Energy Technology Data Exchange (ETDEWEB)
Morenas, Vincent [Ecole Doctorale des Sciences Fondamentales, Universite Blaise Pascal, U.F.R. de Recherche Scientifique et Technique, F-63177 Aubiere (France)
1997-12-19
The study of semileptonic decays is of crucial importance for the physics of beauty. It was usually believed that the rates of these reactions were saturated by the channels leading to the production of ground state D and D{sup *} mesons only. Yet, experimental results have shown recently that the contribution of orbitally excited mesons are not that small. In these thesis it is presented a study of the semileptonic decays of B mesons into the first orbitally excited charmed states D{sup **}: by using the formalism of Bakamjian-Thomas to construct the mesonic states, together with the hypothesis of infinite mass limit of the heavy quark, we provide a covariant description of the hadronic transition amplitude; moreover, all the `good` properties of the heavy quark symmetries are naturally fulfilled. We then fixed the dynamics of the bound states of quarks by introducing four spectroscopic models and made numerical predictions, which are discussed and compared to other theoretical and experimental data when available. Finally, we also applied this formalism to the study of annihilation processes: the transition amplitude are then also written in a covariant way and the properties of heavy quark symmetries fulfilled. Numerical predictions of decay constants were made with the same four spectroscopic models. (author) 87 refs., 20 figs., 13 tabs.
Second-class currents and DELTA s in nu(nu-bar)p elastic scattering
Wilkinson, D H
2001-01-01
nu(nu-bar)p elastic scattering is sensitive to the magnitude, DELTA s, of the strange quark's presence within the proton. But it is also sensitive to the strength of second-class currents so we must be assured that the effect of such currents, having regard for the experimental upper limit to their strength, is negligible before extracting DELTA s from such scattering. It is shown that searches for DELTA s through nu(nu-bar)p elastic scattering are unlikely to be troubled by this consideration below neutrino energies of about 0.1 GeV but that at higher energies very serious uncertainty arises.
Inclusive negative-hadron production from high-energy nu-bar-nucleus charged-current interactions
International Nuclear Information System (INIS)
Berge, J.P.; Bogert, D.; Endorf, R.; Hanft, R.; Malko, J.A.; Moffatt, G.; Nezrick, F.A.; Scott, W.; Smart, W.; Wolfson, J.; Ammosov, V.V.; Amrakhov, A.H.; Denisov, A.G.; Ermolov, P.F.; Gapienko, V.A.; Klukhin, V.I.; Koreshev, V.I.; Pitukhin, P.V.; Rjabov, V.G.; Slobodyuk, E.A.; Sirotenko, V.I.; Efremenko, V.I.; Gorichev, P.A.; Kaftanov, V.S.; Khovansky, V.D.; Kliger, G.K.; Kolganov, V.Z.; Krutchinin, S.P.; Kubantsev, M.A.; Rosanov, A.N.; Savitsky, M.M.; Shevchenko, V.G.; Coffin, C.T.; Diamond, R.N.; French, H.; Louis, W.; Roe, B.P.; Ross, R.T.; Seidl, A.A.; Sinclair, D.
1978-01-01
We present data on inclusive negative-hadron production from charged-current antineutrino interactions in a 21% Ne--H mixture. Inclusive single-particle distributions are presented and are shown to be insensitive to the momentum transferred to the hadron vertex. Comparisons made to inclusive data from π - p and π - n interactions indicate a close similarity between the hadrons resulting from π-nucleon and nu-bar-nucleus interactions. The general features of the nu-bar-nucleus data are found to be similar to those seen in nu-barp interactions. This last observation implies that nu-barp and nu-barn interactions are similar and that nuclear effects are small
SEARCH FOR THE RARE KAON DECAY K{sup +} {yields} {pi}{sup +} {nu}{bar {nu}}
Energy Technology Data Exchange (ETDEWEB)
BHUYAN,B.
2003-05-03
This thesis describes the search for the rare decay K{sup +} {yields} {pi}{sup +} {nu}{bar {nu}} in the pion momentum region 140 MeV/c {le} P{sub {pi}{sup +}} {le} 195 MeV/c. This is a Flavor Changing Neutral Current (FCNC) decay which is forbidden to the first order in the Standard Model (SM) by the GIM mechanism. However, this decay mode is allowed in the second order by two Z-Penguin and one box diagram and is expected to have a branching ratio of (0.72 {+-} 0.21) x 10{sup -10}. This decay mode is sensitive to the coupling of top to down quark and therefore a measurement of the branching ratio for this decay mode provides a measurement of the Cabibbo-Kobayashi-Maskawa matrix element V{sub td}. The recent observation of two events in the pion momentum region 211 MeV/c {le} P{sup {pi}{sup +}} {le} 229 MeV/c estimates a branching ratio of 1.57{sub -0.82}{sup +1.75} x 10{sup -10} for the same decay mode. We have extended the search for this decay to the lower pion momentum region. Data collected by the Experiment E787 at Brookhaven National Laboratory during the 1996 and 1997 run were analyzed in this thesis.
Energy Technology Data Exchange (ETDEWEB)
Popov, B.A
1998-05-01
This work has been done in the framework of the NOMAD experiment at CERN. It is devoted to the {nu}{sub {mu}} {yields} {nu}{sub {tau}} oscillation search in the {tau}{sup -} {yields} e{sup -}{nu}-bar{sub e}{nu}{sub {tau}} decay channel. After a brief reminder on the neutrino properties and a short review of the experimental searches for neutrino oscillations, the description of the NOMAD experiment is given. The event reconstruction in the NOMAD experiment is presented with a special emphasis put on the electron identification and reconstruction. The track model used for the charged track reconstruction is described in details. The algorithm developed to treat electron trajectories in the NOMAD setup based on the sub-detector matching technique and the breakpoint search algorithm is presented. The quality of the reconstruction of the kinematics of neutrino interactions is illustrated. It is shown that the currently used detector simulation program cannot reproduce precisely the behaviour of the hadronic jet observed in the NOMAD real data especially in the plane perpendicular to the incoming neutrino direction. To overcome this problem simulations based on the real data are used whenever possible. The method based on the likelihood ratio is developed to discriminate a signal from a background. A selection of {nu}{sub e} CC candidates from the NOMAD '96 data set is performed using this technique. 1842 events are extracted with a selection efficiency of (38.5 {+-} 0.5%) while the background contamination is estimated to be less than 0.5%. This number of events is compatible with our expectations: 1891 {+-} 25(stat){+-} 95(syst). No sign of possible {nu}{sub {mu}} {yields} {nu}{sub e} oscillation signal corresponding to the LSND solution in the large {delta}m{sup 2} region is observed in the NOMAD data. Finally, the preliminary analysis of the {nu}{sub {mu}} {yields} {nu}{sub {tau}} oscillation search in the {tau}{sup -} {yields} e{sup -}{nu}-bar{sub e
International Nuclear Information System (INIS)
LaBauve, R.J.; Muir, D.W.
1978-01-01
A library of 30-group multigroup covariance data was prepared from preliminary ENDF/B-V data with the NJOY code. Data for Fe, Cr, Ni, 10 B, C, Cu, H, and Pb are included in this library. Reactions include total cross sections, elastic and inelastic scattering cross sections, and the most important absorption cross sections. Typical data from the file are shown. 3 tables
A Search for B+ --> tau + nu tau Recoiling Against B- --> D0 l- nu-bar l X
Sekula, S J
2003-01-01
We present a search for the decay B sup + -> tau sup +nu subtau in 88.9 x 10 sup 6 UPSILON(4S) decays recorded with the BABAR detector at the SLAC B-Factory. A sample of semi-exclusive, semi-leptonic B decays (B sup - -> D sup 0 (ell) sup - (bar nu) sub e sub l sub l X), where X is either a photon, pi sup 0 , or nothing, is used to identify the daughter particles that are associated with the other B meson in each event. These particles are searched for evidence of a one-prong leptonic B sup + -> tau sup +nu subtau decay. For this data sample we set a preliminary upper limit on the branching fraction of BETA(B sup + -> tau sup +nu subtau) tau sup +nu subtau to give a combined preliminary limit of BETA(B sup + -> tau sup +nu subtau) < 4.1 x 10 sup - sup 4.
AFCI-2.0 Neutron Cross Section Covariance Library
Energy Technology Data Exchange (ETDEWEB)
Herman, M.; Herman, M; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.
