirby, Lauren A J; Robinson, Jennifer L
2017-11-01
Functional neuroimaging has the spatial resolution to explain the neural basis of emotions. Activation likelihood estimation (ALE), as opposed to traditional qualitative meta-analysis, quantifies convergence of activation across studies within affective categories. Others have used ALE to investigate a broad range of emotions, but without the convenience of the BrainMap database. We used the BrainMap database and analysis resources to run separate meta-analyses on coordinates reported for anger, anxiety, disgust, fear, happiness, humor, and sadness. Resultant ALE maps were compared to determine areas of convergence between emotions, as well as to identify affect-specific networks. Five out of the seven emotions demonstrated consistent activation within the amygdala, whereas all emotions consistently activated the right inferior frontal gyrus, which has been implicated as an integration hub for affective and cognitive processes. These data provide the framework for models of affect-specific networks, as well as emotional processing hubs, which can be used for future studies of functional or effective connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.
Maximum likelihood estimation for cytogenetic dose-response curves
International Nuclear Information System (INIS)
Frome, E.L.; DuFrain, R.J.
1986-01-01
In vitro dose-response curves are used to describe the relation between chromosome aberrations and radiation dose for human lymphocytes. The lymphocytes are exposed to low-LET radiation, and the resulting dicentric chromosome aberrations follow the Poisson distribution. The expected yield depends on both the magnitude and the temporal distribution of the dose. A general dose-response model that describes this relation has been presented by Kellerer and Rossi (1972, Current Topics on Radiation Research Quarterly 8, 85-158; 1978, Radiation Research 75, 471-488) using the theory of dual radiation action. Two special cases of practical interest are split-dose and continuous exposure experiments, and the resulting dose-time-response models are intrinsically nonlinear in the parameters. A general-purpose maximum likelihood estimation procedure is described, and estimation for the nonlinear models is illustrated with numerical examples from both experimental designs. Poisson regression analysis is used for estimation, hypothesis testing, and regression diagnostics. Results are discussed in the context of exposure assessment procedures for both acute and chronic human radiation exposure
Physical activity may decrease the likelihood of children developing constipation.
Seidenfaden, Sandra; Ormarsson, Orri Thor; Lund, Sigrun H; Bjornsson, Einar S
2018-01-01
Childhood constipation is common. We evaluated children diagnosed with constipation, who were referred to an Icelandic paediatric emergency department, and determined the effect of lifestyle factors on its aetiology. The parents of children who were diagnosed with constipation and participated in a phase IIB clinical trial on laxative suppositories answered an online questionnaire about their children's lifestyle and constipation in March-April 2013. The parents of nonconstipated children that visited the paediatric department of Landspitali University Hospital or an Icelandic outpatient clinic answered the same questionnaire. We analysed responses regarding 190 children aged one year to 18 years: 60 with constipation and 130 without. We found that 40% of the constipated children had recurrent symptoms, 27% had to seek medical attention more than once and 33% received medication per rectum. The 47 of 130 control group subjects aged 10-18 were much more likely to exercise more than three times a week (72%) and for more than a hour (62%) than the 26 of 60 constipated children of the same age (42% and 35%, respectively). Constipation risk factors varied with age and many children diagnosed with constipation had recurrent symptoms. Physical activity may affect the likelihood of developing constipation in older children. ©2017 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.
Kinnear, John; Jackson, Ruth
2017-07-01
Although physicians are highly trained in the application of evidence-based medicine, and are assumed to make rational decisions, there is evidence that their decision making is prone to biases. One of the biases that has been shown to affect accuracy of judgements is that of representativeness and base-rate neglect, where the saliency of a person's features leads to overestimation of their likelihood of belonging to a group. This results in the substitution of 'subjective' probability for statistical probability. This study examines clinicians' propensity to make estimations of subjective probability when presented with clinical information that is considered typical of a medical condition. The strength of the representativeness bias is tested by presenting choices in textual and graphic form. Understanding of statistical probability is also tested by omitting all clinical information. For the questions that included clinical information, 46.7% and 45.5% of clinicians made judgements of statistical probability, respectively. Where the question omitted clinical information, 79.9% of clinicians made a judgement consistent with statistical probability. There was a statistically significant difference in responses to the questions with and without representativeness information (χ2 (1, n=254)=54.45, pprobability. One of the causes for this representativeness bias may be the way clinical medicine is taught where stereotypic presentations are emphasised in diagnostic decision making. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Race of source effects in the elaboration likelihood model.
White, P H; Harkins, S G
1994-11-01
In a series of experiments, we investigated the effect of race of source on persuasive communications in the Elaboration Likelihood Model (R.E. Petty & J.T. Cacioppo, 1981, 1986). In Experiment 1, we found no evidence that White participants responded to a Black source as a simple negative cue. Experiment 2 suggested the possibility that exposure to a Black source led to low-involvement message processing. In Experiments 3 and 4, a distraction paradigm was used to test this possibility, and it was found that participants under low involvement were highly motivated to process a message presented by a Black source. In Experiment 5, we found that attitudes toward the source's ethnic group, rather than violations of expectancies, accounted for this processing effect. Taken together, the results of these experiments are consistent with S.L. Gaertner and J.F. Dovidio's (1986) theory of aversive racism, which suggests that Whites, because of a combination of egalitarian values and underlying negative racial attitudes, are very concerned about not appearing unfavorable toward Blacks, leading them to be highly motivated to process messages presented by a source from this group.
Maximum likelihood estimation for cytogenetic dose-response curves
Energy Technology Data Exchange (ETDEWEB)
Frome, E.L; DuFrain, R.J.
1983-10-01
In vitro dose-response curves are used to describe the relation between the yield of dicentric chromosome aberrations and radiation dose for human lymphocytes. The dicentric yields follow the Poisson distribution, and the expected yield depends on both the magnitude and the temporal distribution of the dose for low LET radiation. A general dose-response model that describes this relation has been obtained by Kellerer and Rossi using the theory of dual radiation action. The yield of elementary lesions is kappa(..gamma..d + g(t, tau)d/sup 2/), where t is the time and d is dose. The coefficient of the d/sup 2/ term is determined by the recovery function and the temporal mode of irradiation. Two special cases of practical interest are split-dose and continuous exposure experiments, and the resulting models are intrinsically nonlinear in the parameters. A general purpose maximum likelihood estimation procedure is described and illustrated with numerical examples from both experimental designs. Poisson regression analysis is used for estimation, hypothesis testing, and regression diagnostics. Results are discussed in the context of exposure assessment procedures for both acute and chronic human radiation exposure.
Estimating likelihood of future crashes for crash-prone drivers
Directory of Open Access Journals (Sweden)
Subasish Das
2015-06-01
Full Text Available At-fault crash-prone drivers are usually considered as the high risk group for possible future incidents or crashes. In Louisiana, 34% of crashes are repeatedly committed by the at-fault crash-prone drivers who represent only 5% of the total licensed drivers in the state. This research has conducted an exploratory data analysis based on the driver faultiness and proneness. The objective of this study is to develop a crash prediction model to estimate the likelihood of future crashes for the at-fault drivers. The logistic regression method is used by employing eight years' traffic crash data (2004–2011 in Louisiana. Crash predictors such as the driver's crash involvement, crash and road characteristics, human factors, collision type, and environmental factors are considered in the model. The at-fault and not-at-fault status of the crashes are used as the response variable. The developed model has identified a few important variables, and is used to correctly classify at-fault crashes up to 62.40% with a specificity of 77.25%. This model can identify as many as 62.40% of the crash incidence of at-fault drivers in the upcoming year. Traffic agencies can use the model for monitoring the performance of an at-fault crash-prone drivers and making roadway improvements meant to reduce crash proneness. From the findings, it is recommended that crash-prone drivers should be targeted for special safety programs regularly through education and regulations.
Smoking increases the likelihood of Helicobacter pylori treatment failure.
Itskoviz, David; Boltin, Doron; Leibovitzh, Haim; Tsadok Perets, Tsachi; Comaneshter, Doron; Cohen, Arnon; Niv, Yaron; Levi, Zohar
2017-07-01
Data regarding the impact of smoking on the success of Helicobacter pylori (H. pylori) eradication are conflicting, partially due to the fact that sociodemographic status is associated with both smoking and H. pylori treatment success. We aimed to assess the effect of smoking on H. pylori eradication rates after controlling for sociodemographic confounders. Included were subjects aged 15 years or older, with a first time positive C 13 -urea breath test (C 13 -UBT) between 2007 to 2014, who underwent a second C 13 -UBT after receiving clarithromycin-based triple therapy. Data regarding age, gender, socioeconomic status (SES), smoking (current smokers or "never smoked"), and drug use were extracted from the Clalit health maintenance organization database. Out of 120,914 subjects with a positive first time C 13 -UBT, 50,836 (42.0%) underwent a second C 13 -UBT test. After excluding former smokers, 48,130 remained who were eligible for analysis. The mean age was 44.3±18.2years, 69.2% were females, 87.8% were Jewish and 12.2% Arabs, 25.5% were current smokers. The overall eradication failure rates were 33.3%: 34.8% in current smokers and 32.8% in subjects who never smoked. In a multivariate analysis, eradication failure was positively associated with current smoking (Odds Ratio {OR} 1.15, 95% CI 1.10-1.20, psmoking was found to significantly increase the likelihood of unsuccessful first-line treatment for H. pylori infection. Copyright © 2017 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.
Obstetric History and Likelihood of Preterm Birth of Twins.
Easter, Sarah Rae; Little, Sarah E; Robinson, Julian N; Mendez-Figueroa, Hector; Chauhan, Suneet P
2018-01-05
The objective of this study was to investigate the relationship between preterm birth in a prior pregnancy and preterm birth in a twin pregnancy. We performed a secondary analysis of a randomized controlled trial evaluating 17-α-hydroxyprogesterone caproate in twins. Women were classified as nulliparous, multiparous with a prior term birth, or multiparous with a prior preterm birth. We used logistic regression to examine the odds of spontaneous preterm birth of twins before 35 weeks according to past obstetric history. Of the 653 women analyzed, 294 were nulliparas, 310 had a prior term birth, and 49 had a prior preterm birth. Prior preterm birth increased the likelihood of spontaneous delivery before 35 weeks (adjusted odds ratio [aOR]: 2.44, 95% confidence interval [CI]: 1.28-4.66), whereas prior term delivery decreased these odds (aOR: 0.55, 95% CI: 0.38-0.78) in the current twin pregnancy compared with the nulliparous reference group. This translated into a lower odds of composite neonatal morbidity (aOR: 0.38, 95% CI: 0.27-0.53) for women with a prior term delivery. For women carrying twins, a history of preterm birth increases the odds of spontaneous preterm birth, whereas a prior term birth decreases odds of spontaneous preterm birth and neonatal morbidity for the current twin pregnancy. These results offer risk stratification and reassurance for clinicians. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
Tectono-sedimentary controls on the likelihood of gas hydrate occurrence near Taiwan
Energy Technology Data Exchange (ETDEWEB)
McDonnell, S.L.; Cherkis, N.Z.; Czarnecki, M.F. [Naval Research Lab., Washington, DC (United States); Max, M.D. [MDS Research, Washington, DC (United States)
2000-09-01
Marine sediments on the continental slope of the NE South China Sea have appropriate thickness, methane-generating potential, and occur in a suitable pressure-temperature regime to host gas hydrate. Evidence for gas hydrate, the bottom simulating reflector (BSR), is observed to the south of Taiwan on reflection seismic records, and can be used to suggest that gas hydrates are widely distributed. The tectono-sedimentary framework south of Taiwan bears directly upon methane generation and the likelihood of the presence of significant gas hydrate deposits. Three zones of probable hydrate occurrence have been delineated along the margins of the NE South China Sea: (1) in a thick accumulation of sediment along the northern passive margin; (2) along a more thinly sedimented eastern active collisional margin, and especially; (3) in a zone of thick originally passive margin sedimentation into which the collisional margin has encroached obliquely. (author)
Simple simulation of diffusion bridges with application to likelihood inference for diffusions
DEFF Research Database (Denmark)
Bladt, Mogens; Sørensen, Michael
2014-01-01
the accuracy and efficiency of the approximate method and compare it to exact simulation methods. In the study, our method provides a very good approximation to the distribution of a diffusion bridge for bridges that are likely to occur in applications to statistical inference. To illustrate the usefulness......With a view to statistical inference for discretely observed diffusion models, we propose simple methods of simulating diffusion bridges, approximately and exactly. Diffusion bridge simulation plays a fundamental role in likelihood and Bayesian inference for diffusion processes. First a simple......-dimensional diffusions and is applicable to all one-dimensional diffusion processes with finite speed-measure. One advantage of the new approach is that simple simulation methods like the Milstein scheme can be applied to bridge simulation. Another advantage over previous bridge simulation methods is that the proposed...
A new maximum likelihood blood velocity estimator incorporating spatial and temporal correlation
DEFF Research Database (Denmark)
Schlaikjer, Malene; Jensen, Jørgen Arendt
2001-01-01
and space. This paper presents a new estimator (STC-MLE), which incorporates the correlation property. It is an expansion of the maximum likelihood estimator (MLE) developed by Ferrara et al. With the MLE a cross-correlation analysis between consecutive RF-lines on complex form is carried out for a range...... of possible velocities. In the new estimator an additional similarity investigation for each evaluated velocity and the available velocity estimates in a temporal (between frames) and spatial (within frames) neighborhood is performed. An a priori probability density term in the distribution...... of the observations gives a probability measure of the correlation between the velocities. Both the MLE and the STC-MLE have been evaluated on simulated and in-vivo RF-data obtained from the carotid artery. Using the MLE 4.1% of the estimates deviate significantly from the true velocities, when the performance...
DEFF Research Database (Denmark)
Philipsen, Kirsten Riber; Christiansen, Lasse Engbo; Mandsberg, Lotte Frigaard
2008-01-01
with an exponentially decaying function of the time between observations is suggested. A model with a full covariance structure containing OD-dependent variance and an autocorrelation structure is compared to a model with variance only and with no variance or correlation implemented. It is shown that the model...... are used for parameter estimation. The data is log-transformed such that a linear model can be applied. The transformation changes the variance structure, and hence an OD-dependent variance is implemented in the model. The autocorrelation in the data is demonstrated, and a correlation model...... that best describes data is a model taking into account the full covariance structure. An inference study is made in order to determine whether the growth rate of the five bacteria strains is the same. After applying a likelihood-ratio test to models with a full covariance structure, it is concluded...
Li, Xinya; Deng, Z. Daniel; Sun, Yannan; Martinez, Jayson J.; Fu, Tao; McMichael, Geoffrey A.; Carlson, Thomas J.
2014-11-01
Better understanding of fish behavior is vital for recovery of many endangered species including salmon. The Juvenile Salmon Acoustic Telemetry System (JSATS) was developed to observe the out-migratory behavior of juvenile salmonids tagged by surgical implantation of acoustic micro-transmitters and to estimate the survival when passing through dams on the Snake and Columbia Rivers. A robust three-dimensional solver was needed to accurately and efficiently estimate the time sequence of locations of fish tagged with JSATS acoustic transmitters, to describe in sufficient detail the information needed to assess the function of dam-passage design alternatives. An approximate maximum likelihood solver was developed using measurements of time difference of arrival from all hydrophones in receiving arrays on which a transmission was detected. Field experiments demonstrated that the developed solver performed significantly better in tracking efficiency and accuracy than other solvers described in the literature.
Probing modifications of general relativity using current cosmological observations
International Nuclear Information System (INIS)
Zhao Gongbo; Bacon, David J.; Koyama, Kazuya; Nichol, Robert C.; Song, Yong-Seon; Giannantonio, Tommaso; Pogosian, Levon; Silvestri, Alessandra
2010-01-01
We test general relativity (GR) using current cosmological data: the CMB from WMAP5 [E. Komatsu et al. (WMAP Collaboration), Astrophys. J. Suppl. Ser. 180, 330 (2009)], the integrated Sachs-Wolfe (ISW) effect from the cross correlation of the CMB with six galaxy catalogs [T. Giannantonio et al., Phys. Rev. D 77, 123520 (2008)], a compilation of supernovae (SNe) type Ia including the latest Sloan Digital Sky Survey SNe [R. Kessler et al., Astrophys. J. Suppl. Ser. 185, 32 (2009).], and part of the weak lensing (WL) data from the Canada-Franco-Hawaii Telescope Legacy Survey [L. Fu et al., Astron. Astrophys. 479, 9 (2008); M. Kilbinger et al., Astron. Astrophys. 497, 677 (2009).] that probe linear and mildly nonlinear scales. We first test a model in which the effective Newtonian constant μ and the ratio of the two gravitational potentials, η, transit from the GR value to another constant at late times; in this case, we find that GR is fully consistent with the combined data. The strongest constraint comes from the ISW effect which would arise from this gravitational transition; the observed ISW signal imposes a tight constraint on a combination of μ and η that characterizes the lensing potential. Next, we consider four pixels in time and space for each function μ and η, and perform a principal component analysis, finding that seven of the resulting eight eigenmodes are consistent with GR within the errors. Only one eigenmode shows a 2σ deviation from the GR prediction, which is likely to be due to a systematic effect. However, the detection of such a deviation demonstrates the power of our time- and scale-dependent principal component analysis methodology when combining observations of structure formation and expansion history to test GR.
Maximum Likelihood Estimation and Inference With Examples in R, SAS and ADMB
Millar, Russell B
2011-01-01
This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statis
Observations of the Polarisation of the Anomalous Microwave Emission: A Review
Directory of Open Access Journals (Sweden)
J. A. Rubiño-Martín
2012-01-01
Full Text Available The observational status of the polarisation of the anomalous microwave emission (AME is reviewed, both for individual compact Galactic regions as well as for the large-scale Galactic emission. There are six Galactic regions with existing polarisation constraints in the relevant range of 10–40 GHz: four dust clouds (Perseus, ρ Ophiuchi, LDN1622, and Pleiades and two HII regions (LPH96 and the Helix nebula. These constraints are discussed in detail and are complemented by deriving upper limits on the polarisation of the AME for those objects without published WMAP constraints. For the case of large-scale emission, two recent works, based on WMAP data, are reviewed. Currently, the best constraints on the fractional polarisation of the AME, at frequencies near the peak of the emission (i.e., 20–30 GHz, are at the level of ~1% (95.4% confidence level. Finally, we compare these constraints with the predictions of some theoretical AME models and discuss the possible impact of polarised AME on future primordial B-mode experiments.
Joint maximum-likelihood magnitudes of presumed underground nuclear test explosions
Peacock, Sheila; Douglas, Alan; Bowers, David
2017-08-01
Body-wave magnitudes (mb) of 606 seismic disturbances caused by presumed underground nuclear test explosions at specific test sites between 1964 and 1996 have been derived from station amplitudes collected by the International Seismological Centre (ISC), by a joint inversion for mb and station-specific magnitude corrections. A maximum-likelihood method was used to reduce the upward bias of network mean magnitudes caused by data censoring, where arrivals at stations that do not report arrivals are assumed to be hidden by the ambient noise at the time. Threshold noise levels at each station were derived from the ISC amplitudes using the method of Kelly and Lacoss, which fits to the observed magnitude-frequency distribution a Gutenberg-Richter exponential decay truncated at low magnitudes by an error function representing the low-magnitude threshold of the station. The joint maximum-likelihood inversion is applied to arrivals from the sites: Semipalatinsk (Kazakhstan) and Novaya Zemlya, former Soviet Union; Singer (Lop Nor), China; Mururoa and Fangataufa, French Polynesia; and Nevada, USA. At sites where eight or more arrivals could be used to derive magnitudes and station terms for 25 or more explosions (Nevada, Semipalatinsk and Mururoa), the resulting magnitudes and station terms were fixed and a second inversion carried out to derive magnitudes for additional explosions with three or more arrivals. 93 more magnitudes were thus derived. During processing for station thresholds, many stations were rejected for sparsity of data, obvious errors in reported amplitude, or great departure of the reported amplitude-frequency distribution from the expected left-truncated exponential decay. Abrupt changes in monthly mean amplitude at a station apparently coincide with changes in recording equipment and/or analysis method at the station.
Dark Energy Survey Year 1 Results: Multi-Probe Methodology and Simulated Likelihood Analyses
Energy Technology Data Exchange (ETDEWEB)
Krause, E.; et al.
2017-06-28
We present the methodology for and detail the implementation of the Dark Energy Survey (DES) 3x2pt DES Year 1 (Y1) analysis, which combines configuration-space two-point statistics from three different cosmological probes: cosmic shear, galaxy-galaxy lensing, and galaxy clustering, using data from the first year of DES observations. We have developed two independent modeling pipelines and describe the code validation process. We derive expressions for analytical real-space multi-probe covariances, and describe their validation with numerical simulations. We stress-test the inference pipelines in simulated likelihood analyses that vary 6-7 cosmology parameters plus 20 nuisance parameters and precisely resemble the analysis to be presented in the DES 3x2pt analysis paper, using a variety of simulated input data vectors with varying assumptions. We find that any disagreement between pipelines leads to changes in assigned likelihood $\\Delta \\chi^2 \\le 0.045$ with respect to the statistical error of the DES Y1 data vector. We also find that angular binning and survey mask do not impact our analytic covariance at a significant level. We determine lower bounds on scales used for analysis of galaxy clustering (8 Mpc$~h^{-1}$) and galaxy-galaxy lensing (12 Mpc$~h^{-1}$) such that the impact of modeling uncertainties in the non-linear regime is well below statistical errors, and show that our analysis choices are robust against a variety of systematics. These tests demonstrate that we have a robust analysis pipeline that yields unbiased cosmological parameter inferences for the flagship 3x2pt DES Y1 analysis. We emphasize that the level of independent code development and subsequent code comparison as demonstrated in this paper is necessary to produce credible constraints from increasingly complex multi-probe analyses of current data.