2011-03-01
materials and fission products, and 20 actinides. Covariances are given in 33-energy groups, from 10?5 eV to 19.6 MeV, obtained by processing with LANL processing code NJOY using 1/E flux. In addition to these 110 files, the library contains 20 files with nu-bar covariances, 3 files with covariances of prompt fission neutron spectra (238,239,240-Pu), and 2 files with mu-bar covariances (23-Na, 56-Fe). Over the period of three years several working versions of the library have been released and tested by ANL and INL reactor analysts. Useful feedback has been collected allowing gradual improvements of the library. In addition, QA system was developed to check basic properties and features of the whole library, allowing visual inspection of uncertainty and correlations plots, inspection of uncertainties of integral quantities with independent databases, and dispersion of cross sections between major evaluated libraries. The COMMARA-2.0 beta version of the library was released to ANL and INL reactor analysts in October 2010. The final version, described in the present report, was released in March 2011.
AFCI-2.0 Neutron Cross Section Covariance Library
International Nuclear Information System (INIS)
Herman, M.; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.
2011-01-01
structural materials and fission products, and 20 actinides. Covariances are given in 33-energy groups, from 10?5 eV to 19.6 MeV, obtained by processing with LANL processing code NJOY using 1/E flux. In addition to these 110 files, the library contains 20 files with nu-bar covariances, 3 files with covariances of prompt fission neutron spectra (238,239,240-Pu), and 2 files with mu-bar covariances (23-Na, 56-Fe). Over the period of three years several working versions of the library have been released and tested by ANL and INL reactor analysts. Useful feedback has been collected allowing gradual improvements of the library. In addition, QA system was developed to check basic properties and features of the whole library, allowing visual inspection of uncertainty and correlations plots, inspection of uncertainties of integral quantities with independent databases, and dispersion of cross sections between major evaluated libraries. The COMMARA-2.0 beta version of the library was released to ANL and INL reactor analysts in October 2010. The final version, described in the present report, was released in March 2011.
International Nuclear Information System (INIS)
Hwang, W.P.; Henley, E.M.; Kisslinger, L.S.
1987-01-01
We investigate Δ(1232) production via charge-changing weak currents e - +p→Δ 0 +ν/sub e/ and e + +p→Δ/sup ++/+nu-bar/sub e/ at electron/positron beam energies in the range of a few GeV. A general formalism is introduced for the N→Δ transition form factors, including the weak magnetism, weak quadrupole, and weak scalar form factors for the polar-vector current and the axial, pseudoscalar, recoil, and weak electric form factors for the axial current. The form factors related to the polar-vector current are related to Δ(1232) electroproduction on a nucleon target. For nucleons and deltas, we adopt in this calculation the flavor SU(6) wave functions, with quarks described as confined Dirac particles. The quark wave function adopted is of the form given by the MIT bag model, with or without the sharp boundary smoothened out. In the few GeV range, it is found that cross sections can be as large as 10/sup -38/ cm 2 and are sensitive to induced form factors such as the weak magnetism form factor. It is also found that, for a beam energy of around 4.0 GeV, the predicted cross sections depend sensitively on whether or not the sharp boundary in the quark wave function is smoothened out
Lika, Konstadia; Kearney, Michael R.; Kooijman, Sebastiaan A. L. M.
2011-11-01
The covariation method for estimating the parameters of the standard Dynamic Energy Budget (DEB) model provides a single-step method of accessing all the core DEB parameters from commonly available empirical data. In this study, we assess the robustness of this parameter estimation procedure and analyse the role of pseudo-data using elasticity coefficients. In particular, we compare the performance of Maximum Likelihood (ML) vs. Weighted Least Squares (WLS) approaches and find that the two approaches tend to converge in performance as the number of uni-variate data sets increases, but that WLS is more robust when data sets comprise single points (zero-variate data). The efficiency of the approach is shown to be high, and the prior parameter estimates (pseudo-data) have very little influence if the real data contain information about the parameter values. For instance, the effects of the pseudo-value for the allocation fraction κ is reduced when there is information for both growth and reproduction, that for the energy conductance is reduced when information on age at birth and puberty is given, and the effects of the pseudo-value for the maturity maintenance rate coefficient are insignificant. The estimation of some parameters (e.g., the zoom factor and the shape coefficient) requires little information, while that of others (e.g., maturity maintenance rate, puberty threshold and reproduction efficiency) require data at several food levels. The generality of the standard DEB model, in combination with the estimation of all of its parameters, allows comparison of species on the basis of parameter values. We discuss a number of preliminary patterns emerging from the present collection of parameter estimates across a wide variety of taxa. We make the observation that the estimated value of the fraction κ of mobilised reserve that is allocated to soma is far away from the value that maximises reproduction. We recognise this as the reason why two very different
Kisil, Vladimir V.
2010-01-01
The paper develops theory of covariant transform, which is inspired by the wavelet construction. It was observed that many interesting types of wavelets (or coherent states) arise from group representations which are not square integrable or vacuum vectors which are not admissible. Covariant transform extends an applicability of the popular wavelets construction to classic examples like the Hardy space H_2, Banach spaces, covariant functional calculus and many others. Keywords: Wavelets, cohe...
International Nuclear Information System (INIS)
Kawano, Toshihiko; Shibata, Keiichi.
1997-09-01
A covariance evaluation system for the evaluated nuclear data library was established. The parameter estimation method and the least squares method with a spline function are used to generate the covariance data. Uncertainties of nuclear reaction model parameters are estimated from experimental data uncertainties, then the covariance of the evaluated cross sections is calculated by means of error propagation. Computer programs ELIESE-3, EGNASH4, ECIS, and CASTHY are used. Covariances of 238 U reaction cross sections were calculated with this system. (author)
Székely, Gábor J.; Rizzo, Maria L.
2010-01-01
Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but generalize and extend these classical bivariate measures of dependence. Distance correlation characterizes independence: it is zero if and only if the random vectors are independent. The notion of covariance with...
Bergshoeff, E.; Pope, C.N.; Stelle, K.S.
1990-01-01
We discuss the notion of higher-spin covariance in w∞ gravity. We show how a recently proposed covariant w∞ gravity action can be obtained from non-chiral w∞ gravity by making field redefinitions that introduce new gauge-field components with corresponding new gauge transformations.
Covariant representations of nuclear *-algebras
International Nuclear Information System (INIS)
Moore, S.M.
1978-01-01
Extensions of the Csup(*)-algebra theory for covariant representations to nuclear *-algebra are considered. Irreducible covariant representations are essentially unique, an invariant state produces a covariant representation with stable vacuum, and the usual relation between ergodic states and covariant representations holds. There exist construction and decomposition theorems and a possible relation between derivations and covariant representations
Covariant Noncommutative Field Theory
Energy Technology Data Exchange (ETDEWEB)
Estrada-Jimenez, S [Licenciaturas en Fisica y en Matematicas, Facultad de Ingenieria, Universidad Autonoma de Chiapas Calle 4a Ote. Nte. 1428, Tuxtla Gutierrez, Chiapas (Mexico); Garcia-Compean, H [Departamento de Fisica, Centro de Investigacion y de Estudios Avanzados del IPN P.O. Box 14-740, 07000 Mexico D.F., Mexico and Centro de Investigacion y de Estudios Avanzados del IPN, Unidad Monterrey Via del Conocimiento 201, Parque de Investigacion e Innovacion Tecnologica (PIIT) Autopista nueva al Aeropuerto km 9.5, Lote 1, Manzana 29, cp. 66600 Apodaca Nuevo Leon (Mexico); Obregon, O [Instituto de Fisica de la Universidad de Guanajuato P.O. Box E-143, 37150 Leon Gto. (Mexico); Ramirez, C [Facultad de Ciencias Fisico Matematicas, Universidad Autonoma de Puebla, P.O. Box 1364, 72000 Puebla (Mexico)
2008-07-02
The covariant approach to noncommutative field and gauge theories is revisited. In the process the formalism is applied to field theories invariant under diffeomorphisms. Local differentiable forms are defined in this context. The lagrangian and hamiltonian formalism is consistently introduced.
Covariant Noncommutative Field Theory
International Nuclear Information System (INIS)
Estrada-Jimenez, S.; Garcia-Compean, H.; Obregon, O.; Ramirez, C.
2008-01-01
The covariant approach to noncommutative field and gauge theories is revisited. In the process the formalism is applied to field theories invariant under diffeomorphisms. Local differentiable forms are defined in this context. The lagrangian and hamiltonian formalism is consistently introduced
Covariance data processing code. ERRORJ
International Nuclear Information System (INIS)
Kosako, Kazuaki
2001-01-01
The covariance data processing code, ERRORJ, was developed to process the covariance data of JENDL-3.2. ERRORJ has the processing functions of covariance data for cross sections including resonance parameters, angular distribution and energy distribution. (author)
Pozsgay, Victor; Hirsch, Flavien; Branciard, Cyril; Brunner, Nicolas
2017-12-01
We introduce Bell inequalities based on covariance, one of the most common measures of correlation. Explicit examples are discussed, and violations in quantum theory are demonstrated. A crucial feature of these covariance Bell inequalities is their nonlinearity; this has nontrivial consequences for the derivation of their local bound, which is not reached by deterministic local correlations. For our simplest inequality, we derive analytically tight bounds for both local and quantum correlations. An interesting application of covariance Bell inequalities is that they can act as "shared randomness witnesses": specifically, the value of the Bell expression gives device-independent lower bounds on both the dimension and the entropy of the shared random variable in a local model.
Energy Technology Data Exchange (ETDEWEB)
Bourget, Antoine; Troost, Jan [Laboratoire de Physique Théorique, École Normale Supérieure, 24 rue Lhomond, 75005 Paris (France)
2016-03-23
We construct a covariant generating function for the spectrum of chiral primaries of symmetric orbifold conformal field theories with N=(4,4) supersymmetry in two dimensions. For seed target spaces K3 and T{sup 4}, the generating functions capture the SO(21) and SO(5) representation theoretic content of the chiral ring respectively. Via string dualities, we relate the transformation properties of the chiral ring under these isometries of the moduli space to the Lorentz covariance of perturbative string partition functions in flat space.
Dimension from covariance matrices.
Carroll, T L; Byers, J M
2017-02-01
We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.
Generalized Linear Covariance Analysis
Carpenter, James R.; Markley, F. Landis
2014-01-01
This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.
Covariant field equations in supergravity
Energy Technology Data Exchange (ETDEWEB)
Vanhecke, Bram [KU Leuven, Institute for Theoretical Physics, Leuven (Belgium); Ghent University, Faculty of Physics, Gent (Belgium); Proeyen, Antoine van [KU Leuven, Institute for Theoretical Physics, Leuven (Belgium)
2017-12-15
Covariance is a useful property for handling supergravity theories. In this paper, we prove a covariance property of supergravity field equations: under reasonable conditions, field equations of supergravity are covariant modulo other field equations. We prove that for any supergravity there exist such covariant equations of motion, other than the regular equations of motion, that are equivalent to the latter. The relations that we find between field equations and their covariant form can be used to obtain multiplets of field equations. In practice, the covariant field equations are easily found by simply covariantizing the ordinary field equations. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Covariant field equations in supergravity
International Nuclear Information System (INIS)
Vanhecke, Bram; Proeyen, Antoine van
2017-01-01
Covariance is a useful property for handling supergravity theories. In this paper, we prove a covariance property of supergravity field equations: under reasonable conditions, field equations of supergravity are covariant modulo other field equations. We prove that for any supergravity there exist such covariant equations of motion, other than the regular equations of motion, that are equivalent to the latter. The relations that we find between field equations and their covariant form can be used to obtain multiplets of field equations. In practice, the covariant field equations are easily found by simply covariantizing the ordinary field equations. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Generally covariant gauge theories
International Nuclear Information System (INIS)
Capovilla, R.
1992-01-01
A new class of generally covariant gauge theories in four space-time dimensions is investigated. The field variables are taken to be a Lie algebra valued connection 1-form and a scalar density. Modulo an important degeneracy, complex [euclidean] vacuum general relativity corresponds to a special case in this class. A canonical analysis of the generally covariant gauge theories with the same gauge group as general relativity shows that they describe two degrees of freedom per space point, qualifying therefore as a new set of neighbors of general relativity. The modification of the algebra of the constraints with respect to the general relativity case is computed; this is used in addressing the question of how general relativity stands out from its neighbors. (orig.)
The Bayesian Covariance Lasso.
Khondker, Zakaria S; Zhu, Hongtu; Chu, Haitao; Lin, Weili; Ibrahim, Joseph G
2013-04-01
Estimation of sparse covariance matrices and their inverse subject to positive definiteness constraints has drawn a lot of attention in recent years. The abundance of high-dimensional data, where the sample size ( n ) is less than the dimension ( d ), requires shrinkage estimation methods since the maximum likelihood estimator is not positive definite in this case. Furthermore, when n is larger than d but not sufficiently larger, shrinkage estimation is more stable than maximum likelihood as it reduces the condition number of the precision matrix. Frequentist methods have utilized penalized likelihood methods, whereas Bayesian approaches rely on matrix decompositions or Wishart priors for shrinkage. In this paper we propose a new method, called the Bayesian Covariance Lasso (BCLASSO), for the shrinkage estimation of a precision (covariance) matrix. We consider a class of priors for the precision matrix that leads to the popular frequentist penalties as special cases, develop a Bayes estimator for the precision matrix, and propose an efficient sampling scheme that does not precalculate boundaries for positive definiteness. The proposed method is permutation invariant and performs shrinkage and estimation simultaneously for non-full rank data. Simulations show that the proposed BCLASSO performs similarly as frequentist methods for non-full rank data.
Lorentz Covariance of Langevin Equation
International Nuclear Information System (INIS)
Koide, T.; Denicol, G.S.; Kodama, T.
2008-01-01
Relativistic covariance of a Langevin type equation is discussed. The requirement of Lorentz invariance generates an entanglement between the force and noise terms so that the noise itself should not be a covariant quantity. (author)
Distance covariance for stochastic processes
DEFF Research Database (Denmark)
Matsui, Muneya; Mikosch, Thomas Valentin; Samorodnitsky, Gennady
2017-01-01
The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analog of the distance covariance for two stochastic processes...
Earth Observing System Covariance Realism
Zaidi, Waqar H.; Hejduk, Matthew D.
2016-01-01
The purpose of covariance realism is to properly size a primary object's covariance in order to add validity to the calculation of the probability of collision. The covariance realism technique in this paper consists of three parts: collection/calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics. An empirical cumulative distribution function (ECDF) Goodness-of-Fit (GOF) method is employed to determine if a covariance is properly sized by comparing the empirical distribution of Mahalanobis distance calculations to the hypothesized parent 3-DoF chi-squared distribution. To realistically size a covariance for collision probability calculations, this study uses a state noise compensation algorithm that adds process noise to the definitive epoch covariance to account for uncertainty in the force model. Process noise is added until the GOF tests pass a group significance level threshold. The results of this study indicate that when outliers attributed to persistently high or extreme levels of solar activity are removed, the aforementioned covariance realism compensation method produces a tuned covariance with up to 80 to 90% of the covariance propagation timespan passing (against a 60% minimum passing threshold) the GOF tests-a quite satisfactory and useful result.
Contributions to Large Covariance and Inverse Covariance Matrices Estimation
Kang, Xiaoning
2016-01-01
Estimation of covariance matrix and its inverse is of great importance in multivariate statistics with broad applications such as dimension reduction, portfolio optimization, linear discriminant analysis and gene expression analysis. However, accurate estimation of covariance or inverse covariance matrices is challenging due to the positive definiteness constraint and large number of parameters, especially in the high-dimensional cases. In this thesis, I develop several approaches for estimat...
International Nuclear Information System (INIS)
Ginelli, Francesco; Politi, Antonio; Chaté, Hugues; Livi, Roberto
2013-01-01
Recent years have witnessed a growing interest in covariant Lyapunov vectors (CLVs) which span local intrinsic directions in the phase space of chaotic systems. Here, we review the basic results of ergodic theory, with a specific reference to the implications of Oseledets’ theorem for the properties of the CLVs. We then present a detailed description of a ‘dynamical’ algorithm to compute the CLVs and show that it generically converges exponentially in time. We also discuss its numerical performance and compare it with other algorithms presented in the literature. We finally illustrate how CLVs can be used to quantify deviations from hyperbolicity with reference to a dissipative system (a chain of Hénon maps) and a Hamiltonian model (a Fermi–Pasta–Ulam chain). This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Lyapunov analysis: from dynamical systems theory to applications’. (paper)
Deriving covariant holographic entanglement
Energy Technology Data Exchange (ETDEWEB)
Dong, Xi [School of Natural Sciences, Institute for Advanced Study, Princeton, NJ 08540 (United States); Lewkowycz, Aitor [Jadwin Hall, Princeton University, Princeton, NJ 08544 (United States); Rangamani, Mukund [Center for Quantum Mathematics and Physics (QMAP), Department of Physics, University of California, Davis, CA 95616 (United States)
2016-11-07
We provide a gravitational argument in favour of the covariant holographic entanglement entropy proposal. In general time-dependent states, the proposal asserts that the entanglement entropy of a region in the boundary field theory is given by a quarter of the area of a bulk extremal surface in Planck units. The main element of our discussion is an implementation of an appropriate Schwinger-Keldysh contour to obtain the reduced density matrix (and its powers) of a given region, as is relevant for the replica construction. We map this contour into the bulk gravitational theory, and argue that the saddle point solutions of these replica geometries lead to a consistent prescription for computing the field theory Rényi entropies. In the limiting case where the replica index is taken to unity, a local analysis suffices to show that these saddles lead to the extremal surfaces of interest. We also comment on various properties of holographic entanglement that follow from this construction.