Maximum likelihood-based analysis of single-molecule photon arrival trajectories
Hajdziona, Marta; Molski, Andrzej
2011-02-01
In this work we explore the statistical properties of the maximum likelihood-based analysis of one-color photon arrival trajectories. This approach does not involve binning and, therefore, all of the information contained in an observed photon strajectory is used. We study the accuracy and precision of parameter estimates and the efficiency of the Akaike information criterion and the Bayesian information criterion (BIC) in selecting the true kinetic model. We focus on the low excitation regime where photon trajectories can be modeled as realizations of Markov modulated Poisson processes. The number of observed photons is the key parameter in determining model selection and parameter estimation. For example, the BIC can select the true three-state model from competing two-, three-, and four-state kinetic models even for relatively short trajectories made up of 2 × 103 photons. When the intensity levels are well-separated and 104 photons are observed, the two-state model parameters can be estimated with about 10% precision and those for a three-state model with about 20% precision.
Maximum likelihood-based analysis of single-molecule photon arrival trajectories.
Hajdziona, Marta; Molski, Andrzej
2011-02-07
In this work we explore the statistical properties of the maximum likelihood-based analysis of one-color photon arrival trajectories. This approach does not involve binning and, therefore, all of the information contained in an observed photon strajectory is used. We study the accuracy and precision of parameter estimates and the efficiency of the Akaike information criterion and the Bayesian information criterion (BIC) in selecting the true kinetic model. We focus on the low excitation regime where photon trajectories can be modeled as realizations of Markov modulated Poisson processes. The number of observed photons is the key parameter in determining model selection and parameter estimation. For example, the BIC can select the true three-state model from competing two-, three-, and four-state kinetic models even for relatively short trajectories made up of 2 × 10(3) photons. When the intensity levels are well-separated and 10(4) photons are observed, the two-state model parameters can be estimated with about 10% precision and those for a three-state model with about 20% precision.
Observational constraints on the types of cosmic strings
International Nuclear Information System (INIS)
Sazhina, Olga S.; Sazhin, Mikhail V.; Scognamiglio, Diana
2014-01-01
This paper is aimed at setting observational limits to the number of cosmic strings (Nambu-Goto, Abelian-Higgs, semilocal) and other topological defects (textures). Radio maps of CMB anisotropy, provided by the space mission Planck for various frequencies, were filtered and then processed by the method of convolution with modified Haar functions (MHF) to search for cosmic string candidates. This method was designed to search for solitary strings, without additional assumptions as regards the presence of networks of such objects. The sensitivity of the MHF method is δT ∼ 10 μK in a background of δT ∼ 100 μK. The comparison of these with previously known results on search string network shows that strings can only be semilocal in the range of 1 / 5, with the upper restriction on individual string tension (linear density) of Gμ/c 2 ≤ 7.36 x 10 -7 . The texture model is also legal. There are no strings with Gμ/c 2 > 7.36 x 10 -7 . However, a comparison with the data for the search of non-Gaussian signals shows that the presence of several (up to three) Nambu-Goto strings is also possible. For Gμ/c 2 ≤ 4.83 x 10 -7 the MHF method is ineffective because of unverifiable spurious string candidates. Thus the existence of strings with tensions Gμ/c 2 ≤ 4.83 x 10 -7 is not prohibited but it is beyond the Planck data possibilities. The same string candidates have been found in the WMAP 9-year data. Independence of Planck and WMAP data sets serves as an additional argument to consider those string candidates as very promising. However, the final proof should be given by optical deep surveys. (orig.)
Determining cosmological parameters with the latest observational data
International Nuclear Information System (INIS)
Xia Junqing; Li Hong; Zhao Gongbo; Zhang Xinmin
2008-01-01
In this paper, we combine the latest observational data, including the WMAP five-year data (WMAP5), BOOMERanG, CBI, VSA, ACBAR, as well as the baryon acoustic oscillations (BAO) and type Ia supernovae (SN) ''union'' compilation (307 sample), and use the Markov Chain Monte Carlo method to determine the cosmological parameters, such as the equation of state (EoS) of dark energy, the curvature of the universe, the total neutrino mass, and the parameters associated with the power spectrum of primordial fluctuations. In a flat universe, we obtain the tight limit on the constant EoS of dark energy as w=-0.977±0.056(stat)±0.057(sys). For the dynamical dark energy models with the time evolving EoS parametrized as w de (a)=w 0 +w 1 (1-a), we find that the best-fit values are w 0 =-1.08 and w 1 =0.368, while the ΛCDM model remains a good fit to the current data. For the curvature of the universe Ω k , our results give -0.012 k de =-1. When considering the dynamics of dark energy, the flat universe is still a good fit to the current data, -0.015 k s ≥1 are excluded at more than 2σ confidence level. However, in the framework of dynamical dark energy models, the allowed region in the parameter space of (n s ,r) is enlarged significantly. Finally, we find no strong evidence for the large running of the spectral index.
Bias Correction for the Maximum Likelihood Estimate of Ability. Research Report. ETS RR-05-15
Zhang, Jinming
2005-01-01
Lord's bias function and the weighted likelihood estimation method are effective in reducing the bias of the maximum likelihood estimate of an examinee's ability under the assumption that the true item parameters are known. This paper presents simulation studies to determine the effectiveness of these two methods in reducing the bias when the item…
Jeon, Jihyoun; Hsu, Li; Gorfine, Malka
2012-07-01
Frailty models are useful for measuring unobserved heterogeneity in risk of failures across clusters, providing cluster-specific risk prediction. In a frailty model, the latent frailties shared by members within a cluster are assumed to act multiplicatively on the hazard function. In order to obtain parameter and frailty variate estimates, we consider the hierarchical likelihood (H-likelihood) approach (Ha, Lee and Song, 2001. Hierarchical-likelihood approach for frailty models. Biometrika 88, 233-243) in which the latent frailties are treated as "parameters" and estimated jointly with other parameters of interest. We find that the H-likelihood estimators perform well when the censoring rate is low, however, they are substantially biased when the censoring rate is moderate to high. In this paper, we propose a simple and easy-to-implement bias correction method for the H-likelihood estimators under a shared frailty model. We also extend the method to a multivariate frailty model, which incorporates complex dependence structure within clusters. We conduct an extensive simulation study and show that the proposed approach performs very well for censoring rates as high as 80%. We also illustrate the method with a breast cancer data set. Since the H-likelihood is the same as the penalized likelihood function, the proposed bias correction method is also applicable to the penalized likelihood estimators.
DEFF Research Database (Denmark)
Nielsen, Jan; Parner, Erik
2010-01-01
In this paper, we model multivariate time-to-event data by composite likelihood of pairwise frailty likelihoods and marginal hazards using natural cubic splines. Both right- and interval-censored data are considered. The suggested approach is applied on two types of family studies using the gamma...
Ros, B.P.; Bijma, F.; de Munck, J.C.; de Gunst, M.C.M.
2016-01-01
This paper deals with multivariate Gaussian models for which the covariance matrix is a Kronecker product of two matrices. We consider maximum likelihood estimation of the model parameters, in particular of the covariance matrix. There is no explicit expression for the maximum likelihood estimator
Use of deterministic sampling for exploring likelihoods in linkage analysis for quantitative traits.
Mackinnon, M.J.; Beek, van der S.; Kinghorn, B.P.
1996-01-01
Deterministic sampling was used to numerically evaluate the expected log-likelihood surfaces of QTL-marker linkage models in large pedigrees with simple structures. By calculating the expected values of likelihoods, questions of power of experimental designs, bias in parameter estimates, approximate
Likelihood ratio data to report the validation of a forensic fingerprint evaluation method
Ramos, Daniel; Haraksim, Rudolf; Meuwly, Didier
2017-01-01
Data to which the authors refer to throughout this article are likelihood ratios (LR) computed from the comparison of 5–12 minutiae fingermarks with fingerprints. These LRs data are used for the validation of a likelihood ratio (LR) method in forensic evidence evaluation. These data present a
A guideline for the validation of likelihood ratio methods used for forensic evidence evaluation
Meuwly, Didier; Ramos, Daniel; Haraksim, Rudolf
2017-01-01
This Guideline proposes a protocol for the validation of forensic evaluation methods at the source level, using the Likelihood Ratio framework as defined within the Bayes’ inference model. In the context of the inference of identity of source, the Likelihood Ratio is used to evaluate the strength of
Predictors of Self-Reported Likelihood of Working with Older Adults
Eshbaugh, Elaine M.; Gross, Patricia E.; Satrom, Tatum
2010-01-01
This study examined the self-reported likelihood of working with older adults in a future career among 237 college undergraduates at a midsized Midwestern university. Although aging anxiety was not significantly related to likelihood of working with older adults, those students who had a greater level of death anxiety were less likely than other…
Krings, Franciska; Facchin, Stephanie
2009-01-01
This study demonstrated relations between men's perceptions of organizational justice and increased sexual harassment proclivities. Respondents reported higher likelihood to sexually harass under conditions of low interactional justice, suggesting that sexual harassment likelihood may increase as a response to perceived injustice. Moreover, the…
Sampling variability in forensic likelihood-ratio computation: A simulation study
Ali, Tauseef; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Meuwly, Didier
2015-01-01
Recently, in the forensic biometric community, there is a growing interest to compute a metric called “likelihood- ratio‿ when a pair of biometric specimens is compared using a biometric recognition system. Generally, a biomet- ric recognition system outputs a score and therefore a likelihood-ratio
Cheng, Qin-Bo; Chen, Xi; Xu, Chong-Yu; Reinhardt-Imjela, Christian; Schulte, Achim
2014-11-01
In this study, the likelihood functions for uncertainty analysis of hydrological models are compared and improved through the following steps: (1) the equivalent relationship between the Nash-Sutcliffe Efficiency coefficient (NSE) and the likelihood function with Gaussian independent and identically distributed residuals is proved; (2) a new estimation method of the Box-Cox transformation (BC) parameter is developed to improve the effective elimination of the heteroscedasticity of model residuals; and (3) three likelihood functions-NSE, Generalized Error Distribution with BC (BC-GED) and Skew Generalized Error Distribution with BC (BC-SGED)-are applied for SWAT-WB-VSA (Soil and Water Assessment Tool - Water Balance - Variable Source Area) model calibration in the Baocun watershed, Eastern China. Performances of calibrated models are compared using the observed river discharges and groundwater levels. The result shows that the minimum variance constraint can effectively estimate the BC parameter. The form of the likelihood function significantly impacts on the calibrated parameters and the simulated results of high and low flow components. SWAT-WB-VSA with the NSE approach simulates flood well, but baseflow badly owing to the assumption of Gaussian error distribution, where the probability of the large error is low, but the small error around zero approximates equiprobability. By contrast, SWAT-WB-VSA with the BC-GED or BC-SGED approach mimics baseflow well, which is proved in the groundwater level simulation. The assumption of skewness of the error distribution may be unnecessary, because all the results of the BC-SGED approach are nearly the same as those of the BC-GED approach.
Directory of Open Access Journals (Sweden)
Suresh Kumar
2014-10-01
Full Text Available In this paper, we study a cosmological model in general relativity within the framework of spatially flat Friedmann–Robertson–Walker space–time filled with ordinary matter (baryonic, radiation, dark matter and dark energy, where the latter two components are described by Chevallier–Polarski–Linder equation of state parameters. We utilize the observational data sets from SNLS3, BAO and Planck + WMAP9 + WiggleZ measurements of matter power spectrum to constrain the model parameters. We find that the current observational data offer tight constraints on the equation of state parameter of dark matter. We consider the perturbations and study the behavior of dark matter by observing its effects on CMB and matter power spectra. We find that the current observational data favor the cold dark matter scenario with the cosmological constant type dark energy at the present epoch.
International Nuclear Information System (INIS)
Kumar, Suresh; Xu, Lixin
2014-01-01
In this paper, we study a cosmological model in general relativity within the framework of spatially flat Friedmann–Robertson–Walker space–time filled with ordinary matter (baryonic), radiation, dark matter and dark energy, where the latter two components are described by Chevallier–Polarski–Linder equation of state parameters. We utilize the observational data sets from SNLS3, BAO and Planck + WMAP9 + WiggleZ measurements of matter power spectrum to constrain the model parameters. We find that the current observational data offer tight constraints on the equation of state parameter of dark matter. We consider the perturbations and study the behavior of dark matter by observing its effects on CMB and matter power spectra. We find that the current observational data favor the cold dark matter scenario with the cosmological constant type dark energy at the present epoch
Statistical modelling of survival data with random effects h-likelihood approach
Ha, Il Do; Lee, Youngjo
2017-01-01
This book provides a groundbreaking introduction to the likelihood inference for correlated survival data via the hierarchical (or h-) likelihood in order to obtain the (marginal) likelihood and to address the computational difficulties in inferences and extensions. The approach presented in the book overcomes shortcomings in the traditional likelihood-based methods for clustered survival data such as intractable integration. The text includes technical materials such as derivations and proofs in each chapter, as well as recently developed software programs in R (“frailtyHL”), while the real-world data examples together with an R package, “frailtyHL” in CRAN, provide readers with useful hands-on tools. Reviewing new developments since the introduction of the h-likelihood to survival analysis (methods for interval estimation of the individual frailty and for variable selection of the fixed effects in the general class of frailty models) and guiding future directions, the book is of interest to research...
The likelihood principle and its proof – a never-ending story…
DEFF Research Database (Denmark)
Jørgensen, Thomas Martini
2015-01-01
An ongoing controversy in philosophy of statistics is the so-called “likelihood principle” essentially stating that all evidence which is obtained from an experiment about an unknown quantity θ is contained in the likelihood function of θ. Common classical statistical methodology, such as the use...... of significance tests, and confidence intervals, depends on the experimental procedure and unrealized events and thus violates the likelihood principle. The likelihood principle was identified by that name and proved in a famous paper by Allan Birnbaum in 1962. However, ever since both the principle itself...... as well as the proof has been highly debated. This presentation will illustrate the debate of both the principle and its proof, from 1962 and up to today. An often-used experiment to illustrate the controversy between classical interpretation and evidential confirmation based on the likelihood principle...
Borrowing strength : a likelihood ratio test for related sparse signals
Wit, Ernst C.; Bakewell, David J. G.
2012-01-01
Motivation: Cancer biology is a field where the complexity of the phenomena battles against the availability of data. Often only a few observations per signal source, i.e. genes, are available. Such scenarios are becoming increasingly more relevant as modern sensing technologies generally have no
Observations of barred spirals
International Nuclear Information System (INIS)
Elmegreen, D.M.
1990-01-01
Observations of barred spiral galaxies are discussed which show that the presence of a bar increases the likelihood for grand design spiral structure only in early Hubble types. This result is contrary to the more common notion that grand design spiral structure generally accompanies bars in galaxies. Enhanced deprojected color images are shown which reveal that a secondary set of spiral arms commonly occurs in barred galaxies and also occasionally in ovally distorted galaxies. 6 refs
Sampling of systematic errors to estimate likelihood weights in nuclear data uncertainty propagation
International Nuclear Information System (INIS)
Helgesson, P.; Sjöstrand, H.; Koning, A.J.; Rydén, J.; Rochman, D.; Alhassan, E.; Pomp, S.
2016-01-01
In methodologies for nuclear data (ND) uncertainty assessment and propagation based on random sampling, likelihood weights can be used to infer experimental information into the distributions for the ND. As the included number of correlated experimental points grows large, the computational time for the matrix inversion involved in obtaining the likelihood can become a practical problem. There are also other problems related to the conventional computation of the likelihood, e.g., the assumption that all experimental uncertainties are Gaussian. In this study, a way to estimate the likelihood which avoids matrix inversion is investigated; instead, the experimental correlations are included by sampling of systematic errors. It is shown that the model underlying the sampling methodology (using univariate normal distributions for random and systematic errors) implies a multivariate Gaussian for the experimental points (i.e., the conventional model). It is also shown that the likelihood estimates obtained through sampling of systematic errors approach the likelihood obtained with matrix inversion as the sample size for the systematic errors grows large. In studied practical cases, it is seen that the estimates for the likelihood weights converge impractically slowly with the sample size, compared to matrix inversion. The computational time is estimated to be greater than for matrix inversion in cases with more experimental points, too. Hence, the sampling of systematic errors has little potential to compete with matrix inversion in cases where the latter is applicable. Nevertheless, the underlying model and the likelihood estimates can be easier to intuitively interpret than the conventional model and the likelihood function involving the inverted covariance matrix. Therefore, this work can both have pedagogical value and be used to help motivating the conventional assumption of a multivariate Gaussian for experimental data. The sampling of systematic errors could also
Observing participating observation
DEFF Research Database (Denmark)
Keiding, Tina Bering
2011-01-01
Current methodology concerning participating observation in general leaves the act of observation unobserved. Approaching participating observation from systems theory offers fundamental new insights into the topic. Observation is always participation. There is no way to escape becoming...
Observing participating observation
DEFF Research Database (Denmark)
Keiding, Tina Bering
2010-01-01
Current methodology concerning participating observation in general leaves the act of observation unobserved. Approaching participating observation from systems theory offers fundamental new insights into the topic. Observation is always participation. There is no way to escape becoming...
An alternative empirical likelihood method in missing response problems and causal inference.
Ren, Kaili; Drummond, Christopher A; Brewster, Pamela S; Haller, Steven T; Tian, Jiang; Cooper, Christopher J; Zhang, Biao
2016-11-30
Missing responses are common problems in medical, social, and economic studies. When responses are missing at random, a complete case data analysis may result in biases. A popular debias method is inverse probability weighting proposed by Horvitz and Thompson. To improve efficiency, Robins et al. proposed an augmented inverse probability weighting method. The augmented inverse probability weighting estimator has a double-robustness property and achieves the semiparametric efficiency lower bound when the regression model and propensity score model are both correctly specified. In this paper, we introduce an empirical likelihood-based estimator as an alternative to Qin and Zhang (2007). Our proposed estimator is also doubly robust and locally efficient. Simulation results show that the proposed estimator has better performance when the propensity score is correctly modeled. Moreover, the proposed method can be applied in the estimation of average treatment effect in observational causal inferences. Finally, we apply our method to an observational study of smoking, using data from the Cardiovascular Outcomes in Renal Atherosclerotic Lesions clinical trial. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Bayesian and maximum likelihood estimation of genetic maps
DEFF Research Database (Denmark)
York, Thomas L.; Durrett, Richard T.; Tanksley, Steven
2005-01-01
There has recently been increased interest in the use of Markov Chain Monte Carlo (MCMC)-based Bayesian methods for estimating genetic maps. The advantage of these methods is that they can deal accurately with missing data and genotyping errors. Here we present an extension of the previous methods...... of genotyping errors. A similar advantage of the Bayesian method was not observed for missing data. We also re-analyse a recently published set of data from the eggplant and show that the use of the MCMC-based method leads to smaller estimates of genetic distances....
The fine-tuning cost of the likelihood in SUSY models
Ghilencea, D M
2013-01-01
In SUSY models, the fine tuning of the electroweak (EW) scale with respect to their parameters gamma_i={m_0, m_{1/2}, mu_0, A_0, B_0,...} and the maximal likelihood L to fit the experimental data are usually regarded as two different problems. We show that, if one regards the EW minimum conditions as constraints that fix the EW scale, this commonly held view is not correct and that the likelihood contains all the information about fine-tuning. In this case we show that the corrected likelihood is equal to the ratio L/Delta of the usual likelihood L and the traditional fine tuning measure Delta of the EW scale. A similar result is obtained for the integrated likelihood over the set {gamma_i}, that can be written as a surface integral of the ratio L/Delta, with the surface in gamma_i space determined by the EW minimum constraints. As a result, a large likelihood actually demands a large ratio L/Delta or equivalently, a small chi^2_{new}=chi^2_{old}+2*ln(Delta). This shows the fine-tuning cost to the likelihood ...
Zeng, X.
2015-12-01
A large number of model executions are required to obtain alternative conceptual models' predictions and their posterior probabilities in Bayesian model averaging (BMA). The posterior model probability is estimated through models' marginal likelihood and prior probability. The heavy computation burden hinders the implementation of BMA prediction, especially for the elaborated marginal likelihood estimator. For overcoming the computation burden of BMA, an adaptive sparse grid (SG) stochastic collocation method is used to build surrogates for alternative conceptual models through the numerical experiment of a synthetical groundwater model. BMA predictions depend on model posterior weights (or marginal likelihoods), and this study also evaluated four marginal likelihood estimators, including arithmetic mean estimator (AME), harmonic mean estimator (HME), stabilized harmonic mean estimator (SHME), and thermodynamic integration estimator (TIE). The results demonstrate that TIE is accurate in estimating conceptual models' marginal likelihoods. The BMA-TIE has better predictive performance than other BMA predictions. TIE has high stability for estimating conceptual model's marginal likelihood. The repeated estimated conceptual model's marginal likelihoods by TIE have significant less variability than that estimated by other estimators. In addition, the SG surrogates are efficient to facilitate BMA predictions, especially for BMA-TIE. The number of model executions needed for building surrogates is 4.13%, 6.89%, 3.44%, and 0.43% of the required model executions of BMA-AME, BMA-HME, BMA-SHME, and BMA-TIE, respectively.
Maximal information analysis: I - various Wayne State plots and the most common likelihood principle
International Nuclear Information System (INIS)
Bonvicini, G.
2005-01-01
Statistical analysis using all moments of the likelihood L(y vertical bar α) (y being the data and α being the fit parameters) is presented. The relevant plots for various data fitting situations are presented. The goodness of fit (GOF) parameter (currently the χ 2 ) is redefined as the isoprobability level in a multidimensional space. Many useful properties of statistical analysis are summarized in a new statistical principle which states that the most common likelihood, and not the tallest, is the best possible likelihood, when comparing experiments or hypotheses
Simplified likelihood for the re-interpretation of public CMS results
The CMS Collaboration
2017-01-01
In this note, a procedure for the construction of simplified likelihoods for the re-interpretation of the results of CMS searches for new physics is presented. The procedure relies on the use of a reduced set of information on the background models used in these searches which can readily be provided by the CMS collaboration. A toy example is used to demonstrate the procedure and its accuracy in reproducing the full likelihood for setting limits in models for physics beyond the standard model. Finally, two representative searches from the CMS collaboration are used to demonstrate the validity of the simplified likelihood approach under realistic conditions.
Observational hints on the Big Bounce
International Nuclear Information System (INIS)
Mielczarek, Jakub; Kurek, Aleksandra; Szydłowski, Marek; Kamionka, Michał
2010-01-01
In this paper we study possible observational consequences of the bouncing cosmology. We consider a model where a phase of inflation is preceded by a cosmic bounce. While we consider in this paper only that the bounce is due to loop quantum gravity, most of the results presented here can be applied for different bouncing cosmologies. We concentrate on the scenario where the scalar field, as the result of contraction of the universe, is driven from the bottom of the potential well. The field is amplified, and finally the phase of the standard slow-roll inflation is realized. Such an evolution modifies the standard inflationary spectrum of perturbations by the additional oscillations and damping on the large scales. We extract the parameters of the model from the observations of the cosmic microwave background radiation. In particular, the value of inflaton mass is equal to m = (1.7±0.6)·10 13 GeV. In our considerations we base on the seven years of observations made by the WMAP satellite. We propose the new observational consistency check for the phase of slow-roll inflation. We investigate the conditions which have to be fulfilled to make the observations of the Big Bounce effects possible. We translate them to the requirements on the parameters of the model and then put the observational constraints on the model. Based on assumption usually made in loop quantum cosmology, the Barbero-Immirzi parameter was shown to be constrained by γ < 1100 from the cosmological observations. We have compared the Big Bounce model with the standard Big Bang scenario and showed that the present observational data is not informative enough to distinguish these models
Mirzakhel, Zibah
When considering factors that contribute to cancer progression, modifications to both the biological and mechanical pathways play significant roles. However, less attention is placed on how the mechanical pathways can specifically contribute to cancerous behavior. Experimental studies have found that malignant cells are significantly softer than healthy, normal cells. In a tissue environment where healthy or malignant cells exist, a distribution of cell stiffness values is observed, with the mean values used to differentiate between these two populations. Rather than focus on the mean values, emphasis will be placed on the distribution, where instances of soft and stiff cells exist in the healthy tissue environment. Since cell deformability is a trait associated with cancer, the question arises as to whether the mechanical variation observed in healthy tissue cell stiffness distributions can influence any instances of tumor growth. To approach this, a 3D discrete model of cells is used, able to monitor and predict the behavior of individual cells while determining any instances of tumor growth in a healthy tissue. In addition to the mechanical variance, the spatial arrangement of cells will also be modeled, as cell interaction could further implicate any incidences of tumor-like malignant populations within the tissue. Results have shown that the likelihood of tumor incidence is driven by both by the increases in the mechanical variation in the distributions as well as larger clustering of cells that are mechanically similar, quantified primarily through higher proliferation rates of tumor-like soft cells. This can be observed though prominent negative shifts in the mean of the distribution, as it begins to transition and show instances of earlystage tumor growth. The model reveals the impact that both the mechanical variation and spatial arrangement of cells has on tumor progression, suggesting the use of these parameters as potential novel biomarkers. With a
Evolutionary analysis of apolipoprotein E by Maximum Likelihood and complex network methods
Directory of Open Access Journals (Sweden)
Leandro de Jesus Benevides
Full Text Available Abstract Apolipoprotein E (apo E is a human glycoprotein with 299 amino acids, and it is a major component of very low density lipoproteins (VLDL and a group of high-density lipoproteins (HDL. Phylogenetic studies are important to clarify how various apo E proteins are related in groups of organisms and whether they evolved from a common ancestor. Here, we aimed at performing a phylogenetic study on apo E carrying organisms. We employed a classical and robust method, such as Maximum Likelihood (ML, and compared the results using a more recent approach based on complex networks. Thirty-two apo E amino acid sequences were downloaded from NCBI. A clear separation could be observed among three major groups: mammals, fish and amphibians. The results obtained from ML method, as well as from the constructed networks showed two different groups: one with mammals only (C1 and another with fish (C2, and a single node with the single sequence available for an amphibian. The accordance in results from the different methods shows that the complex networks approach is effective in phylogenetic studies. Furthermore, our results revealed the conservation of apo E among animal groups.
Camilo, Daniela Castro
2017-10-02
In order to model the complex non-stationary dependence structure of precipitation extremes over the entire contiguous U.S., we propose a flexible local approach based on factor copula models. Our sub-asymptotic spatial modeling framework yields non-trivial tail dependence structures, with a weakening dependence strength as events become more extreme, a feature commonly observed with precipitation data but not accounted for in classical asymptotic extreme-value models. To estimate the local extremal behavior, we fit the proposed model in small regional neighborhoods to high threshold exceedances, under the assumption of local stationarity. This allows us to gain in flexibility, while making inference for such a large and complex dataset feasible. Adopting a local censored likelihood approach, inference is made on a fine spatial grid, and local estimation is performed taking advantage of distributed computing resources and of the embarrassingly parallel nature of this estimation procedure. The local model is efficiently fitted at all grid points, and uncertainty is measured using a block bootstrap procedure. An extensive simulation study shows that our approach is able to adequately capture complex, non-stationary dependencies, while our study of U.S. winter precipitation data reveals interesting differences in local tail structures over space, which has important implications on regional risk assessment of extreme precipitation events. A comparison between past and current data suggests that extremes in certain areas might be slightly wider in extent nowadays than during the first half of the twentieth century.
Maximum Likelihood Time-of-Arrival Estimation of Optical Pulses via Photon-Counting Photodetectors
Erkmen, Baris I.; Moision, Bruce E.
2010-01-01
Many optical imaging, ranging, and communications systems rely on the estimation of the arrival time of an optical pulse. Recently, such systems have been increasingly employing photon-counting photodetector technology, which changes the statistics of the observed photocurrent. This requires time-of-arrival estimators to be developed and their performances characterized. The statistics of the output of an ideal photodetector, which are well modeled as a Poisson point process, were considered. An analytical model was developed for the mean-square error of the maximum likelihood (ML) estimator, demonstrating two phenomena that cause deviations from the minimum achievable error at low signal power. An approximation was derived to the threshold at which the ML estimator essentially fails to provide better than a random guess of the pulse arrival time. Comparing the analytic model performance predictions to those obtained via simulations, it was verified that the model accurately predicts the ML performance over all regimes considered. There is little prior art that attempts to understand the fundamental limitations to time-of-arrival estimation from Poisson statistics. This work establishes both a simple mathematical description of the error behavior, and the associated physical processes that yield this behavior. Previous work on mean-square error characterization for ML estimators has predominantly focused on additive Gaussian noise. This work demonstrates that the discrete nature of the Poisson noise process leads to a distinctly different error behavior.
Implementation of linear filters for iterative penalized maximum likelihood SPECT reconstruction
International Nuclear Information System (INIS)
Liang, Z.
1991-01-01
This paper reports on six low-pass linear filters applied in frequency space implemented for iterative penalized maximum-likelihood (ML) SPECT image reconstruction. The filters implemented were the Shepp-Logan filter, the Butterworth filer, the Gaussian filter, the Hann filter, the Parzen filer, and the Lagrange filter. The low-pass filtering was applied in frequency space to projection data for the initial estimate and to the difference of projection data and reprojected data for higher order approximations. The projection data were acquired experimentally from a chest phantom consisting of non-uniform attenuating media. All the filters could effectively remove the noise and edge artifacts associated with ML approach if the frequency cutoff was properly chosen. The improved performance of the Parzen and Lagrange filters relative to the others was observed. The best image, by viewing its profiles in terms of noise-smoothing, edge-sharpening, and contrast, was the one obtained with the Parzen filter. However, the Lagrange filter has the potential to consider the characteristics of detector response function
Khakzad, Nima; Khan, Faisal; Amyotte, Paul
2015-07-01
Compared to the remarkable progress in risk analysis of normal accidents, the risk analysis of major accidents has not been so well-established, partly due to the complexity of such accidents and partly due to low probabilities involved. The issue of low probabilities normally arises from the scarcity of major accidents' relevant data since such accidents are few and far between. In this work, knowing that major accidents are frequently preceded by accident precursors, a novel precursor-based methodology has been developed for likelihood modeling of major accidents in critical infrastructures based on a unique combination of accident precursor data, information theory, and approximate reasoning. For this purpose, we have introduced an innovative application of information analysis to identify the most informative near accident of a major accident. The observed data of the near accident were then used to establish predictive scenarios to foresee the occurrence of the major accident. We verified the methodology using offshore blowouts in the Gulf of Mexico, and then demonstrated its application to dam breaches in the United Sates. © 2015 Society for Risk Analysis.
Maximum likelihood estimation of semiparametric mixture component models for competing risks data.
Choi, Sangbum; Huang, Xuelin
2014-09-01
In the analysis of competing risks data, the cumulative incidence function is a useful quantity to characterize the crude risk of failure from a specific event type. In this article, we consider an efficient semiparametric analysis of mixture component models on cumulative incidence functions. Under the proposed mixture model, latency survival regressions given the event type are performed through a class of semiparametric models that encompasses the proportional hazards model and the proportional odds model, allowing for time-dependent covariates. The marginal proportions of the occurrences of cause-specific events are assessed by a multinomial logistic model. Our mixture modeling approach is advantageous in that it makes a joint estimation of model parameters associated with all competing risks under consideration, satisfying the constraint that the cumulative probability of failing from any cause adds up to one given any covariates. We develop a novel maximum likelihood scheme based on semiparametric regression analysis that facilitates efficient and reliable estimation. Statistical inferences can be conveniently made from the inverse of the observed information matrix. We establish the consistency and asymptotic normality of the proposed estimators. We validate small sample properties with simulations and demonstrate the methodology with a data set from a study of follicular lymphoma. © 2014, The International Biometric Society.
Yuan, Ke-Hai; Tian, Yubin; Yanagihara, Hirokazu
2015-06-01
Survey data typically contain many variables. Structural equation modeling (SEM) is commonly used in analyzing such data. The most widely used statistic for evaluating the adequacy of a SEM model is T ML, a slight modification to the likelihood ratio statistic. Under normality assumption, T ML approximately follows a chi-square distribution when the number of observations (N) is large and the number of items or variables (p) is small. However, in practice, p can be rather large while N is always limited due to not having enough participants. Even with a relatively large N, empirical results show that T ML rejects the correct model too often when p is not too small. Various corrections to T ML have been proposed, but they are mostly heuristic. Following the principle of the Bartlett correction, this paper proposes an empirical approach to correct T ML so that the mean of the resulting statistic approximately equals the degrees of freedom of the nominal chi-square distribution. Results show that empirically corrected statistics follow the nominal chi-square distribution much more closely than previously proposed corrections to T ML, and they control type I errors reasonably well whenever N ≥ max(50,2p). The formulations of the empirically corrected statistics are further used to predict type I errors of T ML as reported in the literature, and they perform well.
Camilo, Daniela Castro; Huser, Raphaë l
2017-01-01
In order to model the complex non-stationary dependence structure of precipitation extremes over the entire contiguous U.S., we propose a flexible local approach based on factor copula models. Our sub-asymptotic spatial modeling framework yields non-trivial tail dependence structures, with a weakening dependence strength as events become more extreme, a feature commonly observed with precipitation data but not accounted for in classical asymptotic extreme-value models. To estimate the local extremal behavior, we fit the proposed model in small regional neighborhoods to high threshold exceedances, under the assumption of local stationarity. This allows us to gain in flexibility, while making inference for such a large and complex dataset feasible. Adopting a local censored likelihood approach, inference is made on a fine spatial grid, and local estimation is performed taking advantage of distributed computing resources and of the embarrassingly parallel nature of this estimation procedure. The local model is efficiently fitted at all grid points, and uncertainty is measured using a block bootstrap procedure. An extensive simulation study shows that our approach is able to adequately capture complex, non-stationary dependencies, while our study of U.S. winter precipitation data reveals interesting differences in local tail structures over space, which has important implications on regional risk assessment of extreme precipitation events. A comparison between past and current data suggests that extremes in certain areas might be slightly wider in extent nowadays than during the first half of the twentieth century.
Debris Likelihood, based on GhostNet, NASA Aqua MODIS, and GOES Imager, EXPERIMENTAL
National Oceanic and Atmospheric Administration, Department of Commerce — Debris Likelihood Index (Estimated) is calculated from GhostNet, NASA Aqua MODIS Chl a and NOAA GOES Imager SST data. THIS IS AN EXPERIMENTAL PRODUCT: intended...
A biclustering algorithm for binary matrices based on penalized Bernoulli likelihood
Lee, Seokho; Huang, Jianhua Z.
2013-01-01
We propose a new biclustering method for binary data matrices using the maximum penalized Bernoulli likelihood estimation. Our method applies a multi-layer model defined on the logits of the success probabilities, where each layer represents a
Performances of the likelihood-ratio classifier based on different data modelings
Chen, C.; Veldhuis, Raymond N.J.
2008-01-01
The classical likelihood ratio classifier easily collapses in many biometric applications especially with independent training-test subjects. The reason lies in the inaccurate estimation of the underlying user-specific feature density. Firstly, the feature density estimation suffers from
Finite mixture model: A maximum likelihood estimation approach on time series data
Yen, Phoong Seuk; Ismail, Mohd Tahir; Hamzah, Firdaus Mohamad
2014-09-01
Recently, statistician emphasized on the fitting of finite mixture model by using maximum likelihood estimation as it provides asymptotic properties. In addition, it shows consistency properties as the sample sizes increases to infinity. This illustrated that maximum likelihood estimation is an unbiased estimator. Moreover, the estimate parameters obtained from the application of maximum likelihood estimation have smallest variance as compared to others statistical method as the sample sizes increases. Thus, maximum likelihood estimation is adopted in this paper to fit the two-component mixture model in order to explore the relationship between rubber price and exchange rate for Malaysia, Thailand, Philippines and Indonesia. Results described that there is a negative effect among rubber price and exchange rate for all selected countries.
Moral Identity Predicts Doping Likelihood via Moral Disengagement and Anticipated Guilt.
Kavussanu, Maria; Ring, Christopher
2017-08-01
In this study, we integrated elements of social cognitive theory of moral thought and action and the social cognitive model of moral identity to better understand doping likelihood in athletes. Participants (N = 398) recruited from a variety of team sports completed measures of moral identity, moral disengagement, anticipated guilt, and doping likelihood. Moral identity predicted doping likelihood indirectly via moral disengagement and anticipated guilt. Anticipated guilt about potential doping mediated the relationship between moral disengagement and doping likelihood. Our findings provide novel evidence to suggest that athletes, who feel that being a moral person is central to their self-concept, are less likely to use banned substances due to their lower tendency to morally disengage and the more intense feelings of guilt they expect to experience for using banned substances.
Cash, W.
1979-01-01
Many problems in the experimental estimation of parameters for models can be solved through use of the likelihood ratio test. Applications of the likelihood ratio, with particular attention to photon counting experiments, are discussed. The procedures presented solve a greater range of problems than those currently in use, yet are no more difficult to apply. The procedures are proved analytically, and examples from current problems in astronomy are discussed.
Maximum Likelihood Approach for RFID Tag Set Cardinality Estimation with Detection Errors
DEFF Research Database (Denmark)
Nguyen, Chuyen T.; Hayashi, Kazunori; Kaneko, Megumi
2013-01-01
Abstract Estimation schemes of Radio Frequency IDentification (RFID) tag set cardinality are studied in this paper using Maximum Likelihood (ML) approach. We consider the estimation problem under the model of multiple independent reader sessions with detection errors due to unreliable radio...... is evaluated under dierent system parameters and compared with that of the conventional method via computer simulations assuming flat Rayleigh fading environments and framed-slotted ALOHA based protocol. Keywords RFID tag cardinality estimation maximum likelihood detection error...
Directory of Open Access Journals (Sweden)
Azam Zaka
2014-10-01
Full Text Available This paper is concerned with the modifications of maximum likelihood, moments and percentile estimators of the two parameter Power function distribution. Sampling behavior of the estimators is indicated by Monte Carlo simulation. For some combinations of parameter values, some of the modified estimators appear better than the traditional maximum likelihood, moments and percentile estimators with respect to bias, mean square error and total deviation.
Practical Statistics for LHC Physicists: Descriptive Statistics, Probability and Likelihood (1/3)
CERN. Geneva
2015-01-01
These lectures cover those principles and practices of statistics that are most relevant for work at the LHC. The first lecture discusses the basic ideas of descriptive statistics, probability and likelihood. The second lecture covers the key ideas in the frequentist approach, including confidence limits, profile likelihoods, p-values, and hypothesis testing. The third lecture covers inference in the Bayesian approach. Throughout, real-world examples will be used to illustrate the practical application of the ideas. No previous knowledge is assumed.
DEFF Research Database (Denmark)
Christensen, Ole Fredslund; Frydenberg, Morten; Jensen, Jens Ledet
2005-01-01
The large deviation modified likelihood ratio statistic is studied for testing a variance component equal to a specified value. Formulas are presented in the general balanced case, whereas in the unbalanced case only the one-way random effects model is studied. Simulation studies are presented......, showing that the normal approximation to the large deviation modified likelihood ratio statistic gives confidence intervals for variance components with coverage probabilities very close to the nominal confidence coefficient....
Anticipating cognitive effort: roles of perceived error-likelihood and time demands.
Dunn, Timothy L; Inzlicht, Michael; Risko, Evan F
2017-11-13
Why are some actions evaluated as effortful? In the present set of experiments we address this question by examining individuals' perception of effort when faced with a trade-off between two putative cognitive costs: how much time a task takes vs. how error-prone it is. Specifically, we were interested in whether individuals anticipate engaging in a small amount of hard work (i.e., low time requirement, but high error-likelihood) vs. a large amount of easy work (i.e., high time requirement, but low error-likelihood) as being more effortful. In between-subject designs, Experiments 1 through 3 demonstrated that individuals anticipate options that are high in perceived error-likelihood (yet less time consuming) as more effortful than options that are perceived to be more time consuming (yet low in error-likelihood). Further, when asked to evaluate which of the two tasks was (a) more effortful, (b) more error-prone, and (c) more time consuming, effort-based and error-based choices closely tracked one another, but this was not the case for time-based choices. Utilizing a within-subject design, Experiment 4 demonstrated overall similar pattern of judgments as Experiments 1 through 3. However, both judgments of error-likelihood and time demand similarly predicted effort judgments. Results are discussed within the context of extant accounts of cognitive control, with considerations of how error-likelihood and time demands may independently and conjunctively factor into judgments of cognitive effort.
The likelihood ratio as a random variable for linked markers in kinship analysis.
Egeland, Thore; Slooten, Klaas
2016-11-01
The likelihood ratio is the fundamental quantity that summarizes the evidence in forensic cases. Therefore, it is important to understand the theoretical properties of this statistic. This paper is the last in a series of three, and the first to study linked markers. We show that for all non-inbred pairwise kinship comparisons, the expected likelihood ratio in favor of a type of relatedness depends on the allele frequencies only via the number of alleles, also for linked markers, and also if the true relationship is another one than is tested for by the likelihood ratio. Exact expressions for the expectation and variance are derived for all these cases. Furthermore, we show that the expected likelihood ratio is a non-increasing function if the recombination rate increases between 0 and 0.5 when the actual relationship is the one investigated by the LR. Besides being of theoretical interest, exact expressions such as obtained here can be used for software validation as they allow to verify the correctness up to arbitrary precision. The paper also presents results and advice of practical importance. For example, we argue that the logarithm of the likelihood ratio behaves in a fundamentally different way than the likelihood ratio itself in terms of expectation and variance, in agreement with its interpretation as weight of evidence. Equipped with the results presented and freely available software, one may check calculations and software and also do power calculations.
Xu, Maoqi; Chen, Liang
2018-01-01
The individual sample heterogeneity is one of the biggest obstacles in biomarker identification for complex diseases such as cancers. Current statistical models to identify differentially expressed genes between disease and control groups often overlook the substantial human sample heterogeneity. Meanwhile, traditional nonparametric tests lose detailed data information and sacrifice the analysis power, although they are distribution free and robust to heterogeneity. Here, we propose an empirical likelihood ratio test with a mean-variance relationship constraint (ELTSeq) for the differential expression analysis of RNA sequencing (RNA-seq). As a distribution-free nonparametric model, ELTSeq handles individual heterogeneity by estimating an empirical probability for each observation without making any assumption about read-count distribution. It also incorporates a constraint for the read-count overdispersion, which is widely observed in RNA-seq data. ELTSeq demonstrates a significant improvement over existing methods such as edgeR, DESeq, t-tests, Wilcoxon tests and the classic empirical likelihood-ratio test when handling heterogeneous groups. It will significantly advance the transcriptomics studies of cancers and other complex disease. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Improved efficiency of maximum likelihood analysis of time series with temporally correlated errors
Langbein, John
2017-08-01
Most time series of geophysical phenomena have temporally correlated errors. From these measurements, various parameters are estimated. For instance, from geodetic measurements of positions, the rates and changes in rates are often estimated and are used to model tectonic processes. Along with the estimates of the size of the parameters, the error in these parameters needs to be assessed. If temporal correlations are not taken into account, or each observation is assumed to be independent, it is likely that any estimate of the error of these parameters will be too low and the estimated value of the parameter will be biased. Inclusion of better estimates of uncertainties is limited by several factors, including selection of the correct model for the background noise and the computational requirements to estimate the parameters of the selected noise model for cases where there are numerous observations. Here, I address the second problem of computational efficiency using maximum likelihood estimates (MLE). Most geophysical time series have background noise processes that can be represented as a combination of white and power-law noise, 1/f^{α } with frequency, f. With missing data, standard spectral techniques involving FFTs are not appropriate. Instead, time domain techniques involving construction and inversion of large data covariance matrices are employed. Bos et al. (J Geod, 2013. doi: 10.1007/s00190-012-0605-0) demonstrate one technique that substantially increases the efficiency of the MLE methods, yet is only an approximate solution for power-law indices >1.0 since they require the data covariance matrix to be Toeplitz. That restriction can be removed by simply forming a data filter that adds noise processes rather than combining them in quadrature. Consequently, the inversion of the data covariance matrix is simplified yet provides robust results for a wider range of power-law indices.