Networks of myelin covariance.
Melie-Garcia, Lester; Slater, David; Ruef, Anne; Sanabria-Diaz, Gretel; Preisig, Martin; Kherif, Ferath; Draganski, Bogdan; Lutti, Antoine
2018-04-01
Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures (i.e., cortical thickness) between brain structures across subjects (Evans, ). However, the existence of networks of microstructural changes within brain tissue has been largely unexplored so far. In this article, we studied in vivo the concurrent myelination processes among brain anatomical structures that gathered together emerge to form nonrandom networks. We name these "networks of myelin covariance" (Myelin-Nets). The Myelin-Nets were built from quantitative Magnetization Transfer data-an in-vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin-Nets. We therefore selected two age groups: Young-Age (20-31 years old) and Old-Age (60-71 years old) and a pool of participants from 48 to 87 years old for a Myelin-Nets aging trajectory study. We found that the topological organization of the Myelin-Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin-Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
General Galilei Covariant Gaussian Maps
Gasbarri, Giulio; Toroš, Marko; Bassi, Angelo
2017-09-01
We characterize general non-Markovian Gaussian maps which are covariant under Galilean transformations. In particular, we consider translational and Galilean covariant maps and show that they reduce to the known Holevo result in the Markovian limit. We apply the results to discuss measures of macroscopicity based on classicalization maps, specifically addressing dissipation, Galilean covariance and non-Markovianity. We further suggest a possible generalization of the macroscopicity measure defined by Nimmrichter and Hornberger [Phys. Rev. Lett. 110, 16 (2013)].
Fast Computing for Distance Covariance
Huo, Xiaoming; Szekely, Gabor J.
2014-01-01
Distance covariance and distance correlation have been widely adopted in measuring dependence of a pair of random variables or random vectors. If the computation of distance covariance and distance correlation is implemented directly accordingly to its definition then its computational complexity is O($n^2$) which is a disadvantage compared to other faster methods. In this paper we show that the computation of distance covariance and distance correlation of real valued random variables can be...
Covariant electromagnetic field lines
Hadad, Y.; Cohen, E.; Kaminer, I.; Elitzur, A. C.
2017-08-01
Faraday introduced electric field lines as a powerful tool for understanding the electric force, and these field lines are still used today in classrooms and textbooks teaching the basics of electromagnetism within the electrostatic limit. However, despite attempts at generalizing this concept beyond the electrostatic limit, such a fully relativistic field line theory still appears to be missing. In this work, we propose such a theory and define covariant electromagnetic field lines that naturally extend electric field lines to relativistic systems and general electromagnetic fields. We derive a closed-form formula for the field lines curvature in the vicinity of a charge, and show that it is related to the world line of the charge. This demonstrates how the kinematics of a charge can be derived from the geometry of the electromagnetic field lines. Such a theory may also provide new tools in modeling and analyzing electromagnetic phenomena, and may entail new insights regarding long-standing problems such as radiation-reaction and self-force. In particular, the electromagnetic field lines curvature has the attractive property of being non-singular everywhere, thus eliminating all self-field singularities without using renormalization techniques.
Covariation in Natural Causal Induction.
Cheng, Patricia W.; Novick, Laura R.
1991-01-01
Biases and models usually offered by cognitive and social psychology and by philosophy to explain causal induction are evaluated with respect to focal sets (contextually determined sets of events over which covariation is computed). A probabilistic contrast model is proposed as underlying covariation computation in natural causal induction. (SLD)
Slater, David; Ruef, Anne; Sanabria‐Diaz, Gretel; Preisig, Martin; Kherif, Ferath; Draganski, Bogdan; Lutti, Antoine
2017-01-01
Abstract Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures (i.e., cortical thickness) between brain structures across subjects (Evans, 2013). However, the existence of networks of microstructural changes within brain tissue has been largely unexplored so far. In this article, we studied in vivo the concurrent myelination processes among brain anatomical structures that gathered together emerge to form nonrandom networks. We name these “networks of myelin covariance” (Myelin‐Nets). The Myelin‐Nets were built from quantitative Magnetization Transfer data—an in‐vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin‐Nets. We therefore selected two age groups: Young‐Age (20–31 years old) and Old‐Age (60–71 years old) and a pool of participants from 48 to 87 years old for a Myelin‐Nets aging trajectory study. We found that the topological organization of the Myelin‐Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin‐Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging. PMID:29271053
Covariance Manipulation for Conjunction Assessment
Hejduk, M. D.
2016-01-01
The manipulation of space object covariances to try to provide additional or improved information to conjunction risk assessment is not an uncommon practice. Types of manipulation include fabricating a covariance when it is missing or unreliable to force the probability of collision (Pc) to a maximum value ('PcMax'), scaling a covariance to try to improve its realism or see the effect of covariance volatility on the calculated Pc, and constructing the equivalent of an epoch covariance at a convenient future point in the event ('covariance forecasting'). In bringing these methods to bear for Conjunction Assessment (CA) operations, however, some do not remain fully consistent with best practices for conducting risk management, some seem to be of relatively low utility, and some require additional information before they can contribute fully to risk analysis. This study describes some basic principles of modern risk management (following the Kaplan construct) and then examines the PcMax and covariance forecasting paradigms for alignment with these principles; it then further examines the expected utility of these methods in the modern CA framework. Both paradigms are found to be not without utility, but only in situations that are somewhat carefully circumscribed.
Covariance matrices of experimental data
International Nuclear Information System (INIS)
Perey, F.G.
1978-01-01
A complete statement of the uncertainties in data is given by its covariance matrix. It is shown how the covariance matrix of data can be generated using the information available to obtain their standard deviations. Determination of resonance energies by the time-of-flight method is used as an example. The procedure for combining data when the covariance matrix is non-diagonal is given. The method is illustrated by means of examples taken from the recent literature to obtain an estimate of the energy of the first resonance in carbon and for five resonances of 238 U
Evaluation and processing of covariance data
International Nuclear Information System (INIS)
Wagner, M.
1993-01-01
These proceedings of a specialists'meeting on evaluation and processing of covariance data is divided into 4 parts bearing on: part 1- Needs for evaluated covariance data (2 Papers), part 2- generation of covariance data (15 Papers), part 3- Processing of covariance files (2 Papers), part 4-Experience in the use of evaluated covariance data (2 Papers)
On Galilean covariant quantum mechanics
International Nuclear Information System (INIS)
Horzela, A.; Kapuscik, E.; Kempczynski, J.; Joint Inst. for Nuclear Research, Dubna
1991-08-01
Formalism exhibiting the Galilean covariance of wave mechanics is proposed. A new notion of quantum mechanical forces is introduced. The formalism is illustrated on the example of the harmonic oscillator. (author)
Estimation of covariance matrix on the experimental data for nuclear data evaluation
International Nuclear Information System (INIS)
Murata, T.
1985-01-01
In order to evaluate fission and capture cross sections of some U and Pu isotopes for JENDL-3, we have a plan for evaluating them simultaneously with a least-squares method. For the simultaneous evaluation, the covariance matrix is required for each experimental data set. In the present work, we have studied the procedures for deriving the covariance matrix from the error data given in the experimental papers. The covariance matrices were obtained using the partial errors and estimated correlation coefficients between the same type partial errors for different neutron energy. Some examples of the covariance matrix estimation are explained and the preliminary results of the simultaneous evaluation are presented. (author)
Multivariate covariance generalized linear models
DEFF Research Database (Denmark)
Bonat, W. H.; Jørgensen, Bent
2016-01-01
are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions......We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...