Rivera, Diego; Rivas, Yessica; Godoy, Alex
2015-02-01
Hydrological models are simplified representations of natural processes and subject to errors. Uncertainty bounds are a commonly used way to assess the impact of an input or model architecture uncertainty in model outputs. Different sets of parameters could have equally robust goodness-of-fit indicators, which is known as Equifinality. We assessed the outputs from a lumped conceptual hydrological model to an agricultural watershed in central Chile under strong interannual variability (coefficient of variability of 25%) by using the Equifinality concept and uncertainty bounds. The simulation period ran from January 1999 to December 2006. Equifinality and uncertainty bounds from GLUE methodology (Generalized Likelihood Uncertainty Estimation) were used to identify parameter sets as potential representations of the system. The aim of this paper is to exploit the use of uncertainty bounds to differentiate behavioural parameter sets in a simple hydrological model. Then, we analyze the presence of equifinality in order to improve the identification of relevant hydrological processes. The water balance model for Chillan River exhibits, at a first stage, equifinality. However, it was possible to narrow the range for the parameters and eventually identify a set of parameters representing the behaviour of the watershed (a behavioural model) in agreement with observational and soft data (calculation of areal precipitation over the watershed using an isohyetal map). The mean width of the uncertainty bound around the predicted runoff for the simulation period decreased from 50 to 20 m3s-1 after fixing the parameter controlling the areal precipitation over the watershed. This decrement is equivalent to decreasing the ratio between simulated and observed discharge from 5.2 to 2.5. Despite the criticisms against the GLUE methodology, such as the lack of statistical formality, it is identified as a useful tool assisting the modeller with the identification of critical parameters.
BOOK REVIEW: Observational Cosmology Observational Cosmology
Howell, Dale Andrew
2013-04-01
. However, these are usually pointed to in the 'further reading' section at the end of each chapter. I found this to be a welcome compromise: derivations are important but tedious; you should have access to them, but they would bog down a book such as this. Some of the experimental techniques of modern-day cosmology are of sufficient complexity that they require a thorough explanation of the particulars of an experiment intertwined with the fundamentals of cosmology. This is where the book both shines and stumbles. Learning spherical harmonics as an abstraction is a bore. But if you know it will help you to interpret the latest WMAP results, it seems like a vital tool. Pairing topics like these is great for motivation, but at times the execution is lacking. Spherical harmonics are dispensed with in a few paragraphs and a handful of equations. And there are no exercises provided to help students master the basics. This lack of outlets for students to test their knowledge is a serious issue. There are no problem sets at the end of each chapter. Occasionally an exercise is interspersed into the text, but these are relatively rare. The burden will be on the professor to come up with interesting problems to challenge students on most of the topics. A related problem is that the math in the book is too advanced for most undergraduates. After consultation with a British colleague, I don't think this is just a difference between expectations in the American and British systems. In addition to the aforementioned spherical harmonics, advanced Fourier techniques and complicated matrices are presented, with too little background provided. Even tensors are brushed on. Observational Cosmology also tries to serve as a kind of primer on the terminology used by cosmologists. Perhaps this is to help students understand talks, where knowledge of such esoterica as BzK galaxies, Schmidt laws, and Shapiro delays is assumed. This is admirable, and often succeeds, but the result is a book that is
Ellis, Sam; Reader, Andrew J
2018-04-26
Many clinical contexts require the acquisition of multiple positron emission tomography (PET) scans of a single subject, for example to observe and quantify changes in functional behaviour in tumours after treatment in oncology. Typically, the datasets from each of these scans are reconstructed individually, without exploiting the similarities between them. We have recently shown that sharing information between longitudinal PET datasets by penalising voxel-wise differences during image reconstruction can improve reconstructed images by reducing background noise and increasing the contrast-to-noise ratio of high activity lesions. Here we present two additional novel longitudinal difference-image priors and evaluate their performance using 2D simulation studies and a 3D real dataset case study. We have previously proposed a simultaneous difference-image-based penalised maximum likelihood (PML) longitudinal image reconstruction method that encourages sparse difference images (DS-PML), and in this work we propose two further novel prior terms. The priors are designed to encourage longitudinal images with corresponding differences which have i) low entropy (DE-PML), and ii) high sparsity in their spatial gradients (DTV-PML). These two new priors and the originally proposed longitudinal prior were applied to 2D simulated treatment response [ 18 F]fluorodeoxyglucose (FDG) brain tumour datasets and compared to standard maximum likelihood expectation-maximisation (MLEM) reconstructions. These 2D simulation studies explored the effects of penalty strengths, tumour behaviour, and inter-scan coupling on reconstructed images. Finally, a real two-scan longitudinal data series acquired from a head and neck cancer patient was reconstructed with the proposed methods and the results compared to standard reconstruction methods. Using any of the three priors with an appropriate penalty strength produced images with noise levels equivalent to those seen when using standard
The fine-tuning cost of the likelihood in SUSY models
International Nuclear Information System (INIS)
Ghilencea, D.M.; Ross, G.G.
2013-01-01
In SUSY models, the fine-tuning of the electroweak (EW) scale with respect to their parameters γ i ={m 0 ,m 1/2 ,μ 0 ,A 0 ,B 0 ,…} and the maximal likelihood L to fit the experimental data are usually regarded as two different problems. We show that, if one regards the EW minimum conditions as constraints that fix the EW scale, this commonly held view is not correct and that the likelihood contains all the information about fine-tuning. In this case we show that the corrected likelihood is equal to the ratio L/Δ of the usual likelihood L and the traditional fine-tuning measure Δ of the EW scale. A similar result is obtained for the integrated likelihood over the set {γ i }, that can be written as a surface integral of the ratio L/Δ, with the surface in γ i space determined by the EW minimum constraints. As a result, a large likelihood actually demands a large ratio L/Δ or equivalently, a small χ new 2 =χ old 2 +2lnΔ. This shows the fine-tuning cost to the likelihood (χ new 2 ) of the EW scale stability enforced by SUSY, that is ignored in data fits. A good χ new 2 /d.o.f.≈1 thus demands SUSY models have a fine-tuning amount Δ≪exp(d.o.f./2), which provides a model-independent criterion for acceptable fine-tuning. If this criterion is not met, one can thus rule out SUSY models without a further χ 2 /d.o.f. analysis. Numerical methods to fit the data can easily be adapted to account for this effect.
Rice, John D; Tsodikov, Alex
2017-05-30
Continuous outcome data with a proportion of observations equal to zero (often referred to as semicontinuous data) arise frequently in biomedical studies. Typical approaches involve two-part models, with one part a logistic model for the probability of observing a zero and some parametric continuous distribution for modeling the positive part of the data. We propose a semiparametric model based on a biological system with competing damage manifestation and resistance processes. This allows us to derive a closed-form profile likelihood based on the retro-hazard function, leading to a flexible procedure for modeling continuous data with a point mass at zero. A simulation study is presented to examine the properties of the method in finite samples. We apply the method to a data set consisting of pulmonary capillary hemorrhage area in lab rats subjected to diagnostic ultrasound. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Castrillon, Julio
2015-11-10
We develop a multi-level restricted Gaussian maximum likelihood method for estimating the covariance function parameters and computing the best unbiased predictor. Our approach produces a new set of multi-level contrasts where the deterministic parameters of the model are filtered out thus enabling the estimation of the covariance parameters to be decoupled from the deterministic component. Moreover, the multi-level covariance matrix of the contrasts exhibit fast decay that is dependent on the smoothness of the covariance function. Due to the fast decay of the multi-level covariance matrix coefficients only a small set is computed with a level dependent criterion. We demonstrate our approach on problems of up to 512,000 observations with a Matérn covariance function and highly irregular placements of the observations. In addition, these problems are numerically unstable and hard to solve with traditional methods.
Expert elicitation on ultrafine particles: likelihood of health effects and causal pathways
Directory of Open Access Journals (Sweden)
Brunekreef Bert
2009-07-01
Full Text Available Abstract Background Exposure to fine ambient particulate matter (PM has consistently been associated with increased morbidity and mortality. The relationship between exposure to ultrafine particles (UFP and health effects is less firmly established. If UFP cause health effects independently from coarser fractions, this could affect health impact assessment of air pollution, which would possibly lead to alternative policy options to be considered to reduce the disease burden of PM. Therefore, we organized an expert elicitation workshop to assess the evidence for a causal relationship between exposure to UFP and health endpoints. Methods An expert elicitation on the health effects of ambient ultrafine particle exposure was carried out, focusing on: 1 the likelihood of causal relationships with key health endpoints, and 2 the likelihood of potential causal pathways for cardiac events. Based on a systematic peer-nomination procedure, fourteen European experts (epidemiologists, toxicologists and clinicians were selected, of whom twelve attended. They were provided with a briefing book containing key literature. After a group discussion, individual expert judgments in the form of ratings of the likelihood of causal relationships and pathways were obtained using a confidence scheme adapted from the one used by the Intergovernmental Panel on Climate Change. Results The likelihood of an independent causal relationship between increased short-term UFP exposure and increased all-cause mortality, hospital admissions for cardiovascular and respiratory diseases, aggravation of asthma symptoms and lung function decrements was rated medium to high by most experts. The likelihood for long-term UFP exposure to be causally related to all cause mortality, cardiovascular and respiratory morbidity and lung cancer was rated slightly lower, mostly medium. The experts rated the likelihood of each of the six identified possible causal pathways separately. Out of these
Energy Technology Data Exchange (ETDEWEB)
Kubo, Taichi [Univ. of Tsukuba (Japan)
2008-02-01
We have measured the top quark mass with the dynamical likelihood method. The data corresponding to an integrated luminosity of 1.7fb^{-1} was collected in proton antiproton collisions at a center of mass energy of 1.96 TeV with the CDF detector at Fermilab Tevatron during the period March 2002-March 2007. We select t$\\bar{t}$ pair production candidates by requiring one high energy lepton and four jets, in which at least one of jets must be tagged as a b-jet. In order to reconstruct the top quark mass, we use the dynamical likelihood method based on maximum likelihood method where a likelihood is defined as the differential cross section multiplied by the transfer function from observed quantities to parton quantities, as a function of the top quark mass and the jet energy scale(JES). With this method, we measure the top quark mass to be 171.6 ± 2.0 (stat.+ JES) ± 1.3(syst.) = 171.6 ± 2.4 GeV/c^{2}.
Assessing Compatibility of Direct Detection Data: Halo-Independent Global Likelihood Analyses
Gelmini, Graciela B.
2016-10-18
We present two different halo-independent methods utilizing a global maximum likelihood that can assess the compatibility of dark matter direct detection data given a particular dark matter model. The global likelihood we use is comprised of at least one extended likelihood and an arbitrary number of Poisson or Gaussian likelihoods. In the first method we find the global best fit halo function and construct a two sided pointwise confidence band, which can then be compared with those derived from the extended likelihood alone to assess the joint compatibility of the data. In the second method we define a "constrained parameter goodness-of-fit" test statistic, whose $p$-value we then use to define a "plausibility region" (e.g. where $p \\geq 10\\%$). For any halo function not entirely contained within the plausibility region, the level of compatibility of the data is very low (e.g. $p < 10 \\%$). As an example we apply these methods to CDMS-II-Si and SuperCDMS data, assuming dark matter particles with elastic s...
Physician Bayesian updating from personal beliefs about the base rate and likelihood ratio.
Rottman, Benjamin Margolin
2017-02-01
Whether humans can accurately make decisions in line with Bayes' rule has been one of the most important yet contentious topics in cognitive psychology. Though a number of paradigms have been used for studying Bayesian updating, rarely have subjects been allowed to use their own preexisting beliefs about the prior and the likelihood. A study is reported in which physicians judged the posttest probability of a diagnosis for a patient vignette after receiving a test result, and the physicians' posttest judgments were compared to the normative posttest calculated from their own beliefs in the sensitivity and false positive rate of the test (likelihood ratio) and prior probability of the diagnosis. On the one hand, the posttest judgments were strongly related to the physicians' beliefs about both the prior probability as well as the likelihood ratio, and the priors were used considerably more strongly than in previous research. On the other hand, both the prior and the likelihoods were still not used quite as much as they should have been, and there was evidence of other nonnormative aspects to the updating, such as updating independent of the likelihood beliefs. By focusing on how physicians use their own prior beliefs for Bayesian updating, this study provides insight into how well experts perform probabilistic inference in settings in which they rely upon their own prior beliefs rather than experimenter-provided cues. It suggests that there is reason to be optimistic about experts' abilities, but that there is still considerable need for improvement.
A Walk on the Wild Side: The Impact of Music on Risk-Taking Likelihood
Enström, Rickard; Schmaltz, Rodney
2017-01-01
From a marketing perspective, there has been substantial interest in on the role of risk-perception on consumer behavior. Specific ‘problem music’ like rap and heavy metal has long been associated with delinquent behavior, including violence, drug use, and promiscuous sex. Although individuals’ risk preferences have been investigated across a range of decision-making situations, there has been little empirical work demonstrating the direct role music may have on the likelihood of engaging in risky activities. In the exploratory study reported here, we assessed the impact of listening to different styles of music while assessing risk-taking likelihood through a psychometric scale. Risk-taking likelihood was measured across ethical, financial, health and safety, recreational and social domains. Through the means of a canonical correlation analysis, the multivariate relationship between different music styles and individual risk-taking likelihood across the different domains is discussed. Our results indicate that listening to different types of music does influence risk-taking likelihood, though not in areas of health and safety. PMID:28539908
A Walk on the Wild Side: The Impact of Music on Risk-Taking Likelihood.
Enström, Rickard; Schmaltz, Rodney
2017-01-01
From a marketing perspective, there has been substantial interest in on the role of risk-perception on consumer behavior. Specific 'problem music' like rap and heavy metal has long been associated with delinquent behavior, including violence, drug use, and promiscuous sex. Although individuals' risk preferences have been investigated across a range of decision-making situations, there has been little empirical work demonstrating the direct role music may have on the likelihood of engaging in risky activities. In the exploratory study reported here, we assessed the impact of listening to different styles of music while assessing risk-taking likelihood through a psychometric scale. Risk-taking likelihood was measured across ethical, financial, health and safety, recreational and social domains. Through the means of a canonical correlation analysis, the multivariate relationship between different music styles and individual risk-taking likelihood across the different domains is discussed. Our results indicate that listening to different types of music does influence risk-taking likelihood, though not in areas of health and safety.
Susceptibility, likelihood to be diagnosed, worry and fear for contracting Lyme disease.
Fogel, Joshua; Chawla, Gurasees S
Risk perception and psychological concerns are relevant for understanding how people view Lyme disease. This study investigates the four separate outcomes of susceptibility, likelihood to be diagnosed, worry, and fear for contracting Lyme disease. University students (n=713) were surveyed about demographics, perceived health, Lyme disease knowledge, Lyme disease preventive behaviors, Lyme disease history, and Lyme disease miscellaneous variables. We found that women were associated with increased susceptibility and fear. Asian/Asian-American race/ethnicity was associated with increased worry and fear. Perceived good health was associated with increased likelihood to be diagnosed, worry, and fear. Correct knowledge was associated with increased susceptibility and likelihood to be diagnosed. Those who typically spend a lot of time outdoors were associated with increased susceptibility, likelihood to be diagnosed, worry, and fear. In conclusion, healthcare providers and public health campaigns should address susceptibility, likelihood to be diagnosed, worry, and fear about Lyme disease, and should particularly target women and Asians/Asian-Americans to address any possible misconceptions and/or offer effective coping strategies. Copyright © 2016 King Saud Bin Abdulaziz University for Health Sciences. Published by Elsevier Ltd. All rights reserved.
A Walk on the Wild Side: The Impact of Music on Risk-Taking Likelihood
Directory of Open Access Journals (Sweden)
Rickard Enström
2017-05-01
Full Text Available From a marketing perspective, there has been substantial interest in on the role of risk-perception on consumer behavior. Specific ‘problem music’ like rap and heavy metal has long been associated with delinquent behavior, including violence, drug use, and promiscuous sex. Although individuals’ risk preferences have been investigated across a range of decision-making situations, there has been little empirical work demonstrating the direct role music may have on the likelihood of engaging in risky activities. In the exploratory study reported here, we assessed the impact of listening to different styles of music while assessing risk-taking likelihood through a psychometric scale. Risk-taking likelihood was measured across ethical, financial, health and safety, recreational and social domains. Through the means of a canonical correlation analysis, the multivariate relationship between different music styles and individual risk-taking likelihood across the different domains is discussed. Our results indicate that listening to different types of music does influence risk-taking likelihood, though not in areas of health and safety.
Ryu, Jihye; Lee, Chaeyoung
2014-12-01
Positive selection not only increases beneficial allele frequency but also causes augmentation of allele frequencies of sequence variants in close proximity. Signals for positive selection were detected by the statistical differences in subsequent allele frequencies. To identify selection signatures in Korean cattle, we applied a composite log-likelihood (CLL)-based method, which calculates a composite likelihood of the allelic frequencies observed across sliding windows of five adjacent loci and compares the value with the critical statistic estimated by 50,000 permutations. Data for a total of 11,799 nucleotide polymorphisms were used with 71 Korean cattle and 209 foreign beef cattle. As a result, 147 signals were identified for Korean cattle based on CLL estimates (P selected. Further genetic association analysis with 41 intragenic variants in the selection signatures with the greatest CLL for each chromosome revealed that marbling score was associated with five variants. Intensive association studies with all the selection signatures identified in this study are required to exclude signals associated with other phenotypes or signals falsely detected and thus to identify genetic markers for meat quality. © 2014 Stichting International Foundation for Animal Genetics.
Deconvolving the wedge: maximum-likelihood power spectra via spherical-wave visibility modelling
Ghosh, A.; Mertens, F. G.; Koopmans, L. V. E.
2018-03-01
Direct detection of the Epoch of Reionization (EoR) via the red-shifted 21-cm line will have unprecedented implications on the study of structure formation in the infant Universe. To fulfil this promise, current and future 21-cm experiments need to detect this weak EoR signal in the presence of foregrounds that are several orders of magnitude larger. This requires extreme noise control and improved wide-field high dynamic-range imaging techniques. We propose a new imaging method based on a maximum likelihood framework which solves for the interferometric equation directly on the sphere, or equivalently in the uvw-domain. The method uses the one-to-one relation between spherical waves and spherical harmonics (SpH). It consistently handles signals from the entire sky, and does not require a w-term correction. The SpH coefficients represent the sky-brightness distribution and the visibilities in the uvw-domain, and provide a direct estimate of the spatial power spectrum. Using these spectrally smooth SpH coefficients, bright foregrounds can be removed from the signal, including their side-lobe noise, which is one of the limiting factors in high dynamics-range wide-field imaging. Chromatic effects causing the so-called `wedge' are effectively eliminated (i.e. deconvolved) in the cylindrical (k⊥, k∥) power spectrum, compared to a power spectrum computed directly from the images of the foreground visibilities where the wedge is clearly present. We illustrate our method using simulated Low-Frequency Array observations, finding an excellent reconstruction of the input EoR signal with minimal bias.
Penalized maximum likelihood reconstruction for x-ray differential phase-contrast tomography
International Nuclear Information System (INIS)
Brendel, Bernhard; Teuffenbach, Maximilian von; Noël, Peter B.; Pfeiffer, Franz; Koehler, Thomas
2016-01-01
Purpose: The purpose of this work is to propose a cost function with regularization to iteratively reconstruct attenuation, phase, and scatter images simultaneously from differential phase contrast (DPC) acquisitions, without the need of phase retrieval, and examine its properties. Furthermore this reconstruction method is applied to an acquisition pattern that is suitable for a DPC tomographic system with continuously rotating gantry (sliding window acquisition), overcoming the severe smearing in noniterative reconstruction. Methods: We derive a penalized maximum likelihood reconstruction algorithm to directly reconstruct attenuation, phase, and scatter image from the measured detector values of a DPC acquisition. The proposed penalty comprises, for each of the three images, an independent smoothing prior. Image quality of the proposed reconstruction is compared to images generated with FBP and iterative reconstruction after phase retrieval. Furthermore, the influence between the priors is analyzed. Finally, the proposed reconstruction algorithm is applied to experimental sliding window data acquired at a synchrotron and results are compared to reconstructions based on phase retrieval. Results: The results show that the proposed algorithm significantly increases image quality in comparison to reconstructions based on phase retrieval. No significant mutual influence between the proposed independent priors could be observed. Further it could be illustrated that the iterative reconstruction of a sliding window acquisition results in images with substantially reduced smearing artifacts. Conclusions: Although the proposed cost function is inherently nonconvex, it can be used to reconstruct images with less aliasing artifacts and less streak artifacts than reconstruction methods based on phase retrieval. Furthermore, the proposed method can be used to reconstruct images of sliding window acquisitions with negligible smearing artifacts
Likelihood inference of non-constant diversification rates with incomplete taxon sampling.
Höhna, Sebastian
2014-01-01
Large-scale phylogenies provide a valuable source to study background diversification rates and investigate if the rates have changed over time. Unfortunately most large-scale, dated phylogenies are sparsely sampled (fewer than 5% of the described species) and taxon sampling is not uniform. Instead, taxa are frequently sampled to obtain at least one representative per subgroup (e.g. family) and thus to maximize diversity (diversified sampling). So far, such complications have been ignored, potentially biasing the conclusions that have been reached. In this study I derive the likelihood of a birth-death process with non-constant (time-dependent) diversification rates and diversified taxon sampling. Using simulations I test if the true parameters and the sampling method can be recovered when the trees are small or medium sized (fewer than 200 taxa). The results show that the diversification rates can be inferred and the estimates are unbiased for large trees but are biased for small trees (fewer than 50 taxa). Furthermore, model selection by means of Akaike's Information Criterion favors the true model if the true rates differ sufficiently from alternative models (e.g. the birth-death model is recovered if the extinction rate is large and compared to a pure-birth model). Finally, I applied six different diversification rate models--ranging from a constant-rate pure birth process to a decreasing speciation rate birth-death process but excluding any rate shift models--on three large-scale empirical phylogenies (ants, mammals and snakes with respectively 149, 164 and 41 sampled species). All three phylogenies were constructed by diversified taxon sampling, as stated by the authors. However only the snake phylogeny supported diversified taxon sampling. Moreover, a parametric bootstrap test revealed that none of the tested models provided a good fit to the observed data. The model assumptions, such as homogeneous rates across species or no rate shifts, appear to be
Likelihood inference of non-constant diversification rates with incomplete taxon sampling.
Directory of Open Access Journals (Sweden)
Sebastian Höhna
Full Text Available Large-scale phylogenies provide a valuable source to study background diversification rates and investigate if the rates have changed over time. Unfortunately most large-scale, dated phylogenies are sparsely sampled (fewer than 5% of the described species and taxon sampling is not uniform. Instead, taxa are frequently sampled to obtain at least one representative per subgroup (e.g. family and thus to maximize diversity (diversified sampling. So far, such complications have been ignored, potentially biasing the conclusions that have been reached. In this study I derive the likelihood of a birth-death process with non-constant (time-dependent diversification rates and diversified taxon sampling. Using simulations I test if the true parameters and the sampling method can be recovered when the trees are small or medium sized (fewer than 200 taxa. The results show that the diversification rates can be inferred and the estimates are unbiased for large trees but are biased for small trees (fewer than 50 taxa. Furthermore, model selection by means of Akaike's Information Criterion favors the true model if the true rates differ sufficiently from alternative models (e.g. the birth-death model is recovered if the extinction rate is large and compared to a pure-birth model. Finally, I applied six different diversification rate models--ranging from a constant-rate pure birth process to a decreasing speciation rate birth-death process but excluding any rate shift models--on three large-scale empirical phylogenies (ants, mammals and snakes with respectively 149, 164 and 41 sampled species. All three phylogenies were constructed by diversified taxon sampling, as stated by the authors. However only the snake phylogeny supported diversified taxon sampling. Moreover, a parametric bootstrap test revealed that none of the tested models provided a good fit to the observed data. The model assumptions, such as homogeneous rates across species or no rate shifts, appear
Directory of Open Access Journals (Sweden)
Cătălina Lionte
2016-12-01
Full Text Available Purpose: Acute exposure to a systemic poison represents an important segment of medical emergencies. We aimed to estimate the likelihood of systemic poison-induced morbidity in a population admitted in a tertiary referral center from North East Romania, based on the determinant factors. Methodology: This was a prospective observational cohort study on adult poisoned patients. Demographic, clinical and laboratory characteristics were recorded in all patients. We analyzed three groups of patients, based on the associated morbidity during hospitalization. We identified significant differences between groups and predictors with significant effects on morbidity using multiple multinomial logistic regressions. ROC analysis proved that a combination of tests could improve diagnostic accuracy of poison-related morbidity. Main findings: Of the 180 patients included, aged 44.7 ± 17.2 years, 51.1% males, 49.4% had no poison-related morbidity, 28.9% developed a mild morbidity, and 21.7% had a severe morbidity, followed by death in 16 patients (8.9%. Multiple complications and deaths were recorded in patients aged 53.4 ± 17.6 years (p .001, with a lower Glasgow Coma Scale (GCS score upon admission and a significantly higher heart rate (101 ± 32 beats/min, p .011. Routine laboratory tests were significantly higher in patients with a recorded morbidity. Multiple logistic regression analysis demonstrated that a GCS < 8, a high white blood cells count (WBC, alanine aminotransferase (ALAT, myoglobin, glycemia and brain natriuretic peptide (BNP are strongly predictive for in-hospital severe morbidity. Originality: This is the first Romanian prospective study on adult poisoned patients, which identifies the factors responsible for in-hospital morbidity using logistic regression analyses, with resulting receiver operating characteristic (ROC curves. Conclusion: In acute intoxication with systemic poisons, we identified several clinical and laboratory variables
Generalized linear models with random effects unified analysis via H-likelihood
Lee, Youngjo; Pawitan, Yudi
2006-01-01
Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range of applications, including combining information over trials (meta-analysis), analysis of frailty models for survival data, genetic epidemiology, and analysis of spatial and temporal models with correlated errors.Written by pioneering authorities in the field, this reference provides an introduction to various theories and examines likelihood inference and GLMs. The authors show how to extend the class of GLMs while retaining as much simplicity as possible. By maximizing and deriving other quantities from h-likelihood, they also demonstrate how to use a single algorithm for all members of the class, resulting in a faster algorithm as compared to existing alternatives. Complementing theory with examples, many of...
Parallelization of maximum likelihood fits with OpenMP and CUDA
Jarp, S; Leduc, J; Nowak, A; Pantaleo, F
2011-01-01
Data analyses based on maximum likelihood fits are commonly used in the high energy physics community for fitting statistical models to data samples. This technique requires the numerical minimization of the negative log-likelihood function. MINUIT is the most common package used for this purpose in the high energy physics community. The main algorithm in this package, MIGRAD, searches the minimum by using the gradient information. The procedure requires several evaluations of the function, depending on the number of free parameters and their initial values. The whole procedure can be very CPU-time consuming in case of complex functions, with several free parameters, many independent variables and large data samples. Therefore, it becomes particularly important to speed-up the evaluation of the negative log-likelihood function. In this paper we present an algorithm and its implementation which benefits from data vectorization and parallelization (based on OpenMP) and which was also ported to Graphics Processi...
Maximum likelihood positioning for gamma-ray imaging detectors with depth of interaction measurement
International Nuclear Information System (INIS)
Lerche, Ch.W.; Ros, A.; Monzo, J.M.; Aliaga, R.J.; Ferrando, N.; Martinez, J.D.; Herrero, V.; Esteve, R.; Gadea, R.; Colom, R.J.; Toledo, J.; Mateo, F.; Sebastia, A.; Sanchez, F.; Benlloch, J.M.
2009-01-01
The center of gravity algorithm leads to strong artifacts for gamma-ray imaging detectors that are based on monolithic scintillation crystals and position sensitive photo-detectors. This is a consequence of using the centroids as position estimates. The fact that charge division circuits can also be used to compute the standard deviation of the scintillation light distribution opens a way out of this drawback. We studied the feasibility of maximum likelihood estimation for computing the true gamma-ray photo-conversion position from the centroids and the standard deviation of the light distribution. The method was evaluated on a test detector that consists of the position sensitive photomultiplier tube H8500 and a monolithic LSO crystal (42mmx42mmx10mm). Spatial resolution was measured for the centroids and the maximum likelihood estimates. The results suggest that the maximum likelihood positioning is feasible and partially removes the strong artifacts of the center of gravity algorithm.
Maximum likelihood positioning for gamma-ray imaging detectors with depth of interaction measurement
Energy Technology Data Exchange (ETDEWEB)
Lerche, Ch.W. [Grupo de Sistemas Digitales, ITACA, Universidad Politecnica de Valencia, 46022 Valencia (Spain)], E-mail: lerche@ific.uv.es; Ros, A. [Grupo de Fisica Medica Nuclear, IFIC, Universidad de Valencia-Consejo Superior de Investigaciones Cientificas, 46980 Paterna (Spain); Monzo, J.M.; Aliaga, R.J.; Ferrando, N.; Martinez, J.D.; Herrero, V.; Esteve, R.; Gadea, R.; Colom, R.J.; Toledo, J.; Mateo, F.; Sebastia, A. [Grupo de Sistemas Digitales, ITACA, Universidad Politecnica de Valencia, 46022 Valencia (Spain); Sanchez, F.; Benlloch, J.M. [Grupo de Fisica Medica Nuclear, IFIC, Universidad de Valencia-Consejo Superior de Investigaciones Cientificas, 46980 Paterna (Spain)
2009-06-01
The center of gravity algorithm leads to strong artifacts for gamma-ray imaging detectors that are based on monolithic scintillation crystals and position sensitive photo-detectors. This is a consequence of using the centroids as position estimates. The fact that charge division circuits can also be used to compute the standard deviation of the scintillation light distribution opens a way out of this drawback. We studied the feasibility of maximum likelihood estimation for computing the true gamma-ray photo-conversion position from the centroids and the standard deviation of the light distribution. The method was evaluated on a test detector that consists of the position sensitive photomultiplier tube H8500 and a monolithic LSO crystal (42mmx42mmx10mm). Spatial resolution was measured for the centroids and the maximum likelihood estimates. The results suggest that the maximum likelihood positioning is feasible and partially removes the strong artifacts of the center of gravity algorithm.
Maximum likelihood estimation for Cox's regression model under nested case-control sampling
DEFF Research Database (Denmark)
Scheike, Thomas Harder; Juul, Anders
2004-01-01
-like growth factor I was associated with ischemic heart disease. The study was based on a population of 3784 Danes and 231 cases of ischemic heart disease where controls were matched on age and gender. We illustrate the use of the MLE for these data and show how the maximum likelihood framework can be used......Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazards...... model. The MLE is computed by the EM-algorithm, which is easy to implement in the proportional hazards setting. Standard errors are estimated by a numerical profile likelihood approach based on EM aided differentiation. The work was motivated by a nested case-control study that hypothesized that insulin...
Maximum Likelihood Blind Channel Estimation for Space-Time Coding Systems
Directory of Open Access Journals (Sweden)
Hakan A. Çırpan
2002-05-01
Full Text Available Sophisticated signal processing techniques have to be developed for capacity enhancement of future wireless communication systems. In recent years, space-time coding is proposed to provide significant capacity gains over the traditional communication systems in fading wireless channels. Space-time codes are obtained by combining channel coding, modulation, transmit diversity, and optional receive diversity in order to provide diversity at the receiver and coding gain without sacrificing the bandwidth. In this paper, we consider the problem of blind estimation of space-time coded signals along with the channel parameters. Both conditional and unconditional maximum likelihood approaches are developed and iterative solutions are proposed. The conditional maximum likelihood algorithm is based on iterative least squares with projection whereas the unconditional maximum likelihood approach is developed by means of finite state Markov process modelling. The performance analysis issues of the proposed methods are studied. Finally, some simulation results are presented.
Uncertainty about the true source. A note on the likelihood ratio at the activity level.
Taroni, Franco; Biedermann, Alex; Bozza, Silvia; Comte, Jennifer; Garbolino, Paolo
2012-07-10
This paper focuses on likelihood ratio based evaluations of fibre evidence in cases in which there is uncertainty about whether or not the reference item available for analysis - that is, an item typically taken from the suspect or seized at his home - is the item actually worn at the time of the offence. A likelihood ratio approach is proposed that, for situations in which certain categorical assumptions can be made about additionally introduced parameters, converges to formula described in existing literature. The properties of the proposed likelihood ratio approach are analysed through sensitivity analyses and discussed with respect to possible argumentative implications that arise in practice. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Daniel L. Rabosky
2006-01-01
Full Text Available Rates of species origination and extinction can vary over time during evolutionary radiations, and it is possible to reconstruct the history of diversification using molecular phylogenies of extant taxa only. Maximum likelihood methods provide a useful framework for inferring temporal variation in diversification rates. LASER is a package for the R programming environment that implements maximum likelihood methods based on the birth-death process to test whether diversification rates have changed over time. LASER contrasts the likelihood of phylogenetic data under models where diversification rates have changed over time to alternative models where rates have remained constant over time. Major strengths of the package include the ability to detect temporal increases in diversification rates and the inference of diversification parameters under multiple rate-variable models of diversification. The program and associated documentation are freely available from the R package archive at http://cran.r-project.org.
Likelihood for transcriptions in a genetic regulatory system under asymmetric stable Lévy noise.
Wang, Hui; Cheng, Xiujun; Duan, Jinqiao; Kurths, Jürgen; Li, Xiaofan
2018-01-01
This work is devoted to investigating the evolution of concentration in a genetic regulation system, when the synthesis reaction rate is under additive and multiplicative asymmetric stable Lévy fluctuations. By focusing on the impact of skewness (i.e., non-symmetry) in the probability distributions of noise, we find that via examining the mean first exit time (MFET) and the first escape probability (FEP), the asymmetric fluctuations, interacting with nonlinearity in the system, lead to peculiar likelihood for transcription. This includes, in the additive noise case, realizing higher likelihood of transcription for larger positive skewness (i.e., asymmetry) index β, causing a stochastic bifurcation at the non-Gaussianity index value α = 1 (i.e., it is a separating point or line for the likelihood for transcription), and achieving a turning point at the threshold value β≈-0.5 (i.e., beyond which the likelihood for transcription suddenly reversed for α values). The stochastic bifurcation and turning point phenomena do not occur in the symmetric noise case (β = 0). While in the multiplicative noise case, non-Gaussianity index value α = 1 is a separating point or line for both the MFET and the FEP. We also investigate the noise enhanced stability phenomenon. Additionally, we are able to specify the regions in the whole parameter space for the asymmetric noise, in which we attain desired likelihood for transcription. We have conducted a series of numerical experiments in "regulating" the likelihood of gene transcription by tuning asymmetric stable Lévy noise indexes. This work offers insights for possible ways of achieving gene regulation in experimental research.
Generalized Empirical Likelihood-Based Focused Information Criterion and Model Averaging
Directory of Open Access Journals (Sweden)
Naoya Sueishi
2013-07-01
Full Text Available This paper develops model selection and averaging methods for moment restriction models. We first propose a focused information criterion based on the generalized empirical likelihood estimator. We address the issue of selecting an optimal model, rather than a correct model, for estimating a specific parameter of interest. Then, this study investigates a generalized empirical likelihood-based model averaging estimator that minimizes the asymptotic mean squared error. A simulation study suggests that our averaging estimator can be a useful alternative to existing post-selection estimators.
Maximum likelihood estimation of the parameters of nonminimum phase and noncausal ARMA models
DEFF Research Database (Denmark)
Rasmussen, Klaus Bolding
1994-01-01
The well-known prediction-error-based maximum likelihood (PEML) method can only handle minimum phase ARMA models. This paper presents a new method known as the back-filtering-based maximum likelihood (BFML) method, which can handle nonminimum phase and noncausal ARMA models. The BFML method...... is identical to the PEML method in the case of a minimum phase ARMA model, and it turns out that the BFML method incorporates a noncausal ARMA filter with poles outside the unit circle for estimation of the parameters of a causal, nonminimum phase ARMA model...
Maximum likelihood estimation of the position of a radiating source in a waveguide
International Nuclear Information System (INIS)
Hinich, M.J.
1979-01-01
An array of sensors is receiving radiation from a source of interest. The source and the array are in a one- or two-dimensional waveguide. The maximum-likelihood estimators of the coordinates of the source are analyzed under the assumptions that the noise field is Gaussian. The Cramer-Rao lower bound is of the order of the number of modes which define the source excitation function. The results show that the accuracy of the maximum likelihood estimator of source depth using a vertical array in a infinite horizontal waveguide (such as the ocean) is limited by the number of modes detected by the array regardless of the array size
A maximum pseudo-likelihood approach for estimating species trees under the coalescent model
Directory of Open Access Journals (Sweden)
Edwards Scott V
2010-10-01
Full Text Available Abstract Background Several phylogenetic approaches have been developed to estimate species trees from collections of gene trees. However, maximum likelihood approaches for estimating species trees under the coalescent model are limited. Although the likelihood of a species tree under the multispecies coalescent model has already been derived by Rannala and Yang, it can be shown that the maximum likelihood estimate (MLE of the species tree (topology, branch lengths, and population sizes from gene trees under this formula does not exist. In this paper, we develop a pseudo-likelihood function of the species tree to obtain maximum pseudo-likelihood estimates (MPE of species trees, with branch lengths of the species tree in coalescent units. Results We show that the MPE of the species tree is statistically consistent as the number M of genes goes to infinity. In addition, the probability that the MPE of the species tree matches the true species tree converges to 1 at rate O(M -1. The simulation results confirm that the maximum pseudo-likelihood approach is statistically consistent even when the species tree is in the anomaly zone. We applied our method, Maximum Pseudo-likelihood for Estimating Species Trees (MP-EST to a mammal dataset. The four major clades found in the MP-EST tree are consistent with those in the Bayesian concatenation tree. The bootstrap supports for the species tree estimated by the MP-EST method are more reasonable than the posterior probability supports given by the Bayesian concatenation method in reflecting the level of uncertainty in gene trees and controversies over the relationship of four major groups of placental mammals. Conclusions MP-EST can consistently estimate the topology and branch lengths (in coalescent units of the species tree. Although the pseudo-likelihood is derived from coalescent theory, and assumes no gene flow or horizontal gene transfer (HGT, the MP-EST method is robust to a small amount of HGT in the
Regularization parameter selection methods for ill-posed Poisson maximum likelihood estimation
International Nuclear Information System (INIS)
Bardsley, Johnathan M; Goldes, John
2009-01-01
In image processing applications, image intensity is often measured via the counting of incident photons emitted by the object of interest. In such cases, image data noise is accurately modeled by a Poisson distribution. This motivates the use of Poisson maximum likelihood estimation for image reconstruction. However, when the underlying model equation is ill-posed, regularization is needed. Regularized Poisson likelihood estimation has been studied extensively by the authors, though a problem of high importance remains: the choice of the regularization parameter. We will present three statistically motivated methods for choosing the regularization parameter, and numerical examples will be presented to illustrate their effectiveness
Planck 2015 results: XI. CMB power spectra, likelihoods, and robustness of parameters
DEFF Research Database (Denmark)
Aghanim, N.; Arnaud, M.; Ashdown, M.
2016-01-01
on the same hybrid approach used for the previous release, i.e., a pixel-based likelihood at low multipoles (ℓ data and of Planck polarization......This paper presents the Planck 2015 likelihoods, statistical descriptions of the 2-point correlationfunctions of the cosmic microwave background (CMB) temperature and polarization fluctuations that account for relevant uncertainties, both instrumental and astrophysical in nature. They are based...... information, along with more detailed models of foregrounds and instrumental uncertainties. The increased redundancy brought by more than doubling the amount of data analysed enables further consistency checks and enhanced immunity to systematic effects. It also improves the constraining power of Planck...
Average Likelihood Methods of Classification of Code Division Multiple Access (CDMA)
2016-05-01
subject to code matrices that follows the structure given by (113). [⃗ yR y⃗I ] = √ Es 2L [ GR1 −GI1 GI2 GR2 ] [ QR −QI QI QR ] [⃗ bR b⃗I ] + [⃗ nR n⃗I... QR ] [⃗ b+ b⃗− ] + [⃗ n+ n⃗− ] (115) The average likelihood for type 4 CDMA (116) is a special case of type 1 CDMA with twice the code length and...AVERAGE LIKELIHOOD METHODS OF CLASSIFICATION OF CODE DIVISION MULTIPLE ACCESS (CDMA) MAY 2016 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE
Block Empirical Likelihood for Longitudinal Single-Index Varying-Coefficient Model
Directory of Open Access Journals (Sweden)
Yunquan Song
2013-01-01
Full Text Available In this paper, we consider a single-index varying-coefficient model with application to longitudinal data. In order to accommodate the within-group correlation, we apply the block empirical likelihood procedure to longitudinal single-index varying-coefficient model, and prove a nonparametric version of Wilks’ theorem which can be used to construct the block empirical likelihood confidence region with asymptotically correct coverage probability for the parametric component. In comparison with normal approximations, the proposed method does not require a consistent estimator for the asymptotic covariance matrix, making it easier to conduct inference for the model's parametric component. Simulations demonstrate how the proposed method works.
Design of Simplified Maximum-Likelihood Receivers for Multiuser CPM Systems
Directory of Open Access Journals (Sweden)
Li Bing
2014-01-01
Full Text Available A class of simplified maximum-likelihood receivers designed for continuous phase modulation based multiuser systems is proposed. The presented receiver is built upon a front end employing mismatched filters and a maximum-likelihood detector defined in a low-dimensional signal space. The performance of the proposed receivers is analyzed and compared to some existing receivers. Some schemes are designed to implement the proposed receivers and to reveal the roles of different system parameters. Analysis and numerical results show that the proposed receivers can approach the optimum multiuser receivers with significantly (even exponentially in some cases reduced complexity and marginal performance degradation.
Design of simplified maximum-likelihood receivers for multiuser CPM systems.
Bing, Li; Bai, Baoming
2014-01-01
A class of simplified maximum-likelihood receivers designed for continuous phase modulation based multiuser systems is proposed. The presented receiver is built upon a front end employing mismatched filters and a maximum-likelihood detector defined in a low-dimensional signal space. The performance of the proposed receivers is analyzed and compared to some existing receivers. Some schemes are designed to implement the proposed receivers and to reveal the roles of different system parameters. Analysis and numerical results show that the proposed receivers can approach the optimum multiuser receivers with significantly (even exponentially in some cases) reduced complexity and marginal performance degradation.
Derivation of LDA log likelihood ratio one-to-one classifier
Spreeuwers, Lieuwe Jan
2014-01-01
The common expression for the Likelihood Ratio classifier using LDA assumes that the reference class mean is available. In biometrics, this is often not the case and only a single sample of the reference class is available. In this paper expressions are derived for biometric comparison between
Comparison of IRT Likelihood Ratio Test and Logistic Regression DIF Detection Procedures
Atar, Burcu; Kamata, Akihito
2011-01-01
The Type I error rates and the power of IRT likelihood ratio test and cumulative logit ordinal logistic regression procedures in detecting differential item functioning (DIF) for polytomously scored items were investigated in this Monte Carlo simulation study. For this purpose, 54 simulation conditions (combinations of 3 sample sizes, 2 sample…
Marsh, Benjamin U; Pezdek, Kathy; Lam, Shirley T
2014-07-01
Two experiments tested and confirmed the hypothesis that when the phenomenological characteristics of imagined events are more similar to those of related autobiographical memories, the imagined event is more likely to be considered to have occurred. At Time 1 and 2-weeks later, individuals rated the likelihood of occurrence for 20 life events. In Experiment 1, 1-week after Time 1, individuals imagined 3 childhood events from a first-person or third-person perspective. There was a no-imagination control. An increase in likelihood ratings from Time 1 to Time 2 resulted when imagination was from the third-person but not first-person perspective. In Experiment 2, childhood and recent events were imagined from a third- or first-person perspective. A significant interaction resulted. For childhood events, likelihood change scores were greater for third-person than first-person perspective; for recent adult events, likelihood change scores were greater for first-person than third-person perspective, although this latter trend was not significant. Copyright © 2014 Elsevier B.V. All rights reserved.