GLq(N)-covariant quantum algebras and covariant differential calculus
International Nuclear Information System (INIS)
Isaev, A.P.; Pyatov, P.N.
1992-01-01
GL q (N)-covariant quantum algebras with generators satisfying quadratic polynomial relations are considered. It is that, up to some innessential arbitrariness, there are only two kinds of such quantum algebras, namely, the algebras with q-deformed commutation and q-deformed anticommutation relations. 25 refs
GLq(N)-covariant quantum algebras and covariant differential calculus
International Nuclear Information System (INIS)
Isaev, A.P.; Pyatov, P.N.
1993-01-01
We consider GL q (N)-covariant quantum algebras with generators satisfying quadratic polynomial relations. We show that, up to some inessential arbitrariness, there are only two kinds of such quantum algebras, namely, the algebras with q-deformed commutation and q-deformed anticommutation relations. The connection with the bicovariant differential calculus on the linear quantum groups is discussed. (orig.)
A class of covariate-dependent spatiotemporal covariance functions
Reich, Brian J; Eidsvik, Jo; Guindani, Michele; Nail, Amy J; Schmidt, Alexandra M.
2014-01-01
In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. However, these assumptions are often untenable in practice because of the influence of local effects in the correlation structure. Therefore, it has been of prolonged interest in the literature to provide flexible and effective ways to model non-stationarity in the spatial effects. Arguably, due to the local nature of the problem, we might envision that the correlation structure would be highly dependent on local characteristics of the domain of study, namely the latitude, longitude and altitude of the observation sites, as well as other locally defined covariate information. In this work, we provide a flexible and computationally feasible way for allowing the correlation structure of the underlying processes to depend on local covariate information. We discuss the properties of the induced covariance functions and discuss methods to assess its dependence on local covariate information by means of a simulation study and the analysis of data observed at ozone-monitoring stations in the Southeast United States. PMID:24772199
Cosmic censorship conjecture revisited: covariantly
International Nuclear Information System (INIS)
Hamid, Aymen I M; Goswami, Rituparno; Maharaj, Sunil D
2014-01-01
In this paper we study the dynamics of the trapped region using a frame independent semi-tetrad covariant formalism for general locally rotationally symmetric (LRS) class II spacetimes. We covariantly prove some important geometrical results for the apparent horizon, and state the necessary and sufficient conditions for a singularity to be locally naked. These conditions bring out, for the first time in a quantitative and transparent manner, the importance of the Weyl curvature in deforming and delaying the trapped region during continual gravitational collapse, making the central singularity locally visible. (paper)
Altered structural covariance of the striatum in functional dyspepsia patients.
Liu, P; Zeng, F; Yang, F; Wang, J; Liu, X; Wang, Q; Zhou, G; Zhang, D; Zhu, M; Zhao, R; Wang, A; Gong, Q; Liang, F
2014-08-01
Functional dyspepsia (FD) is thought to be involved in dysregulation within the brain-gut axis. Recently, altered striatum activation has been reported in patients with FD. However, the gray matter (GM) volumes in the striatum and structural covariance patterns of this area are rarely explored. The purpose of this study was to examine the GM volumes and structural covariance patterns of the striatum between FD patients and healthy controls (HCs). T1-weighted magnetic resonance images were obtained from 44 FD patients and 39 HCs. Voxel-based morphometry (VBM) analysis was adopted to examine the GM volumes in the two groups. The caudate- or putamen-related regions identified from VBM analysis were then used as seeds to map the whole brain voxel-wise structural covariance patterns. Finally, a correlation analysis was used to investigate the effects of FD symptoms on the striatum. The results showed increased GM volumes in the bilateral putamen and right caudate. Compared with the structural covariance patterns of the HCs, the FD-related differences were mainly located in the amygdala, hippocampus/parahippocampus (HIPP/paraHIPP), thalamus, lingual gyrus, and cerebellum. And significant positive correlations were found between the volumes in the striatum and the FD duration in the patients. These findings provided preliminary evidence for GM changes in the striatum and different structural covariance patterns in patients with FD. The current results might expand our understanding of the pathophysiology of FD. © 2014 John Wiley & Sons Ltd.
Covariance matrix estimation for stationary time series
Xiao, Han; Wu, Wei Biao
2011-01-01
We obtain a sharp convergence rate for banded covariance matrix estimates of stationary processes. A precise order of magnitude is derived for spectral radius of sample covariance matrices. We also consider a thresholded covariance matrix estimator that can better characterize sparsity if the true covariance matrix is sparse. As our main tool, we implement Toeplitz [Math. Ann. 70 (1911) 351–376] idea and relate eigenvalues of covariance matrices to the spectral densities or Fourier transforms...
Condition Number Regularized Covariance Estimation.
Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
2013-06-01
Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n " setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.
Condition Number Regularized Covariance Estimation*
Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
2012-01-01
Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197
Covariant Gauss law commutator anomaly
International Nuclear Information System (INIS)
Dunne, G.V.; Trugenberger, C.A.; Massachusetts Inst. of Tech., Cambridge
1990-01-01
Using a (fixed-time) hamiltonian formalism we derive a covariant form for the anomaly in the commutator algebra of Gauss law generators for chiral fermions interacting with a dynamical non-abelian gauge field in 3+1 dimensions. (orig.)
Covariant gauges for constrained systems
International Nuclear Information System (INIS)
Gogilidze, S.A.; Khvedelidze, A.M.; Pervushin, V.N.
1995-01-01
The method of constructing of extended phase space for singular theories which permits the consideration of covariant gauges without the introducing of a ghost fields, is proposed. The extension of the phase space is carried out by the identification of the initial theory with an equivalent theory with higher derivatives and applying to it the Ostrogradsky method of Hamiltonian description. 7 refs
Uncertainty covariances in robotics applications
International Nuclear Information System (INIS)
Smith, D.L.
1984-01-01
The application of uncertainty covariance matrices in the analysis of robot trajectory errors is explored. First, relevant statistical concepts are reviewed briefly. Then, a simple, hypothetical robot model is considered to illustrate methods for error propagation and performance test data evaluation. The importance of including error correlations is emphasized
Group covariance and metrical theory
International Nuclear Information System (INIS)
Halpern, L.
1983-01-01
The a priori introduction of a Lie group of transformations into a physical theory has often proved to be useful; it usually serves to describe special simplified conditions before a general theory can be worked out. Newton's assumptions of absolute space and time are examples where the Euclidian group and translation group have been introduced. These groups were extended to the Galilei group and modified in the special theory of relativity to the Poincare group to describe physics under the given conditions covariantly in the simplest way. The criticism of the a priori character leads to the formulation of the general theory of relativity. The general metric theory does not really give preference to a particular invariance group - even the principle of equivalence can be adapted to a whole family of groups. The physical laws covariantly inserted into the metric space are however adapted to the Poincare group. 8 references
Phenotypic covariance at species' borders.
Caley, M Julian; Cripps, Edward; Game, Edward T
2013-05-28
Understanding the evolution of species limits is important in ecology, evolution, and conservation biology. Despite its likely importance in the evolution of these limits, little is known about phenotypic covariance in geographically marginal populations, and the degree to which it constrains, or facilitates, responses to selection. We investigated phenotypic covariance in morphological traits at species' borders by comparing phenotypic covariance matrices (P), including the degree of shared structure, the distribution of strengths of pair-wise correlations between traits, the degree of morphological integration of traits, and the ranks of matricies, between central and marginal populations of three species-pairs of coral reef fishes. Greater structural differences in P were observed between populations close to range margins and conspecific populations toward range centres, than between pairs of conspecific populations that were both more centrally located within their ranges. Approximately 80% of all pair-wise trait correlations within populations were greater in the north, but these differences were unrelated to the position of the sampled population with respect to the geographic range of the species. Neither the degree of morphological integration, nor ranks of P, indicated greater evolutionary constraint at range edges. Characteristics of P observed here provide no support for constraint contributing to the formation of these species' borders, but may instead reflect structural change in P caused by selection or drift, and their potential to evolve in the future.
Modeling Covariance Breakdowns in Multivariate GARCH
Jin, Xin; Maheu, John M
2014-01-01
This paper proposes a flexible way of modeling dynamic heterogeneous covariance breakdowns in multivariate GARCH (MGARCH) models. During periods of normal market activity, volatility dynamics are governed by an MGARCH specification. A covariance breakdown is any significant temporary deviation of the conditional covariance matrix from its implied MGARCH dynamics. This is captured through a flexible stochastic component that allows for changes in the conditional variances, covariances and impl...