McGuire, Connor; Kristman, Vicki L; Shaw, William; Williams-Whitt, Kelly; Reguly, Paula; Soklaridis, Sophie
2015-09-01
To determine the association between supervisors' leadership style and autonomy and supervisors' likelihood of supporting job accommodations for back-injured workers. A cross-sectional study of supervisors from Canadian and US employers was conducted using a web-based, self-report questionnaire that included a case vignette of a back-injured worker. Autonomy and two dimensions of leadership style (considerate and initiating structure) were included as exposures. The outcome, supervisors' likeliness to support job accommodation, was measured with the Job Accommodation Scale (JAS). We conducted univariate analyses of all variables and bivariate analyses of the JAS score with each exposure and potential confounding factor. We used multivariable generalized linear models to control for confounding factors. A total of 796 supervisors participated. Considerate leadership style (β = .012; 95% CI .009-.016) and autonomy (β = .066; 95% CI .025-.11) were positively associated with supervisors' likelihood to accommodate after adjusting for appropriate confounding factors. An initiating structure leadership style was not significantly associated with supervisors' likelihood to accommodate (β = .0018; 95% CI -.0026 to .0061) after adjusting for appropriate confounders. Autonomy and a considerate leadership style were positively associated with supervisors' likelihood to accommodate a back-injured worker. Providing supervisors with more autonomy over decisions of accommodation and developing their considerate leadership style may aid in increasing work accommodation for back-injured workers and preventing prolonged work disability.
McGuire, Connor; Kristman, Vicki L; Williams-Whitt, Kelly; Reguly, Paula; Shaw, William; Soklaridis, Sophie
2015-01-01
PURPOSE To determine the association between supervisors’ leadership style and autonomy and supervisors’ likelihood of supporting job accommodations for back-injured workers. METHODS A cross-sectional study of supervisors from Canadian and US employers was conducted using a web-based, self-report questionnaire that included a case vignette of a back-injured worker. Autonomy and two dimensions of leadership style (considerate and initiating structure) were included as exposures. The outcome, supervisors’ likeliness to support job accommodation, was measured with the Job Accommodation Scale. We conducted univariate analyses of all variables and bivariate analyses of the JAS score with each exposure and potential confounding factor. We used multivariable generalized linear models to control for confounding factors. RESULTS A total of 796 supervisors participated. Considerate leadership style (β= .012; 95% CI: .009–.016) and autonomy (β= .066; 95% CI: .025–.11) were positively associated with supervisors’ likelihood to accommodate after adjusting for appropriate confounding factors. An initiating structure leadership style was not significantly associated with supervisors’ likelihood to accommodate (β = .0018; 95% CI: −.0026–.0061) after adjusting for appropriate confounders. CONCLUSIONS Autonomy and a considerate leadership style were positively associated with supervisors’ likelihood to accommodate a back-injured worker. Providing supervisors with more autonomy over decisions of accommodation and developing their considerate leadership style may aid in increasing work accommodation for back-injured workers and preventing prolonged work disability. PMID:25595332
Maximum likelihood estimation of ancestral codon usage bias parameters in Drosophila
DEFF Research Database (Denmark)
Nielsen, Rasmus; Bauer DuMont, Vanessa L; Hubisz, Melissa J
2007-01-01
: the selection coefficient for optimal codon usage (S), allowing joint maximum likelihood estimation of S and the dN/dS ratio. We apply the method to previously published data from Drosophila melanogaster, Drosophila simulans, and Drosophila yakuba and show, in accordance with previous results, that the D...
Robust Biometric Score Fusion by Naive Likelihood Ratio via Receiver Operating Characteristics
Tao, Q.; Veldhuis, Raymond N.J.
This paper presents a novel method of fusing multiple biometrics on the matching score level. We estimate the likelihood ratios of the fused biometric scores, via individual receiver operating characteristics (ROC) which construct the Naive Bayes classifier. Using a limited number of operation
Arshad, Saadia; Winterhalder, Robert; Underwood, Lisa; Kelesidi, Katerina; Chaplin, Eddie; Kravariti, Eugenia; Anagnostopoulos, Dimitrios; Bouras, Nick; McCarthy, Jane; Tsakanikos, Elias
2011-01-01
Although epilepsy is particularly common among people with intellectual disability (ID) it remains unclear whether it is associated with an increased likelihood of co-morbid psychopathology. We therefore investigated rates of mental health problems and other clinical characteristics in patients with ID and epilepsy (N=156) as compared to patients…
Heterogeneity in the Likelihood of Market Advisory Service Use by U.S. Crop Producers
Pennings, J.M.E.; Irwin, S.; Good, D.; Isengildina, O.
2005-01-01
Abstract Analysis of a unique data set of 1,400 U.S. crop producers using a mixture-modeling framework shows that the likelihood of Marketing Advisory Services (MAS) use is, among others, driven by the perceived performance of MAS in terms of return and risk reduction, the match between the MAS and
The Influence of criminal history on the likelihood of committing lethal versus nonlethal violence
Ganpat, Soenita M.; Liem, Marieke; van der Leun, Joanne; Nieuwbeerta, Paul
2014-01-01
This study focuses on the criminal history of serious violent offenders. Our aim is to determine: (a) to what extent the criminal history of lethally violent offenders differs from nonlethally violent offenders and (b) to what extent one's criminal history influences the likelihood that violence
Application of the Method of Maximum Likelihood to Identification of Bipedal Walking Robots
Czech Academy of Sciences Publication Activity Database
Dolinský, Kamil; Čelikovský, Sergej
(2017) ISSN 1063-6536 R&D Projects: GA ČR(CZ) GA17-04682S Institutional support: RVO:67985556 Keywords : Control * identification * maximum likelihood (ML) * walking robots Subject RIV: BC - Control Systems Theory Impact factor: 3.882, year: 2016 http://ieeexplore.ieee.org/document/7954032/
Aquilino, William S.
1990-01-01
Estimated influence of child, parent, and family structural characteristics on likelihood of parents having coresident adult child, based on national sample of 4,893 parents. Results indicated most parents maintained own households and most parents and adult children who coresided lived in parents' home. Family structure was found to exert strong…
Magis, David; Raiche, Gilles
2010-01-01
In this article the authors focus on the issue of the nonuniqueness of the maximum likelihood (ML) estimator of proficiency level in item response theory (with special attention to logistic models). The usual maximum a posteriori (MAP) method offers a good alternative within that framework; however, this article highlights some drawbacks of its…
Litvinenko, Alexander
2017-01-01
and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters
Validation of software for calculating the likelihood ratio for parentage and kinship.
Drábek, J
2009-03-01
Although the likelihood ratio is a well-known statistical technique, commercial off-the-shelf (COTS) software products for its calculation are not sufficiently validated to suit general requirements for the competence of testing and calibration laboratories (EN/ISO/IEC 17025:2005 norm) per se. The software in question can be considered critical as it directly weighs the forensic evidence allowing judges to decide on guilt or innocence or to identify person or kin (i.e.: in mass fatalities). For these reasons, accredited laboratories shall validate likelihood ratio software in accordance with the above norm. To validate software for calculating the likelihood ratio in parentage/kinship scenarios I assessed available vendors, chose two programs (Paternity Index and familias) for testing, and finally validated them using tests derived from elaboration of the available guidelines for the field of forensics, biomedicine, and software engineering. MS Excel calculation using known likelihood ratio formulas or peer-reviewed results of difficult paternity cases were used as a reference. Using seven testing cases, it was found that both programs satisfied the requirements for basic paternity cases. However, only a combination of two software programs fulfills the criteria needed for our purpose in the whole spectrum of functions under validation with the exceptions of providing algebraic formulas in cases of mutation and/or silent allele.
John Hogland; Nedret Billor; Nathaniel Anderson
2013-01-01
Discriminant analysis, referred to as maximum likelihood classification within popular remote sensing software packages, is a common supervised technique used by analysts. Polytomous logistic regression (PLR), also referred to as multinomial logistic regression, is an alternative classification approach that is less restrictive, more flexible, and easy to interpret. To...
Predicting the Likelihood of Going to Graduate School: The Importance of Locus of Control
Nordstrom, Cynthia R.; Segrist, Dan J.
2009-01-01
Although many undergraduates apply to graduate school, only a fraction will be admitted. A question arises as to what factors relate to the likelihood of pursuing graduate studies. The current research examined this question by surveying students in a Careers in Psychology course. We hypothesized that GPA, a more internal locus of control…
DEFF Research Database (Denmark)
Borkowski, Robert; Johannisson, Pontus; Wymeersch, Henk
2014-01-01
We perform an experimental investigation of a maximum likelihood-based (ML-based) algorithm for bulk chromatic dispersion estimation for digital coherent receivers operating in uncompensated optical networks. We demonstrate the robustness of the method at low optical signal-to-noise ratio (OSNR...
Shenkman, Geva
2012-10-01
This study examined the frequencies of the desires and likelihood estimations of Israeli gay men regarding fatherhood and couplehood, using a sample of 183 gay men aged 19-50. It follows previous research which indicated the existence of a gap in the United States with respect to fatherhood, and called for generalizability examinations in other countries and the exploration of possible explanations. As predicted, a gap was also found in Israel between fatherhood desires and their likelihood estimations, as well as between couplehood desires and their likelihood estimations. In addition, lower estimations of fatherhood likelihood were found to predict depression and to correlate with decreased subjective well-being. Possible psychosocial explanations are offered. Moreover, by mapping attitudes toward fatherhood and couplehood among Israeli gay men, the current study helps to extend our knowledge of several central human development motivations and their correlations with depression and subjective well-being in a less-studied sexual minority in a complex cultural climate. (PsycINFO Database Record (c) 2012 APA, all rights reserved).
Casabianca, Jodi M.; Lewis, Charles
2015-01-01
Loglinear smoothing (LLS) estimates the latent trait distribution while making fewer assumptions about its form and maintaining parsimony, thus leading to more precise item response theory (IRT) item parameter estimates than standard marginal maximum likelihood (MML). This article provides the expectation-maximization algorithm for MML estimation…
Haraksim, Rudolf
2014-01-01
In this chapter the Likelihood Ratio (LR) inference model will be introduced, the theoretical aspects of probabilities will be discussed and the validation framework for LR methods used for forensic evidence evaluation will be presented. Prior to introducing the validation framework, following
Kamans, Elanor; Otten, Sabine; Gordijn, Ernestine H.; Spears, Russell
2010-01-01
The aim of the current study was to show that the type of conflict behavior (constructive vs. unconstructive) groups use in conflicts depends on their power position as well as the likelihood that power determines victory and defeat. In an alleged online debate, we created a conflict between two
The skewed weak lensing likelihood: why biases arise, despite data and theory being sound.
Sellentin, Elena; Heymans, Catherine; Harnois-Déraps, Joachim
2018-04-01
We derive the essentials of the skewed weak lensing likelihood via a simple Hierarchical Forward Model. Our likelihood passes four objective and cosmology-independent tests which a standard Gaussian likelihood fails. We demonstrate that sound weak lensing data are naturally biased low, since they are drawn from a skewed distribution. This occurs already in the framework of ΛCDM. Mathematically, the biases arise because noisy two-point functions follow skewed distributions. This form of bias is already known from CMB analyses, where the low multipoles have asymmetric error bars. Weak lensing is more strongly affected by this asymmetry as galaxies form a discrete set of shear tracer particles, in contrast to a smooth shear field. We demonstrate that the biases can be up to 30% of the standard deviation per data point, dependent on the properties of the weak lensing survey and the employed filter function. Our likelihood provides a versatile framework with which to address this bias in future weak lensing analyses.
Validation of DNA-based identification software by computation of pedigree likelihood ratios.
Slooten, K
2011-08-01
Disaster victim identification (DVI) can be aided by DNA-evidence, by comparing the DNA-profiles of unidentified individuals with those of surviving relatives. The DNA-evidence is used optimally when such a comparison is done by calculating the appropriate likelihood ratios. Though conceptually simple, the calculations can be quite involved, especially with large pedigrees, precise mutation models etc. In this article we describe a series of test cases designed to check if software designed to calculate such likelihood ratios computes them correctly. The cases include both simple and more complicated pedigrees, among which inbred ones. We show how to calculate the likelihood ratio numerically and algebraically, including a general mutation model and possibility of allelic dropout. In Appendix A we show how to derive such algebraic expressions mathematically. We have set up these cases to validate new software, called Bonaparte, which performs pedigree likelihood ratio calculations in a DVI context. Bonaparte has been developed by SNN Nijmegen (The Netherlands) for the Netherlands Forensic Institute (NFI). It is available free of charge for non-commercial purposes (see www.dnadvi.nl for details). Commercial licenses can also be obtained. The software uses Bayesian networks and the junction tree algorithm to perform its calculations. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Validation of DNA-based identification software by computation of pedigree likelihood ratios
Slooten, K.
Disaster victim identification (DVI) can be aided by DNA-evidence, by comparing the DNA-profiles of unidentified individuals with those of surviving relatives. The DNA-evidence is used optimally when such a comparison is done by calculating the appropriate likelihood ratios. Though conceptually
A simple route to maximum-likelihood estimates of two-locus
Indian Academy of Sciences (India)
Home; Journals; Journal of Genetics; Volume 94; Issue 3. A simple route to maximum-likelihood estimates of two-locus recombination fractions under inequality restrictions. Iain L. Macdonald Philasande Nkalashe. Research Note Volume 94 Issue 3 September 2015 pp 479-481 ...
Monte Carlo Maximum Likelihood Estimation for Generalized Long-Memory Time Series Models
Mesters, G.; Koopman, S.J.; Ooms, M.
2016-01-01
An exact maximum likelihood method is developed for the estimation of parameters in a non-Gaussian nonlinear density function that depends on a latent Gaussian dynamic process with long-memory properties. Our method relies on the method of importance sampling and on a linear Gaussian approximating
A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses
Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini
2012-01-01
The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…
Estimation of stochastic frontier models with fixed-effects through Monte Carlo Maximum Likelihood
Emvalomatis, G.; Stefanou, S.E.; Oude Lansink, A.G.J.M.
2011-01-01
Estimation of nonlinear fixed-effects models is plagued by the incidental parameters problem. This paper proposes a procedure for choosing appropriate densities for integrating the incidental parameters from the likelihood function in a general context. The densities are based on priors that are
Maximum likelihood estimation for Cox's regression model under nested case-control sampling
DEFF Research Database (Denmark)
Scheike, Thomas; Juul, Anders
2004-01-01
Nested case-control sampling is designed to reduce the costs of large cohort studies. It is important to estimate the parameters of interest as efficiently as possible. We present a new maximum likelihood estimator (MLE) for nested case-control sampling in the context of Cox's proportional hazard...
Penfield, Randall D.; Bergeron, Jennifer M.
2005-01-01
This article applies a weighted maximum likelihood (WML) latent trait estimator to the generalized partial credit model (GPCM). The relevant equations required to obtain the WML estimator using the Newton-Raphson algorithm are presented, and a simulation study is described that compared the properties of the WML estimator to those of the maximum…
Maximum Likelihood Dynamic Factor Modeling for Arbitrary "N" and "T" Using SEM
Voelkle, Manuel C.; Oud, Johan H. L.; von Oertzen, Timo; Lindenberger, Ulman
2012-01-01
This article has 3 objectives that build on each other. First, we demonstrate how to obtain maximum likelihood estimates for dynamic factor models (the direct autoregressive factor score model) with arbitrary "T" and "N" by means of structural equation modeling (SEM) and compare the approach to existing methods. Second, we go beyond standard time…
Akdemir, Ömür; Vural, Ömer F.; Çolakoglu, Özgür M.
2015-01-01
Individuals act different in virtual environment than real life. The primary purpose of this study is to investigate the prospective teachers' likelihood of performing unethical behaviors in the real and virtual environments. Prospective teachers are surveyed online and their perceptions have been collected for various scenarios. Findings revealed…
Evaluation of Smoking Prevention Television Messages Based on the Elaboration Likelihood Model
Flynn, Brian S.; Worden, John K.; Bunn, Janice Yanushka; Connolly, Scott W.; Dorwaldt, Anne L.
2011-01-01
Progress in reducing youth smoking may depend on developing improved methods to communicate with higher risk youth. This study explored the potential of smoking prevention messages based on the Elaboration Likelihood Model (ELM) to address these needs. Structured evaluations of 12 smoking prevention messages based on three strategies derived from…
SIERO, FW; DOOSJE, BJ
1993-01-01
An experiment was conducted to examine the influence of the perceived extremity of a message and motivation to elaborate upon the process of persuasion. The first goal was to test a model of attitude change relating Social Judgment Theory to the Elaboration Likelihood Model. The second objective was
Petty, Richard E.; And Others
1987-01-01
Answers James Stiff's criticism of the Elaboration Likelihood Model (ELM) of persuasion. Corrects certain misperceptions of the ELM and criticizes Stiff's meta-analysis that compares ELM predictions with those derived from Kahneman's elastic capacity model. Argues that Stiff's presentation of the ELM and the conclusions he draws based on the data…
The Elaboration Likelihood Model: Implications for the Practice of School Psychology.
Petty, Richard E.; Heesacker, Martin; Hughes, Jan N.
1997-01-01
Reviews a contemporary theory of attitude change, the Elaboration Likelihood Model (ELM) of persuasion, and addresses its relevance to school psychology. Claims that a key postulate of ELM is that attitude change results from thoughtful (central route) or nonthoughtful (peripheral route) processes. Illustrations of ELM's utility for school…
Heppner, Mary J.; And Others
1995-01-01
Intervention sought to improve first-year college students' attitudes about rape. Used the Elaboration Likelihood Model to examine men's and women's attitude change process. Found numerous sex differences in ways men and women experienced and changed during and after intervention. Women's attitude showed more lasting change while men's was more…
Application of the Elaboration Likelihood Model of Attitude Change to Assertion Training.
Ernst, John M.; Heesacker, Martin
1993-01-01
College students (n=113) participated in study comparing effects of elaboration likelihood model (ELM) based assertion workshop with those of typical assertion workshop. ELM-based workshop was significantly better at producing favorable attitude change, greater intention to act assertively, and more favorable evaluations of workshop content.…
Eaves, Michael
This paper provides a literature review of the elaboration likelihood model (ELM) as applied in persuasion. Specifically, the paper addresses distraction with regard to effects on persuasion. In addition, the application of proxemic violations as peripheral cues in message processing is discussed. Finally, the paper proposes to shed new light on…
Fast maximum likelihood estimation of mutation rates using a birth-death process.
Wu, Xiaowei; Zhu, Hongxiao
2015-02-07
Since fluctuation analysis was first introduced by Luria and Delbrück in 1943, it has been widely used to make inference about spontaneous mutation rates in cultured cells. Under certain model assumptions, the probability distribution of the number of mutants that appear in a fluctuation experiment can be derived explicitly, which provides the basis of mutation rate estimation. It has been shown that, among various existing estimators, the maximum likelihood estimator usually demonstrates some desirable properties such as consistency and lower mean squared error. However, its application in real experimental data is often hindered by slow computation of likelihood due to the recursive form of the mutant-count distribution. We propose a fast maximum likelihood estimator of mutation rates, MLE-BD, based on a birth-death process model with non-differential growth assumption. Simulation studies demonstrate that, compared with the conventional maximum likelihood estimator derived from the Luria-Delbrück distribution, MLE-BD achieves substantial improvement on computational speed and is applicable to arbitrarily large number of mutants. In addition, it still retains good accuracy on point estimation. Published by Elsevier Ltd.
Assessing compatibility of direct detection data: halo-independent global likelihood analyses
Energy Technology Data Exchange (ETDEWEB)
Gelmini, Graciela B. [Department of Physics and Astronomy, UCLA,475 Portola Plaza, Los Angeles, CA 90095 (United States); Huh, Ji-Haeng [CERN Theory Division,CH-1211, Geneva 23 (Switzerland); Witte, Samuel J. [Department of Physics and Astronomy, UCLA,475 Portola Plaza, Los Angeles, CA 90095 (United States)
2016-10-18
We present two different halo-independent methods to assess the compatibility of several direct dark matter detection data sets for a given dark matter model using a global likelihood consisting of at least one extended likelihood and an arbitrary number of Gaussian or Poisson likelihoods. In the first method we find the global best fit halo function (we prove that it is a unique piecewise constant function with a number of down steps smaller than or equal to a maximum number that we compute) and construct a two-sided pointwise confidence band at any desired confidence level, which can then be compared with those derived from the extended likelihood alone to assess the joint compatibility of the data. In the second method we define a “constrained parameter goodness-of-fit” test statistic, whose p-value we then use to define a “plausibility region” (e.g. where p≥10%). For any halo function not entirely contained within the plausibility region, the level of compatibility of the data is very low (e.g. p<10%). We illustrate these methods by applying them to CDMS-II-Si and SuperCDMS data, assuming dark matter particles with elastic spin-independent isospin-conserving interactions or exothermic spin-independent isospin-violating interactions.
Magis, David; Raiche, Gilles
2012-01-01
This paper focuses on two estimators of ability with logistic item response theory models: the Bayesian modal (BM) estimator and the weighted likelihood (WL) estimator. For the BM estimator, Jeffreys' prior distribution is considered, and the corresponding estimator is referred to as the Jeffreys modal (JM) estimator. It is established that under…
Audio-visual Classification and Fusion of Spontaneous Affect Data in Likelihood Space
Nicolaou, Mihalis A.; Gunes, Hatice; Pantic, Maja
2010-01-01
This paper focuses on audio-visual (using facial expression, shoulder and audio cues) classification of spontaneous affect, utilising generative models for classification (i) in terms of Maximum Likelihood Classification with the assumption that the generative model structure in the classifier is
Likelihood of Suicidality at Varying Levels of Depression Severity: A Re-Analysis of NESARC Data
Uebelacker, Lisa A.; Strong, David; Weinstock, Lauren M.; Miller, Ivan W.
2010-01-01
Although it is clear that increasing depression severity is associated with more risk for suicidality, less is known about at what levels of depression severity the risk for different suicide symptoms increases. We used item response theory to estimate the likelihood of endorsing suicide symptoms across levels of depression severity in an…
Inflation after False Vacuum Decay observational Prospects after Planck
Bousso, Raphael; Senatore, Leonardo
2015-01-01
We assess potential signals of the formation of our universe by the decay of a false vacuum. Negative spatial curvature is one possibility, but the window for its detection is now small. However, another possible signal is a suppression of the CMB power spectrum at large angles. This arises from the steepening of the effective potential as it interpolates between a flat inflationary plateau and the high barrier separating us from our parent vacuum. We demonstrate that these two effects can be parametrically separated in angular scale. Observationally, the steepening effect appears to be excluded at large l; but it remains consistent with the slight lack of power below l about 30 found by the WMAP and Planck collaborations. We give two simple models which improve the fit to the Planck data; one with observable curvature and one without. Despite cosmic variance, we argue that future CMB polarization and most importantly large-scale structure observations should be able to corroborate the Planck anomaly if it is...
Greenery in the university environment: Students’ preferences and perceived restoration likelihood
2018-01-01
A large body of evidence shows that interaction with greenery can be beneficial for human stress reduction, emotional states, and improved cognitive function. It can, therefore, be expected that university students might benefit from greenery in the university environment. Before investing in real-life interventions in a university environment, it is necessary to first explore students’ perceptions of greenery in the university environment. This study examined (1) preference for university indoor and outdoor spaces with and without greenery (2) perceived restoration likelihood of university outdoor spaces with and without greenery and (3) if preference and perceived restoration likelihood ratings were modified by demographic characteristics or connectedness to nature in Dutch university students (N = 722). Digital photographic stimuli represented four university spaces (lecture hall, classroom, study area, university outdoor space). For each of the three indoor spaces there were four or five stimuli conditions: (1) the standard design (2) the standard design with a colorful poster (3) the standard design with a nature poster (4) the standard design with a green wall (5) the standard design with a green wall plus interior plants. The university outdoor space included: (1) the standard design (2) the standard design with seating (3) the standard design with colorful artifacts (4) the standard design with green elements (5) the standard design with extensive greenery. Multi-level analyses showed that students gave higher preference ratings to the indoor spaces with a nature poster, a green wall, or a green wall plus interior plants than to the standard designs and the designs with the colorful posters. Students also rated preference and perceived restoration likelihood of the outdoor spaces that included greenery higher than those without. Preference and perceived restoration likelihood were not modified by demographic characteristics, but students with strong
Greenery in the university environment: Students' preferences and perceived restoration likelihood.
Directory of Open Access Journals (Sweden)
Nicole van den Bogerd
Full Text Available A large body of evidence shows that interaction with greenery can be beneficial for human stress reduction, emotional states, and improved cognitive function. It can, therefore, be expected that university students might benefit from greenery in the university environment. Before investing in real-life interventions in a university environment, it is necessary to first explore students' perceptions of greenery in the university environment. This study examined (1 preference for university indoor and outdoor spaces with and without greenery (2 perceived restoration likelihood of university outdoor spaces with and without greenery and (3 if preference and perceived restoration likelihood ratings were modified by demographic characteristics or connectedness to nature in Dutch university students (N = 722. Digital photographic stimuli represented four university spaces (lecture hall, classroom, study area, university outdoor space. For each of the three indoor spaces there were four or five stimuli conditions: (1 the standard design (2 the standard design with a colorful poster (3 the standard design with a nature poster (4 the standard design with a green wall (5 the standard design with a green wall plus interior plants. The university outdoor space included: (1 the standard design (2 the standard design with seating (3 the standard design with colorful artifacts (4 the standard design with green elements (5 the standard design with extensive greenery. Multi-level analyses showed that students gave higher preference ratings to the indoor spaces with a nature poster, a green wall, or a green wall plus interior plants than to the standard designs and the designs with the colorful posters. Students also rated preference and perceived restoration likelihood of the outdoor spaces that included greenery higher than those without. Preference and perceived restoration likelihood were not modified by demographic characteristics, but students with strong
Greenery in the university environment: Students' preferences and perceived restoration likelihood.
van den Bogerd, Nicole; Dijkstra, S Coosje; Seidell, Jacob C; Maas, Jolanda
2018-01-01
A large body of evidence shows that interaction with greenery can be beneficial for human stress reduction, emotional states, and improved cognitive function. It can, therefore, be expected that university students might benefit from greenery in the university environment. Before investing in real-life interventions in a university environment, it is necessary to first explore students' perceptions of greenery in the university environment. This study examined (1) preference for university indoor and outdoor spaces with and without greenery (2) perceived restoration likelihood of university outdoor spaces with and without greenery and (3) if preference and perceived restoration likelihood ratings were modified by demographic characteristics or connectedness to nature in Dutch university students (N = 722). Digital photographic stimuli represented four university spaces (lecture hall, classroom, study area, university outdoor space). For each of the three indoor spaces there were four or five stimuli conditions: (1) the standard design (2) the standard design with a colorful poster (3) the standard design with a nature poster (4) the standard design with a green wall (5) the standard design with a green wall plus interior plants. The university outdoor space included: (1) the standard design (2) the standard design with seating (3) the standard design with colorful artifacts (4) the standard design with green elements (5) the standard design with extensive greenery. Multi-level analyses showed that students gave higher preference ratings to the indoor spaces with a nature poster, a green wall, or a green wall plus interior plants than to the standard designs and the designs with the colorful posters. Students also rated preference and perceived restoration likelihood of the outdoor spaces that included greenery higher than those without. Preference and perceived restoration likelihood were not modified by demographic characteristics, but students with strong
Delaney, W; Grube, J W; Ames, G M
1998-03-01
This research investigated belief, social support and background predictors of employee likelihood to use an Employee Assistance Program (EAP) for a drinking problem. An anonymous cross-sectional survey was administered in the home. Bivariate analyses and simultaneous equations path analysis were used to explore a model of EAP use. Survey and ethnographic research were conducted in a unionized heavy machinery manufacturing plant in the central states of the United States. A random sample of 852 hourly and salaried employees was selected. In addition to background variables, measures included: likelihood of going to an EAP for a drinking problem, belief the EAP can help, social support for the EAP from co-workers/others, belief that EAP use will harm employment, and supervisor encourages the EAP for potential drinking problems. Belief in EAP efficacy directly increased the likelihood of going to an EAP. Greater perceived social support and supervisor encouragement increased the likelihood of going to an EAP both directly and indirectly through perceived EAP efficacy. Black and union hourly employees were more likely to say they would use an EAP. Males and those who reported drinking during working hours were less likely to say they would use an EAP for a drinking problem. EAP beliefs and social support have significant effects on likelihood to go to an EAP for a drinking problem. EAPs may wish to focus their efforts on creating an environment where there is social support from coworkers and encouragement from supervisors for using EAP services. Union networks and team members have an important role to play in addition to conventional supervisor intervention.
Powdered alcohol: Awareness and likelihood of use among a sample of college students.
Vail-Smith, Karen; Chaney, Beth H; Martin, Ryan J; Don Chaney, J
2016-01-01
In March 2015, the Alcohol and Tobacco Tax and Trade Bureau approved the sale of Palcohol, the first powdered alcohol product to be marketed and sold in the U.S. Powdered alcohol is freeze-dried, and one individual-serving size packet added to 6 ounces of liquid is equivalent to a standard drink. This study assessed awareness of powered alcohol and likelihood to use and/or misuse powdered alcohol among college students. Surveys were administered to a convenience sample of 1,841 undergraduate students. Only 16.4% of respondents had heard of powdered alcohol. After being provided a brief description of powdered alcohol, 23% indicated that they would use the product if available, and of those, 62.1% also indicated likelihood of misusing the product (eg, snorting it, mixing it with alcohol). Caucasian students (OR = 1.5) and hazardous drinkers (based on AUDIT-C scores; OR = 4.7) were significantly more likely to indicate likelihood of use. Hazardous drinkers were also six times more likely to indicate likelihood to misuse the product. These findings can inform upstream prevention efforts in states debating bans on powdered alcohol. In states where powdered alcohol will soon be available, alcohol education initiatives should be updated to include information on the potential risks of use and be targeted to those populations most likely to misuse. This is the first peer-reviewed study to assess the awareness of and likelihood to use and/or misuse powdered alcohol, a potentially emerging form of alcohol. © American Academy of Addiction Psychiatry.
International Nuclear Information System (INIS)
Song, N; Frey, E C; He, B; Wahl, R L
2011-01-01
Optimizing targeted radionuclide therapy requires patient-specific estimation of organ doses. The organ doses are estimated from quantitative nuclear medicine imaging studies, many of which involve planar whole body scans. We have previously developed the quantitative planar (QPlanar) processing method and demonstrated its ability to provide more accurate activity estimates than conventional geometric-mean-based planar (CPlanar) processing methods using physical phantom and simulation studies. The QPlanar method uses the maximum likelihood-expectation maximization algorithm, 3D organ volume of interests (VOIs), and rigorous models of physical image degrading factors to estimate organ activities. However, the QPlanar method requires alignment between the 3D organ VOIs and the 2D planar projections and assumes uniform activity distribution in each VOI. This makes application to patients challenging. As a result, in this paper we propose an extended QPlanar (EQPlanar) method that provides independent-organ rigid registration and includes multiple background regions. We have validated this method using both Monte Carlo simulation and patient data. In the simulation study, we evaluated the precision and accuracy of the method in comparison to the original QPlanar method. For the patient studies, we compared organ activity estimates at 24 h after injection with those from conventional geometric mean-based planar quantification using a 24 h post-injection quantitative SPECT reconstruction as the gold standard. We also compared the goodness of fit of the measured and estimated projections obtained from the EQPlanar method to those from the original method at four other time points where gold standard data were not available. In the simulation study, more accurate activity estimates were provided by the EQPlanar method for all the organs at all the time points compared with the QPlanar method. Based on the patient data, we concluded that the EQPlanar method provided a
Marill, Keith A; Chang, Yuchiao; Wong, Kim F; Friedman, Ari B
2017-08-01
Objectives Assessing high-sensitivity tests for mortal illness is crucial in emergency and critical care medicine. Estimating the 95% confidence interval (CI) of the likelihood ratio (LR) can be challenging when sample sensitivity is 100%. We aimed to develop, compare, and automate a bootstrapping method to estimate the negative LR CI when sample sensitivity is 100%. Methods The lowest population sensitivity that is most likely to yield sample sensitivity 100% is located using the binomial distribution. Random binomial samples generated using this population sensitivity are then used in the LR bootstrap. A free R program, "bootLR," automates the process. Extensive simulations were performed to determine how often the LR bootstrap and comparator method 95% CIs cover the true population negative LR value. Finally, the 95% CI was compared for theoretical sample sizes and sensitivities approaching and including 100% using: (1) a technique of individual extremes, (2) SAS software based on the technique of Gart and Nam, (3) the Score CI (as implemented in the StatXact, SAS, and R PropCI package), and (4) the bootstrapping technique. Results The bootstrapping approach demonstrates appropriate coverage of the nominal 95% CI over a spectrum of populations and sample sizes. Considering a study of sample size 200 with 100 patients with disease, and specificity 60%, the lowest population sensitivity with median sample sensitivity 100% is 99.31%. When all 100 patients with disease test positive, the negative LR 95% CIs are: individual extremes technique (0,0.073), StatXact (0,0.064), SAS Score method (0,0.057), R PropCI (0,0.062), and bootstrap (0,0.048). Similar trends were observed for other sample sizes. Conclusions When study samples demonstrate 100% sensitivity, available methods may yield inappropriately wide negative LR CIs. An alternative bootstrapping approach and accompanying free open-source R package were developed to yield realistic estimates easily. This
Observational constraints on dark energy and cosmic curvature
International Nuclear Information System (INIS)
Wang Yun; Mukherjee, Pia
2007-01-01
Current observational bounds on dark energy depend on our assumptions about the curvature of the universe. We present a simple and efficient method for incorporating constraints from cosmic microwave background (CMB) anisotropy data and use it to derive constraints on cosmic curvature and dark energy density as a free function of cosmic time using current CMB, Type Ia supernova (SN Ia), and baryon acoustic oscillation data. We show that there are two CMB shift parameters, R≡√(Ω m H 0 2 )r(z CMB ) (the scaled distance to recombination) and l a ≡πr(z CMB )/r s (z CMB ) (the angular scale of the sound horizon at recombination), with measured values that are nearly uncorrelated with each other. Allowing nonzero cosmic curvature, the three-year WMAP (Wilkinson Microwave Anisotropy Probe) data give R=1.71±0.03, l a =302.5±1.2, and Ω b h 2 =0.02173±0.00082, independent of the dark energy model. The corresponding bounds for a flat universe are R=1.70±0.03, l a =302.2±1.2, and Ω b h 2 =0.022±0.00082. We give the covariance matrix of (R,l a ,Ω b h 2 ) from the three-year WMAP data. We find that (R,l a ,Ω b h 2 ) provide an efficient and intuitive summary of CMB data as far as dark energy constraints are concerned. Assuming the Hubble Space Telescope (HST) prior of H 0 =72±8 (km/s) Mpc -1 , using 182 SNe Ia (from the HST/GOODS program, the first year Supernova Legacy Survey, and nearby SN Ia surveys), (R,l a ,Ω b h 2 ) from WMAP three-year data, and SDSS (Sloan Digital Sky Survey) measurement of the baryon acoustic oscillation scale, we find that dark energy density is consistent with a constant in cosmic time, with marginal deviations from a cosmological constant that may reflect current systematic uncertainties or true evolution in dark energy. A flat universe is allowed by current data: Ω k =-0.006 -0.012-0.025 +0.013+0.025 for assuming that the dark energy equation of state w X (z) is constant, and Ω k =-0.002 -0.018-0.032 +0.018+0.041 for w X (z
On what scale should inflationary observables be constrained?
International Nuclear Information System (INIS)
Cortes, Marina; Liddle, Andrew R.; Mukherjee, Pia
2007-01-01
We examine the choice of scale at which constraints on inflationary observables are presented. We describe an implementation of the hierarchy of inflationary consistency equations which ensures that they remain enforced on different scales, and then seek to optimize the scale for presentation of constraints on marginalized inflationary parameters from WMAP3 data. For models with spectral index running, we find a strong variation of the constraints through the range of observational scales available, and optimize by finding the scale which decorrelates constraints on the spectral index n S and the running. This scale is k=0.017 Mpc -1 , and gives a reduction by a factor of more than four in the allowed parameter area in the n S -r plane (r being the tensor-to-scalar ratio) relative to k=0.002 Mpc -1 . These optimized constraints are similar to those obtained in the no-running case. We also extend the analysis to a larger compilation of data, finding essentially the same conclusions
The Cosmic Abundance of 3He: Green Bank Telescope Observations
Balser, Dana; Bania, Thomas
2018-01-01
The Big Bang theory for the origin of the Universe predicts that during the first ~1,000 seconds significant amounts of the light elements (2H, 3He, 4He, and 7Li) were produced. Many generations of stellar evolution in the Galaxy modifies these primordial abundances. Observations of the 3He+ hyperfine transition in Galactic HII regions reveals a 3He/H abundance ratio that is constant with Galactocentric radius to within the uncertainties, and is consistent with the primordial value as determined from cosmic microwave background experiments (e.g., WMAP). This "3He Plateau" indicates that the net production and destruction of 3He in stars is approximately zero. Recent stellar evolution models that include thermohaline mixing, however, predict that 3He/H abundance ratios should slightly decrease with Galactocentric radius, or in places in the Galaxy with lower star formation rates. Here we discuss sensitive Green Bank Telescope (GBT) observations of 3He+ at 3.46 cm in a subset of our HII region sample. We develop HII region models and derive accurate 3He/H abundance ratios to better constrain these new stellar evolution models.
Multimodal Personal Verification Using Likelihood Ratio for the Match Score Fusion
Directory of Open Access Journals (Sweden)
Long Binh Tran
2017-01-01
Full Text Available In this paper, the authors present a novel personal verification system based on the likelihood ratio test for fusion of match scores from multiple biometric matchers (face, fingerprint, hand shape, and palm print. In the proposed system, multimodal features are extracted by Zernike Moment (ZM. After matching, the match scores from multiple biometric matchers are fused based on the likelihood ratio test. A finite Gaussian mixture model (GMM is used for estimating the genuine and impostor densities of match scores for personal verification. Our approach is also compared to some different famous approaches such as the support vector machine and the sum rule with min-max. The experimental results have confirmed that the proposed system can achieve excellent identification performance for its higher level in accuracy than different famous approaches and thus can be utilized for more application related to person verification.
Maximum likelihood pixel labeling using a spatially variant finite mixture model
International Nuclear Information System (INIS)
Gopal, S.S.; Hebert, T.J.
1996-01-01
We propose a spatially-variant mixture model for pixel labeling. Based on this spatially-variant mixture model we derive an expectation maximization algorithm for maximum likelihood estimation of the pixel labels. While most algorithms using mixture models entail the subsequent use of a Bayes classifier for pixel labeling, the proposed algorithm yields maximum likelihood estimates of the labels themselves and results in unambiguous pixel labels. The proposed algorithm is fast, robust, easy to implement, flexible in that it can be applied to any arbitrary image data where the number of classes is known and, most importantly, obviates the need for an explicit labeling rule. The algorithm is evaluated both quantitatively and qualitatively on simulated data and on clinical magnetic resonance images of the human brain
Kelly, D. A.; Fermelia, A.; Lee, G. K. F.
1990-01-01
An adaptive Kalman filter design that utilizes recursive maximum likelihood parameter identification is discussed. At the center of this design is the Kalman filter itself, which has the responsibility for attitude determination. At the same time, the identification algorithm is continually identifying the system parameters. The approach is applicable to nonlinear, as well as linear systems. This adaptive Kalman filter design has much potential for real time implementation, especially considering the fast clock speeds, cache memory and internal RAM available today. The recursive maximum likelihood algorithm is discussed in detail, with special attention directed towards its unique matrix formulation. The procedure for using the algorithm is described along with comments on how this algorithm interacts with the Kalman filter.
On Bayesian Testing of Additive Conjoint Measurement Axioms Using Synthetic Likelihood.
Karabatsos, George
2018-06-01
This article introduces a Bayesian method for testing the axioms of additive conjoint measurement. The method is based on an importance sampling algorithm that performs likelihood-free, approximate Bayesian inference using a synthetic likelihood to overcome the analytical intractability of this testing problem. This new method improves upon previous methods because it provides an omnibus test of the entire hierarchy of cancellation axioms, beyond double cancellation. It does so while accounting for the posterior uncertainty that is inherent in the empirical orderings that are implied by these axioms, together. The new method is illustrated through a test of the cancellation axioms on a classic survey data set, and through the analysis of simulated data.
Clarification of the use of chi-square and likelihood functions in fits to histograms
International Nuclear Information System (INIS)
Baker, S.; Cousins, R.D.
1984-01-01
We consider the problem of fitting curves to histograms in which the data obey multinomial or Poisson statistics. Techniques commonly used by physicists are examined in light of standard results found in the statistics literature. We review the relationship between multinomial and Poisson distributions, and clarify a sufficient condition for equality of the area under the fitted curve and the number of events on the histogram. Following the statisticians, we use the likelihood ratio test to construct a general Z 2 statistic, Zsub(lambda) 2 , which yields parameter and error estimates identical to those of the method of maximum likelihood. The Zsub(lambda) 2 statistic is further useful for testing goodness-of-fit since the value of its minimum asymptotically obeys a classical chi-square distribution. One should be aware, however, of the potential for statistical bias, especially when the number of events is small. (orig.)
International Nuclear Information System (INIS)
Beer, M.
1980-01-01
The maximum likelihood method for the multivariate normal distribution is applied to the case of several individual eigenvalues. Correlated Monte Carlo estimates of the eigenvalue are assumed to follow this prescription and aspects of the assumption are examined. Monte Carlo cell calculations using the SAM-CE and VIM codes for the TRX-1 and TRX-2 benchmark reactors, and SAM-CE full core results are analyzed with this method. Variance reductions of a few percent to a factor of 2 are obtained from maximum likelihood estimation as compared with the simple average and the minimum variance individual eigenvalue. The numerical results verify that the use of sample variances and correlation coefficients in place of the corresponding population statistics still leads to nearly minimum variance estimation for a sufficient number of histories and aggregates
Energy Technology Data Exchange (ETDEWEB)
Singh, Harpreet; Arvind; Dorai, Kavita, E-mail: kavita@iisermohali.ac.in
2016-09-07
Estimation of quantum states is an important step in any quantum information processing experiment. A naive reconstruction of the density matrix from experimental measurements can often give density matrices which are not positive, and hence not physically acceptable. How do we ensure that at all stages of reconstruction, we keep the density matrix positive? Recently a method has been suggested based on maximum likelihood estimation, wherein the density matrix is guaranteed to be positive definite. We experimentally implement this protocol on an NMR quantum information processor. We discuss several examples and compare with the standard method of state estimation. - Highlights: • State estimation using maximum likelihood method was performed on an NMR quantum information processor. • Physically valid density matrices were obtained every time in contrast to standard quantum state tomography. • Density matrices of several different entangled and separable states were reconstructed for two and three qubits.
Likelihood updating of random process load and resistance parameters by monitoring
DEFF Research Database (Denmark)
Friis-Hansen, Peter; Ditlevsen, Ove Dalager
2003-01-01
that maximum likelihood estimation is a rational alternative to an arbitrary weighting for least square fitting. The derived likelihood function gets singularities if the spectrum is prescribed with zero values at some frequencies. This is often the case for models of technically relevant processes......, even though it is of complicated mathematical form, allows an approximate Bayesian updating and control of the time development of the parameters. Some of these parameters can be structural parameters that by too much change reveal progressing damage or other malfunctioning. Thus current process......Spectral parameters for a stationary Gaussian process are most often estimated by Fourier transformation of a realization followed by some smoothing procedure. This smoothing is often a weighted least square fitting of some prespecified parametric form of the spectrum. In this paper it is shown...
Diagonal Likelihood Ratio Test for Equality of Mean Vectors in High-Dimensional Data
Hu, Zongliang; Tong, Tiejun; Genton, Marc G.