Proofs of Contracted Length Non-covariance
International Nuclear Information System (INIS)
Strel'tsov, V.N.
1994-01-01
Different proofs of contracted length non covariance are discussed. The way based on the establishment of interval inconstancy (dependence on velocity) seems to be the most convincing one. It is stressed that the known non covariance of the electromagnetic field energy and momentum of a moving charge ('the problem 4/3') is a direct consequence of contracted length non covariance. 8 refs
Structural Analysis of Covariance and Correlation Matrices.
Joreskog, Karl G.
1978-01-01
A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…
Construction of covariance matrix for experimental data
International Nuclear Information System (INIS)
Liu Tingjin; Zhang Jianhua
1992-01-01
For evaluators and experimenters, the information is complete only in the case when the covariance matrix is given. The covariance matrix of the indirectly measured data has been constructed and discussed. As an example, the covariance matrix of 23 Na(n, 2n) cross section is constructed. A reasonable result is obtained
Lorentz covariant theory of gravitation
International Nuclear Information System (INIS)
Fagundes, H.V.
1974-12-01
An alternative method for the calculation of second order effects, like the secular shift of Mercury's perihelium is developed. This method uses the basic ideas of thirring combined with the more mathematical approach of Feyman. In the case of a static source, the treatment used is greatly simplified. Besides, Einstein-Infeld-Hoffmann's Lagrangian for a system of two particles and spin-orbit and spin-spin interactions of two particles with classical spin, ie, internal angular momentum in Moller's sense, are obtained from the Lorentz covariant theory
International Nuclear Information System (INIS)
Sebestyen, A.
1975-07-01
The principle of covariance is extended to coordinates corresponding to internal degrees of freedom. The conditions for a system to be isolated are given. It is shown how internal forces arise in such systems. Equations for internal fields are derived. By an interpretation of the generalized coordinates based on group theory it is shown how particles of the ordinary sense enter into the model and as a simple application the gravitational interaction of two pointlike particles is considered and the shift of the perihelion is deduced. (Sz.Z.)
Covariant gauges at finite temperature
Landshoff, Peter V
1992-01-01
A prescription is presented for real-time finite-temperature perturbation theory in covariant gauges, in which only the two physical degrees of freedom of the gauge-field propagator acquire thermal parts. The propagators for the unphysical degrees of freedom of the gauge field, and for the Faddeev-Popov ghost field, are independent of temperature. This prescription is applied to the calculation of the one-loop gluon self-energy and the two-loop interaction pressure, and is found to be simpler to use than the conventional one.
Covariance Evaluation Methodology for Neutron Cross Sections
Energy Technology Data Exchange (ETDEWEB)
Herman,M.; Arcilla, R.; Mattoon, C.M.; Mughabghab, S.F.; Oblozinsky, P.; Pigni, M.; Pritychenko, b.; Songzoni, A.A.
2008-09-01
We present the NNDC-BNL methodology for estimating neutron cross section covariances in thermal, resolved resonance, unresolved resonance and fast neutron regions. The three key elements of the methodology are Atlas of Neutron Resonances, nuclear reaction code EMPIRE, and the Bayesian code implementing Kalman filter concept. The covariance data processing, visualization and distribution capabilities are integral components of the NNDC methodology. We illustrate its application on examples including relatively detailed evaluation of covariances for two individual nuclei and massive production of simple covariance estimates for 307 materials. Certain peculiarities regarding evaluation of covariances for resolved resonances and the consistency between resonance parameter uncertainties and thermal cross section uncertainties are also discussed.
Poincare covariance and κ-Minkowski spacetime
International Nuclear Information System (INIS)
Dabrowski, Ludwik; Piacitelli, Gherardo
2011-01-01
A fully Poincare covariant model is constructed as an extension of the κ-Minkowski spacetime. Covariance is implemented by a unitary representation of the Poincare group, and thus complies with the original Wigner approach to quantum symmetries. This provides yet another example (besides the DFR model), where Poincare covariance is realised a la Wigner in the presence of two characteristic dimensionful parameters: the light speed and the Planck length. In other words, a Doubly Special Relativity (DSR) framework may well be realised without deforming the meaning of 'Poincare covariance'. -- Highlights: → We construct a 4d model of noncommuting coordinates (quantum spacetime). → The coordinates are fully covariant under the undeformed Poincare group. → Covariance a la Wigner holds in presence of two dimensionful parameters. → Hence we are not forced to deform covariance (e.g. as quantum groups). → The underlying κ-Minkowski model is unphysical; covariantisation does not cure this.
COVARIANCE ASSISTED SCREENING AND ESTIMATION.
Ke, By Tracy; Jin, Jiashun; Fan, Jianqing
2014-11-01
Consider a linear model Y = X β + z , where X = X n,p and z ~ N (0, I n ). The vector β is unknown and it is of interest to separate its nonzero coordinates from the zero ones (i.e., variable selection). Motivated by examples in long-memory time series (Fan and Yao, 2003) and the change-point problem (Bhattacharya, 1994), we are primarily interested in the case where the Gram matrix G = X ' X is non-sparse but sparsifiable by a finite order linear filter. We focus on the regime where signals are both rare and weak so that successful variable selection is very challenging but is still possible. We approach this problem by a new procedure called the Covariance Assisted Screening and Estimation (CASE). CASE first uses a linear filtering to reduce the original setting to a new regression model where the corresponding Gram (covariance) matrix is sparse. The new covariance matrix induces a sparse graph, which guides us to conduct multivariate screening without visiting all the submodels. By interacting with the signal sparsity, the graph enables us to decompose the original problem into many separated small-size subproblems (if only we know where they are!). Linear filtering also induces a so-called problem of information leakage , which can be overcome by the newly introduced patching technique. Together, these give rise to CASE, which is a two-stage Screen and Clean (Fan and Song, 2010; Wasserman and Roeder, 2009) procedure, where we first identify candidates of these submodels by patching and screening , and then re-examine each candidate to remove false positives. For any procedure β̂ for variable selection, we measure the performance by the minimax Hamming distance between the sign vectors of β̂ and β. We show that in a broad class of situations where the Gram matrix is non-sparse but sparsifiable, CASE achieves the optimal rate of convergence. The results are successfully applied to long-memory time series and the change-point model.
Non-Critical Covariant Superstrings
Grassi, P A
2005-01-01
We construct a covariant description of non-critical superstrings in even dimensions. We construct explicitly supersymmetric hybrid type variables in a linear dilaton background, and study an underlying N=2 twisted superconformal algebra structure. We find similarities between non-critical superstrings in 2n+2 dimensions and critical superstrings compactified on CY_(4-n) manifolds. We study the spectrum of the non-critical strings, and in particular the Ramond-Ramond massless fields. We use the supersymmetric variables to construct the non-critical superstrings sigma-model action in curved target space backgrounds with coupling to the Ramond-Ramond fields. We consider as an example non-critical type IIA strings on AdS_2 background with Ramond-Ramond 2-form flux.
ISSUES IN NEUTRON CROSS SECTION COVARIANCES
Energy Technology Data Exchange (ETDEWEB)
Mattoon, C.M.; Oblozinsky,P.
2010-04-30
We review neutron cross section covariances in both the resonance and fast neutron regions with the goal to identify existing issues in evaluation methods and their impact on covariances. We also outline ideas for suitable covariance quality assurance procedures.We show that the topic of covariance data remains controversial, the evaluation methodologies are not fully established and covariances produced by different approaches have unacceptable spread. The main controversy is in very low uncertainties generated by rigorous evaluation methods and much larger uncertainties based on simple estimates from experimental data. Since the evaluators tend to trust the former, while the users tend to trust the latter, this controversy has considerable practical implications. Dedicated effort is needed to arrive at covariance evaluation methods that would resolve this issue and produce results accepted internationally both by evaluators and users.