2017-01-01
We propose a likelihood ratio test framework for testing normal mean vectors in high-dimensional data under two common scenarios: the one-sample test and the two-sample test with equal covariance matrices. We derive the test statistics under the assumption that the covariance matrices follow a diagonal matrix structure. In comparison with the diagonal Hotelling's tests, our proposed test statistics display some interesting characteristics. In particular, they are a summation of the log-transformed squared t-statistics rather than a direct summation of those components. More importantly, to derive the asymptotic normality of our test statistics under the null and local alternative hypotheses, we do not require the assumption that the covariance matrix follows a diagonal matrix structure. As a consequence, our proposed test methods are very flexible and can be widely applied in practice. Finally, simulation studies and a real data analysis are also conducted to demonstrate the advantages of our likelihood ratio test method.
Planck 2015 results. XI. CMB power spectra, likelihoods, and robustness of parameters
Aghanim, N.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A.J.; Barreiro, R.B.; Bartlett, J.G.; Bartolo, N.; Battaner, E.; Benabed, K.; Benoit, A.; Benoit-Levy, A.; Bernard, J.P.; Bersanelli, M.; Bielewicz, P.; Bock, J.J.; Bonaldi, A.; Bonavera, L.; Bond, J.R.; Borrill, J.; Bouchet, F.R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R.C.; Calabrese, E.; Cardoso, J.F.; Catalano, A.; Challinor, A.; Chiang, H.C.; Christensen, P.R.; Clements, D.L.; Colombo, L.P.L.; Combet, C.; Coulais, A.; Crill, B.P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R.D.; Davis, R.J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Desert, F.X.; Di Valentino, E.; Dickinson, C.; Diego, J.M.; Dolag, K.; Dole, H.; Donzelli, S.; Dore, O.; Douspis, M.; Ducout, A.; Dunkley, J.; Dupac, X.; Efstathiou, G.; Elsner, F.; Ensslin, T.A.; Eriksen, H.K.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A.A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Gauthier, C.; Gerbino, M.; Giard, M.; Gjerlow, E.; Gonzalez-Nuevo, J.; Gorski, K.M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J.E.; Hamann, J.; Hansen, F.K.; Harrison, D.L.; Helou, G.; Henrot-Versille, S.; Hernandez-Monteagudo, C.; Herranz, D.; Hildebrandt, S.R.; Hivon, E.; Holmes, W.A.; Hornstrup, A.; Huffenberger, K.M.; Hurier, G.; Jaffe, A.H.; Jones, W.C.; Juvela, M.; Keihanen, E.; Keskitalo, R.; Kiiveri, K.; Knoche, J.; Knox, L.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lahteenmaki, A.; Lamarre, J.M.; Lasenby, A.; Lattanzi, M.; Lawrence, C.R.; Le Jeune, M.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Lewis, A.; Liguori, M.; Lilje, P.B.; Lilley, M.; Linden-Vornle, M.; Lindholm, V.; Lopez-Caniego, M.; Macias-Perez, J.F.; Maffei, B.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P.G.; Martinez-Gonzalez, E.; Masi, S.; Matarrese, S.; Meinhold, P.R.; Melchiorri, A.; Migliaccio, M.; Millea, M.; Miville-Deschenes, M.A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J.A.; Narimani, A.; Naselsky, P.; Nati, F.; Natoli, P.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C.A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Partridge, B.; Pasian, F.; Patanchon, G.; Pearson, T.J.; Perdereau, O.; Perotto, L.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Pratt, G.W.; Prunet, S.; Puget, J.L.; Rachen, J.P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rossetti, M.; Roudier, G.; d'Orfeuil, B.Rouille; Rubino-Martin, J.A.; Rusholme, B.; Salvati, L.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Serra, P.; Spencer, L.D.; Spinelli, M.; Stolyarov, V.; Stompor, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.S.; Sygnet, J.F.; Tauber, J.A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Trombetti, T.; Tucci, M.; Tuovinen, J.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L.A.; Wandelt, B.D.; Wehus, I.K.; Yvon, D.; Zacchei, A.; Zonca, A.
2016-01-01
This paper presents the Planck 2015 likelihoods, statistical descriptions of the 2-point correlation functions of CMB temperature and polarization. They use the hybrid approach employed previously: pixel-based at low multipoles, $\\ell$, and a Gaussian approximation to the distribution of cross-power spectra at higher $\\ell$. The main improvements are the use of more and better processed data and of Planck polarization data, and more detailed foreground and instrumental models. More than doubling the data allows further checks and enhanced immunity to systematics. Progress in foreground modelling enables a larger sky fraction, contributing to enhanced precision. Improvements in processing and instrumental models further reduce uncertainties. Extensive tests establish robustness and accuracy, from temperature, from polarization, and from their combination, and show that the {\\Lambda}CDM model continues to offer a very good fit. We further validate the likelihood against specific extensions to this baseline, suc...
A review of studies on persuasion from the viewpoint of the Elaboration Likelihood Model (1)
Fukada, Hiromi; Kimura, Kenichi; Makino, Koshi; Higuchi, Masataka
2000-01-01
The purpose of this paper was to review studies on persuasion from the viewpoint of the Elaboration Likelihood Model based on Petty & Wegener (1998). The paper consists of the following four parts. 1. Introduction. 2. Multiple roles for persuasion variables. 3. Source variables: (1) credibility (expertise, trustworthiness), (2) attractiveness/likableness, (3) power, (4) additional source factors related to credibility, liking and power (speed of speech, demographic variables, majority/minorit...
On-line validation of linear process models using generalized likelihood ratios
International Nuclear Information System (INIS)
Tylee, J.L.
1981-12-01
A real-time method for testing the validity of linear models of nonlinear processes is described and evaluated. Using generalized likelihood ratios, the model dynamics are continually monitored to see if the process has moved far enough away from the nominal linear model operating point to justify generation of a new linear model. The method is demonstrated using a seventh-order model of a natural circulation steam generator
Estimation of Financial Agent-Based Models with Simulated Maximum Likelihood
Czech Academy of Sciences Publication Activity Database
Kukačka, Jiří; Baruník, Jozef
2017-01-01
Roč. 85, č. 1 (2017), s. 21-45 ISSN 0165-1889 R&D Projects: GA ČR(CZ) GBP402/12/G097 Institutional support: RVO:67985556 Keywords : heterogeneous agent model, * simulated maximum likelihood * switching Subject RIV: AH - Economics OBOR OECD: Finance Impact factor: 1.000, year: 2016 http://library.utia.cas.cz/separaty/2017/E/kukacka-0478481.pdf
A Reliability Test of a Complex System Based on Empirical Likelihood
Zhou, Yan; Fu, Liya; Zhang, Jun; Hui, Yongchang
2016-01-01
To analyze the reliability of a complex system described by minimal paths, an empirical likelihood method is proposed to solve the reliability test problem when the subsystem distributions are unknown. Furthermore, we provide a reliability test statistic of the complex system and extract the limit distribution of the test statistic. Therefore, we can obtain the confidence interval for reliability and make statistical inferences. The simulation studies also demonstrate the theorem results.
Maximum likelihood reconstruction in fully 3D PET via the SAGE algorithm
International Nuclear Information System (INIS)
Ollinger, J.M.; Goggin, A.S.
1996-01-01
The SAGE and ordered subsets algorithms have been proposed as fast methods to compute penalized maximum likelihood estimates in PET. We have implemented both for use in fully 3D PET and completed a preliminary evaluation. The technique used to compute the transition matrix is fully described. The evaluation suggests that the ordered subsets algorithm converges much faster than SAGE, but that it stops short of the optimal solution
Elaboration Likelihood Model and an Analysis of the Contexts of Its Application
Aslıhan Kıymalıoğlu
2014-01-01
Elaboration Likelihood Model (ELM), which supports the existence of two routes to persuasion: central and peripheral routes, has been one of the major models on persuasion. As the number of studies in the Turkish literature on ELM is limited, a detailed explanation of the model together with a comprehensive literature review was considered to be contributory for this gap. The findings of the review reveal that the model was mostly used in marketing and advertising researches, that the concept...
Maximum likelihood unit rooting test in the presence GARCH: A new test with increased power
Cook , Steve
2008-01-01
Abstract The literature on testing the unit root hypothesis in the presence of GARCH errors is extended. A new test based upon the combination of local-to-unity detrending and joint maximum likelihood estimation of the autoregressive parameter and GARCH process is presented. The finite sample distribution of the test is derived under alternative decisions regarding the deterministic terms employed. Using Monte Carlo simulation, the newly proposed ML t-test is shown to exhibit incre...
L.U.St: a tool for approximated maximum likelihood supertree reconstruction.
Akanni, Wasiu A; Creevey, Christopher J; Wilkinson, Mark; Pisani, Davide
2014-06-12
Supertrees combine disparate, partially overlapping trees to generate a synthesis that provides a high level perspective that cannot be attained from the inspection of individual phylogenies. Supertrees can be seen as meta-analytical tools that can be used to make inferences based on results of previous scientific studies. Their meta-analytical application has increased in popularity since it was realised that the power of statistical tests for the study of evolutionary trends critically depends on the use of taxon-dense phylogenies. Further to that, supertrees have found applications in phylogenomics where they are used to combine gene trees and recover species phylogenies based on genome-scale data sets. Here, we present the L.U.St package, a python tool for approximate maximum likelihood supertree inference and illustrate its application using a genomic data set for the placental mammals. L.U.St allows the calculation of the approximate likelihood of a supertree, given a set of input trees, performs heuristic searches to look for the supertree of highest likelihood, and performs statistical tests of two or more supertrees. To this end, L.U.St implements a winning sites test allowing ranking of a collection of a-priori selected hypotheses, given as a collection of input supertree topologies. It also outputs a file of input-tree-wise likelihood scores that can be used as input to CONSEL for calculation of standard tests of two trees (e.g. Kishino-Hasegawa, Shimidoara-Hasegawa and Approximately Unbiased tests). This is the first fully parametric implementation of a supertree method, it has clearly understood properties, and provides several advantages over currently available supertree approaches. It is easy to implement and works on any platform that has python installed. bitBucket page - https://afro-juju@bitbucket.org/afro-juju/l.u.st.git. Davide.Pisani@bristol.ac.uk.
Climatic and ecological future of the Amazon: likelihood and causes of change
B. Cook; N. Zeng; J.-H. Yoon
2010-01-01
Some recent climate modeling results suggested a possible dieback of the Amazon rainforest under future climate change, a prediction that raised considerable interest as well as controversy. To determine the likelihood and causes of such changes, we analyzed the output of 15 models from the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC/AR4) and a dynamic vegetation model VEGAS driven by these climate output. Our results suggest that the core of the Amazon rainforest...
Rahnamaei, Z.; Nematollahi, N.; Farnoosh, R.
2012-01-01
We introduce an alternative skew-slash distribution by using the scale mixture of the exponential power distribution. We derive the properties of this distribution and estimate its parameter by Maximum Likelihood and Bayesian methods. By a simulation study we compute the mentioned estimators and their mean square errors, and we provide an example on real data to demonstrate the modeling strength of the new distribution.
Directory of Open Access Journals (Sweden)
Z. Rahnamaei
2012-01-01
Full Text Available We introduce an alternative skew-slash distribution by using the scale mixture of the exponential power distribution. We derive the properties of this distribution and estimate its parameter by Maximum Likelihood and Bayesian methods. By a simulation study we compute the mentioned estimators and their mean square errors, and we provide an example on real data to demonstrate the modeling strength of the new distribution.
Cosmic shear measurement with maximum likelihood and maximum a posteriori inference
Hall, Alex; Taylor, Andy
2017-06-01
We investigate the problem of noise bias in maximum likelihood and maximum a posteriori estimators for cosmic shear. We derive the leading and next-to-leading order biases and compute them in the context of galaxy ellipticity measurements, extending previous work on maximum likelihood inference for weak lensing. We show that a large part of the bias on these point estimators can be removed using information already contained in the likelihood when a galaxy model is specified, without the need for external calibration. We test these bias-corrected estimators on simulated galaxy images similar to those expected from planned space-based weak lensing surveys, with promising results. We find that the introduction of an intrinsic shape prior can help with mitigation of noise bias, such that the maximum a posteriori estimate can be made less biased than the maximum likelihood estimate. Second-order terms offer a check on the convergence of the estimators, but are largely subdominant. We show how biases propagate to shear estimates, demonstrating in our simple set-up that shear biases can be reduced by orders of magnitude and potentially to within the requirements of planned space-based surveys at mild signal-to-noise ratio. We find that second-order terms can exhibit significant cancellations at low signal-to-noise ratio when Gaussian noise is assumed, which has implications for inferring the performance of shear-measurement algorithms from simplified simulations. We discuss the viability of our point estimators as tools for lensing inference, arguing that they allow for the robust measurement of ellipticity and shear.
Unbinned maximum likelihood fit for the CP conserving couplings for W + photon production at CDF
International Nuclear Information System (INIS)
Lannon, K.
1994-01-01
We present an unbinned maximum likelihood fit as an alternative to the currently used fit for the CP conserving couplings W plus photon production studied at CDF. We show that a four parameter double exponential fits the E T spectrum of the photon very well. We also show that the fit parameters can be related to and by a second order polynomial. Finally, we discuss various conclusions we have reasoned from our results to the fit so far
Performance of penalized maximum likelihood in estimation of genetic covariances matrices
Directory of Open Access Journals (Sweden)
Meyer Karin
2011-11-01
Full Text Available Abstract Background Estimation of genetic covariance matrices for multivariate problems comprising more than a few traits is inherently problematic, since sampling variation increases dramatically with the number of traits. This paper investigates the efficacy of regularized estimation of covariance components in a maximum likelihood framework, imposing a penalty on the likelihood designed to reduce sampling variation. In particular, penalties that "borrow strength" from the phenotypic covariance matrix are considered. Methods An extensive simulation study was carried out to investigate the reduction in average 'loss', i.e. the deviation in estimated matrices from the population values, and the accompanying bias for a range of parameter values and sample sizes. A number of penalties are examined, penalizing either the canonical eigenvalues or the genetic covariance or correlation matrices. In addition, several strategies to determine the amount of penalization to be applied, i.e. to estimate the appropriate tuning factor, are explored. Results It is shown that substantial reductions in loss for estimates of genetic covariance can be achieved for small to moderate sample sizes. While no penalty performed best overall, penalizing the variance among the estimated canonical eigenvalues on the logarithmic scale or shrinking the genetic towards the phenotypic correlation matrix appeared most advantageous. Estimating the tuning factor using cross-validation resulted in a loss reduction 10 to 15% less than that obtained if population values were known. Applying a mild penalty, chosen so that the deviation in likelihood from the maximum was non-significant, performed as well if not better than cross-validation and can be recommended as a pragmatic strategy. Conclusions Penalized maximum likelihood estimation provides the means to 'make the most' of limited and precious data and facilitates more stable estimation for multi-dimensional analyses. It should
Taghva, Alexander; Karst, Edward; Underwood, Paul
2017-08-01
Concordant paresthesia coverage is an independent predictor of pain relief following spinal cord stimulation (SCS). Using aggregate data, our objective is to produce a map of paresthesia coverage as a function of electrode location in SCS. This retrospective analysis used x-rays, SCS programming data, and paresthesia coverage maps from the EMPOWER registry of SCS implants for chronic neuropathic pain. Spinal level of dorsal column stimulation was determined by x-ray adjudication and active cathodes in patient programs. Likelihood of paresthesia coverage was determined as a function of stimulating electrode location. Segments of paresthesia coverage were grouped anatomically. Fisher's exact test was used to identify significant differences in likelihood of paresthesia coverage as a function of spinal stimulation level. In the 178 patients analyzed, the most prevalent areas of paresthesia coverage were buttocks, anterior and posterior thigh (each 98%), and low back (94%). Unwanted paresthesia at the ribs occurred in 8% of patients. There were significant differences in the likelihood of achieving paresthesia, with higher thoracic levels (T5, T6, and T7) more likely to achieve low back coverage but also more likely to introduce paresthesia felt at the ribs. Higher levels in the thoracic spine were associated with greater coverage of the buttocks, back, and thigh, and with lesser coverage of the leg and foot. This paresthesia atlas uses real-world, aggregate data to determine likelihood of paresthesia coverage as a function of stimulating electrode location. It represents an application of "big data" techniques, and a step toward achieving personalized SCS therapy tailored to the individual's chronic pain. © 2017 International Neuromodulation Society.
International Nuclear Information System (INIS)
1984-05-01
The disposal of radioactive wastes in deep geologic formations provides a means of isolating the waste from people until the radioactivity has decayed to safe levels. However, isolating people from the wastes is a different problem, since we do not know what the future condition of society will be. The Human Interference Task Force was convened by the US Department of Energy to determine whether reasonable means exist (or could be developed) to reduce the likelihood of future human unintentionally intruding on radioactive waste isolation systems. The task force concluded that significant reductions in the likelihood of human interference could be achieved, for perhaps thousands of years into the future, if appropriate steps are taken to communicate the existence of the repository. Consequently, for two years the task force directed most of its study toward the area of long-term communication. Methods are discussed for achieving long-term communication by using permanent markers and widely disseminated records, with various steps taken to provide multiple levels of protection against loss, destruction, and major language/societal changes. Also developed is the concept of a universal symbol to denote Caution - Biohazardous Waste Buried Here. If used for the thousands of non-radioactive biohazardous waste sites in this country alone, a symbol could transcend generations and language changes, thereby vastly improving the likelihood of successful isolation of all buried biohazardous wastes
Risk Presentation Using the Three Dimensions of Likelihood, Severity, and Level of Control
Watson, Clifford
2010-01-01
Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the two-dimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the leastwell-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and three-dimensional charting gives a visual confirmation of the relationship between causes and their controls.
Watson, Clifford C.
2011-01-01
Traditional hazard analysis techniques utilize a two-dimensional representation of the results determined by relative likelihood and severity of the residual risk. These matrices present a quick-look at the Likelihood (Y-axis) and Severity (X-axis) of the probable outcome of a hazardous event. A three-dimensional method, described herein, utilizes the traditional X and Y axes, while adding a new, third dimension, shown as the Z-axis, and referred to as the Level of Control. The elements of the Z-axis are modifications of the Hazard Elimination and Control steps (also known as the Hazard Reduction Precedence Sequence). These steps are: 1. Eliminate risk through design. 2. Substitute less risky materials for more hazardous materials. 3. Install safety devices. 4. Install caution and warning devices. 5. Develop administrative controls (to include special procedures and training.) 6. Provide protective clothing and equipment. When added to the two-dimensional models, the level of control adds a visual representation of the risk associated with the hazardous condition, creating a tall-pole for the least-well-controlled failure while establishing the relative likelihood and severity of all causes and effects for an identified hazard. Computer modeling of the analytical results, using spreadsheets and three-dimensional charting gives a visual confirmation of the relationship between causes and their controls.
Directory of Open Access Journals (Sweden)
Ross S Williamson
2015-04-01
Full Text Available Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular method, known as maximally informative dimensions (MID, uses an information-theoretic quantity known as "single-spike information" to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex.
Directory of Open Access Journals (Sweden)
K. Yao
2007-12-01
Full Text Available We investigate the maximum likelihood (ML direction-of-arrival (DOA estimation of multiple wideband sources in the presence of unknown nonuniform sensor noise. New closed-form expression for the direction estimation CramÃƒÂ©r-Rao-Bound (CRB has been derived. The performance of the conventional wideband uniform ML estimator under nonuniform noise has been studied. In order to mitigate the performance degradation caused by the nonuniformity of the noise, a new deterministic wideband nonuniform ML DOA estimator is derived and two associated processing algorithms are proposed. The first algorithm is based on an iterative procedure which stepwise concentrates the log-likelihood function with respect to the DOAs and the noise nuisance parameters, while the second is a noniterative algorithm that maximizes the derived approximately concentrated log-likelihood function. The performance of the proposed algorithms is tested through extensive computer simulations. Simulation results show the stepwise-concentrated ML algorithm (SC-ML requires only a few iterations to converge and both the SC-ML and the approximately-concentrated ML algorithm (AC-ML attain a solution close to the derived CRB at high signal-to-noise ratio.
Directory of Open Access Journals (Sweden)
Yuejiao Fu
2018-04-01
Full Text Available The Sharpe ratio is a widely used risk-adjusted performance measurement in economics and finance. Most of the known statistical inferential methods devoted to the Sharpe ratio are based on the assumption that the data are normally distributed. In this article, without making any distributional assumption on the data, we develop the adjusted empirical likelihood method to obtain inference for a parameter of interest in the presence of nuisance parameters. We show that the log adjusted empirical likelihood ratio statistic is asymptotically distributed as the chi-square distribution. The proposed method is applied to obtain inference for the Sharpe ratio. Simulation results illustrate that the proposed method is comparable to Jobson and Korkie’s method (1981 and outperforms the empirical likelihood method when the data are from a symmetric distribution. In addition, when the data are from a skewed distribution, the proposed method significantly outperforms all other existing methods. A real-data example is analyzed to exemplify the application of the proposed method.
Likelihood-based methods for evaluating principal surrogacy in augmented vaccine trials.
Liu, Wei; Zhang, Bo; Zhang, Hui; Zhang, Zhiwei
2017-04-01
There is growing interest in assessing immune biomarkers, which are quick to measure and potentially predictive of long-term efficacy, as surrogate endpoints in randomized, placebo-controlled vaccine trials. This can be done under a principal stratification approach, with principal strata defined using a subject's potential immune responses to vaccine and placebo (the latter may be assumed to be zero). In this context, principal surrogacy refers to the extent to which vaccine efficacy varies across principal strata. Because a placebo recipient's potential immune response to vaccine is unobserved in a standard vaccine trial, augmented vaccine trials have been proposed to produce the information needed to evaluate principal surrogacy. This article reviews existing methods based on an estimated likelihood and a pseudo-score (PS) and proposes two new methods based on a semiparametric likelihood (SL) and a pseudo-likelihood (PL), for analyzing augmented vaccine trials. Unlike the PS method, the SL method does not require a model for missingness, which can be advantageous when immune response data are missing by happenstance. The SL method is shown to be asymptotically efficient, and it performs similarly to the PS and PL methods in simulation experiments. The PL method appears to have a computational advantage over the PS and SL methods.