Covariant diagrams for one-loop matching
Energy Technology Data Exchange (ETDEWEB)
Zhang, Zhengkang [Michigan Center for Theoretical Physics (MCTP), University of Michigan,450 Church Street, Ann Arbor, MI 48109 (United States); Deutsches Elektronen-Synchrotron (DESY),Notkestraße 85, 22607 Hamburg (Germany)
2017-05-30
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariant diagrams for one-loop matching
International Nuclear Information System (INIS)
Zhang, Zhengkang
2017-01-01
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Improvement of covariance data for fast reactors
International Nuclear Information System (INIS)
Shibata, Keiichi; Hasegawa, Akira
2000-02-01
We estimated covariances of the JENDL-3.2 data on the nuclides and reactions needed to analyze fast-reactor cores for the past three years, and produced covariance files. The present work was undertaken to re-examine the covariance files and to make some improvements. The covariances improved are the ones for the inelastic scattering cross section of 16 O, the total cross section of 23 Na, the fission cross section of 235 U, the capture cross section of 238 U, and the resolved resonance parameters for 238 U. Moreover, the covariances of 233 U data were newly estimated by the present work. The covariances obtained were compiled in the ENDF-6 format. (author)
ANL Critical Assembly Covariance Matrix Generation - Addendum
Energy Technology Data Exchange (ETDEWEB)
McKnight, Richard D. [Argonne National Lab. (ANL), Argonne, IL (United States); Grimm, Karl N. [Argonne National Lab. (ANL), Argonne, IL (United States)
2014-01-13
In March 2012, a report was issued on covariance matrices for Argonne National Laboratory (ANL) critical experiments. That report detailed the theory behind the calculation of covariance matrices and the methodology used to determine the matrices for a set of 33 ANL experimental set-ups. Since that time, three new experiments have been evaluated and approved. This report essentially updates the previous report by adding in these new experiments to the preceding covariance matrix structure.
Neutron spectrum adjustment. The role of covariances
International Nuclear Information System (INIS)
Remec, I.
1992-01-01
Neutron spectrum adjustment method is shortly reviewed. Practical example dealing with power reactor pressure vessel exposure rates determination is analysed. Adjusted exposure rates are found only slightly affected by the covariances of measured reaction rates and activation cross sections, while the multigroup spectra covariances were found important. Approximate spectra covariance matrices, as suggested in Astm E944-89, were found useful but care is advised if they are applied in adjustments of spectra at locations without dosimetry. (author) [sl
Modifications of Sp(2) covariant superfield quantization
Energy Technology Data Exchange (ETDEWEB)
Gitman, D.M.; Moshin, P.Yu
2003-12-04
We propose a modification of the Sp(2) covariant superfield quantization to realize a superalgebra of generating operators isomorphic to the massless limit of the corresponding superalgebra of the osp(1,2) covariant formalism. The modified scheme ensures the compatibility of the superalgebra of generating operators with extended BRST symmetry without imposing restrictions eliminating superfield components from the quantum action. The formalism coincides with the Sp(2) covariant superfield scheme and with the massless limit of the osp(1,2) covariant quantization in particular cases of gauge-fixing and solutions of the quantum master equations.
Competing risks and time-dependent covariates
DEFF Research Database (Denmark)
Cortese, Giuliana; Andersen, Per K
2010-01-01
Time-dependent covariates are frequently encountered in regression analysis for event history data and competing risks. They are often essential predictors, which cannot be substituted by time-fixed covariates. This study briefly recalls the different types of time-dependent covariates......, as classified by Kalbfleisch and Prentice [The Statistical Analysis of Failure Time Data, Wiley, New York, 2002] with the intent of clarifying their role and emphasizing the limitations in standard survival models and in the competing risks setting. If random (internal) time-dependent covariates...
Activities of covariance utilization working group
International Nuclear Information System (INIS)
Tsujimoto, Kazufumi
2013-01-01
During the past decade, there has been a interest in the calculational uncertainties induced by nuclear data uncertainties in the neutronics design of advanced nuclear system. The covariance nuclear data is absolutely essential for the uncertainty analysis. In the latest version of JENDL, JENDL-4.0, the covariance data for many nuclides, especially actinide nuclides, was substantialy enhanced. The growing interest in the uncertainty analysis and the covariance data has led to the organisation of the working group for covariance utilization under the JENDL committee. (author)
General covariance and quantum theory
International Nuclear Information System (INIS)
Mashhoon, B.
1986-01-01
The extension of the principle of relativity to general coordinate systems is based on the hypothesis that an accelerated observer is locally equivalent to a hypothetical inertial observer with the same velocity as the noninertial observer. This hypothesis of locality is expected to be valid for classical particle phenomena as well as for classical wave phenomena but only in the short-wavelength approximation. The generally covariant theory is therefore expected to be in conflict with the quantum theory which is based on wave-particle duality. This is explicitly demonstrated for the frequency of electromagnetic radiation measured by a uniformly rotating observer. The standard Doppler formula is shown to be valid only in the geometric optics approximation. A new definition for the frequency is proposed, and the resulting formula for the frequency measured by the rotating observer is shown to be consistent with expectations based on the classical theory of electrons. A tentative quantum theory is developed on the basis of the generalization of the Bohr frequency condition to include accelerated observers. The description of the causal sequence of events is assumed to be independent of the motion of the observer. Furthermore, the quantum hypothesis is supposed to be valid for all observers. The implications of this theory are critically examined. The new formula for frequency, which is still based on the hypothesis of locality, leads to the observation of negative energy quanta by the rotating observer and is therefore in conflict with the quantum theory
Parameters of the covariance function of galaxies
International Nuclear Information System (INIS)
Fesenko, B.I.; Onuchina, E.V.
1988-01-01
The two-point angular covariance functions for two samples of galaxies are considered using quick methods of analysis. It is concluded that in the previous investigations the amplitude of the covariance function in the Lick counts was overestimated and the rate of decrease of the function underestimated
Covariance Function for Nearshore Wave Assimilation Systems
2018-01-30
which is applicable for any spectral wave model. The four dimensional variational (4DVar) assimilation methods are based on the mathematical ...covariance can be modeled by a parameterized Gaussian function, for nearshore wave assimilation applications , the covariance function depends primarily on...SPECTRAL ACTION DENSITY, RESPECTIVELY. ............................ 5 FIGURE 2. TOP ROW: STATISTICAL ANALYSIS OF THE WAVE-FIELD PROPERTIES AT THE
Treatment Effects with Many Covariates and Heteroskedasticity
DEFF Research Database (Denmark)
Cattaneo, Matias D.; Jansson, Michael; Newey, Whitney K.
The linear regression model is widely used in empirical work in Economics. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroskedasticity. Our results...
Covariance and sensitivity data generation at ORNL
International Nuclear Information System (INIS)
Leal, L. C.; Derrien, H.; Larson, N. M.; Alpan, A.
2005-01-01
Covariance data are required to assess uncertainties in design parameters in several nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the US Evaluated Nuclear Data Library, ENDF/B. The uncertainty files in the ENDF/B library are obtained from the analysis of experimental data and are stored as variance and covariance data. In this paper we address the generation of covariance data in the resonance region done with the computer code SAMMY. SAMMY is used in the evaluation of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on the generalised least-squares formalism (Bayesian theory) together with the resonance formalism described by R-matrix theory. Two approaches are used in SAMMY for the generation of resonance parameter covariance data. In the evaluation process SAMMY generates a set of resonance parameters that fit the data, and, it provides the resonance parameter covariances. For resonance parameter evaluations where there are no resonance parameter covariance data available, the alternative is to use an approach called the 'retroactive' resonance parameter covariance generation. In this paper, we describe the application of the retroactive covariance generation approach for the gadolinium isotopes. (authors)
Position Error Covariance Matrix Validation and Correction
Frisbee, Joe, Jr.
2016-01-01
In order to calculate operationally accurate collision probabilities, the position error covariance matrices predicted at times of closest approach must be sufficiently accurate representations of the position uncertainties. This presentation will discuss why the Gaussian distribution is a reasonable expectation for the position uncertainty and how this assumed distribution type is used in the validation and correction of position error covariance matrices.
Quality Quantification of Evaluated Cross Section Covariances
International Nuclear Information System (INIS)
Varet, S.; Dossantos-Uzarralde, P.; Vayatis, N.
2015-01-01
Presently, several methods are used to estimate the covariance matrix of evaluated nuclear cross sections. Because the resulting covariance matrices can be different according to the method used and according to the assumptions of the method, we propose a general and objective approach to quantify the quality of the covariance estimation for evaluated cross sections. The first step consists in defining an objective criterion. The second step is computation of the criterion. In this paper the Kullback-Leibler distance is proposed for the quality quantification of a covariance matrix estimation and its inverse. It is based on the distance to the true covariance matrix. A method based on the bootstrap is presented for the estimation of this criterion, which can be applied with most methods for covariance matrix estimation and without the knowledge of the true covariance matrix. The full approach is illustrated on the 85 Rb nucleus evaluations and the results are then used for a discussion on scoring and Monte Carlo approaches for covariance matrix estimation of the cross section evaluations
On the algebraic structure of covariant anomalies and covariant Schwinger terms
International Nuclear Information System (INIS)
Kelnhofer, G.
1992-01-01
A cohomological characterization of covariant anomalies and covariant Schwinger terms in an anomalous Yang-Mills theory is formulated and w ill be geometrically interpreted. The BRS and anti-BRS transformations are defined as purely differential geometric objects. Finally the covariant descent equations are formulated within this context. (author)
Covariant diagrams for one-loop matching
International Nuclear Information System (INIS)
Zhang, Zhengkang
2016-10-01
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariant diagrams for one-loop matching
Energy Technology Data Exchange (ETDEWEB)
Zhang, Zhengkang [Michigan Univ., Ann Arbor, MI (United States). Michigan Center for Theoretical Physics; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
2016-10-15
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
On estimating cosmology-dependent covariance matrices
International Nuclear Information System (INIS)
Morrison, Christopher B.; Schneider, Michael D.
2013-01-01
We describe a statistical model to estimate the covariance matrix of matter tracer two-point correlation functions with cosmological simulations. Assuming a fixed number of cosmological simulation runs, we describe how to build a 'statistical emulator' of the two-point function covariance over a specified range of input cosmological parameters. Because the simulation runs with different cosmological models help to constrain the form of the covariance, we predict that the cosmology-dependent covariance may be estimated with a comparable number of simulations as would be needed to estimate the covariance for fixed cosmology. Our framework is a necessary first step in planning a simulations campaign for analyzing the next generation of cosmological surveys
Covariance descriptor fusion for target detection
Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih
2016-05-01
Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.
Covariant quantizations in plane and curved spaces
International Nuclear Information System (INIS)
Assirati, J.L.M.; Gitman, D.M.
2017-01-01
We present covariant quantization rules for nonsingular finite-dimensional classical theories with flat and curved configuration spaces. In the beginning, we construct a family of covariant quantizations in flat spaces and Cartesian coordinates. This family is parametrized by a function ω(θ), θ element of (1,0), which describes an ambiguity of the quantization. We generalize this construction presenting covariant quantizations of theories with flat configuration spaces but already with arbitrary curvilinear coordinates. Then we construct a so-called minimal family of covariant quantizations for theories with curved configuration spaces. This family of quantizations is parametrized by the same function ω(θ). Finally, we describe a more wide family of covariant quantizations in curved spaces. This family is already parametrized by two functions, the previous one ω(θ) and by an additional function Θ(x,ξ). The above mentioned minimal family is a part at Θ = 1 of the wide family of quantizations. We study constructed quantizations in detail, proving their consistency and covariance. As a physical application, we consider a quantization of a non-relativistic particle moving in a curved space, discussing the problem of a quantum potential. Applying the covariant quantizations in flat spaces to an old problem of constructing quantum Hamiltonian in polar coordinates, we directly obtain a correct result. (orig.)
Covariant quantizations in plane and curved spaces
Energy Technology Data Exchange (ETDEWEB)
Assirati, J.L.M. [University of Sao Paulo, Institute of Physics, Sao Paulo (Brazil); Gitman, D.M. [Tomsk State University, Department of Physics, Tomsk (Russian Federation); P.N. Lebedev Physical Institute, Moscow (Russian Federation); University of Sao Paulo, Institute of Physics, Sao Paulo (Brazil)
2017-07-15
We present covariant quantization rules for nonsingular finite-dimensional classical theories with flat and curved configuration spaces. In the beginning, we construct a family of covariant quantizations in flat spaces and Cartesian coordinates. This family is parametrized by a function ω(θ), θ element of (1,0), which describes an ambiguity of the quantization. We generalize this construction presenting covariant quantizations of theories with flat configuration spaces but already with arbitrary curvilinear coordinates. Then we construct a so-called minimal family of covariant quantizations for theories with curved configuration spaces. This family of quantizations is parametrized by the same function ω(θ). Finally, we describe a more wide family of covariant quantizations in curved spaces. This family is already parametrized by two functions, the previous one ω(θ) and by an additional function Θ(x,ξ). The above mentioned minimal family is a part at Θ = 1 of the wide family of quantizations. We study constructed quantizations in detail, proving their consistency and covariance. As a physical application, we consider a quantization of a non-relativistic particle moving in a curved space, discussing the problem of a quantum potential. Applying the covariant quantizations in flat spaces to an old problem of constructing quantum Hamiltonian in polar coordinates, we directly obtain a correct result. (orig.)
Students’ Covariational Reasoning in Solving Integrals’ Problems
Harini, N. V.; Fuad, Y.; Ekawati, R.
2018-01-01
Covariational reasoning plays an important role to indicate quantities vary in learning calculus. This study investigates students’ covariational reasoning during their studies concerning two covarying quantities in integral problem. Six undergraduate students were chosen to solve problems that involved interpreting and representing how quantities change in tandem. Interviews were conducted to reveal the students’ reasoning while solving covariational problems. The result emphasizes that undergraduate students were able to construct the relation of dependent variables that changes in tandem with the independent variable. However, students faced difficulty in forming images of continuously changing rates and could not accurately apply the concept of integrals. These findings suggest that learning calculus should be increased emphasis on coordinating images of two quantities changing in tandem about instantaneously rate of change and to promote conceptual knowledge in integral techniques.
Covariant Quantization with Extended BRST Symmetry
Geyer, B.; Gitman, D. M.; Lavrov, P. M.
1999-01-01
A short rewiev of covariant quantization methods based on BRST-antiBRST symmetry is given. In particular problems of correct definition of Sp(2) symmetric quantization scheme known as triplectic quantization are considered.
Covariant extensions and the nonsymmetric unified field
International Nuclear Information System (INIS)
Borchsenius, K.
1976-01-01
The problem of generally covariant extension of Lorentz invariant field equations, by means of covariant derivatives extracted from the nonsymmetric unified field, is considered. It is shown that the contracted curvature tensor can be expressed in terms of a covariant gauge derivative which contains the gauge derivative corresponding to minimal coupling, if the universal constant p, characterizing the nonsymmetric theory, is fixed in terms of Planck's constant and the elementary quantum of charge. By this choice the spinor representation of the linear connection becomes closely related to the spinor affinity used by Infeld and Van Der Waerden (Sitzungsber. Preuss. Akad. Wiss. Phys. Math. Kl.; 9:380 (1933)) in their generally covariant formulation of Dirac's equation. (author)
Covariance Spectroscopy for Fissile Material Detection
International Nuclear Information System (INIS)
Trainham, Rusty; Tinsley, Jim; Hurley, Paul; Keegan, Ray
2009-01-01
Nuclear fission produces multiple prompt neutrons and gammas at each fission event. The resulting daughter nuclei continue to emit delayed radiation as neutrons boil off, beta decay occurs, etc. All of the radiations are causally connected, and therefore correlated. The correlations are generally positive, but when different decay channels compete, so that some radiations tend to exclude others, negative correlations could also be observed. A similar problem of reduced complexity is that of cascades radiation, whereby a simple radioactive decay produces two or more correlated gamma rays at each decay. Covariance is the usual means for measuring correlation, and techniques of covariance mapping may be useful to produce distinct signatures of special nuclear materials (SNM). A covariance measurement can also be used to filter data streams because uncorrelated signals are largely rejected. The technique is generally more effective than a coincidence measurement. In this poster, we concentrate on cascades and the covariance filtering problem
Covariant amplitudes in Polyakov string theory
International Nuclear Information System (INIS)
Aoyama, H.; Dhar, A.; Namazie, M.A.
1986-01-01
A manifestly Lorentz-covariant and reparametrization-invariant procedure for computing string amplitudes using Polyakov's formulation is described. Both bosonic and superstring theories are dealt with. The computation of string amplitudes is greatly facilitated by this formalism. (orig.)
Covariance upperbound controllers for networked control systems
International Nuclear Information System (INIS)
Ko, Sang Ho
2012-01-01
This paper deals with designing covariance upperbound controllers for a linear system that can be used in a networked control environment in which control laws are calculated in a remote controller and transmitted through a shared communication link to the plant. In order to compensate for possible packet losses during the transmission, two different techniques are often employed: the zero-input and the hold-input strategy. These use zero input and the latest control input, respectively, when a packet is lost. For each strategy, we synthesize a class of output covariance upperbound controllers for a given covariance upperbound and a packet loss probability. Existence conditions of the covariance upperbound controller are also provided for each strategy. Through numerical examples, performance of the two strategies is compared in terms of feasibility of implementing the controllers
Forecasting Covariance Matrices: A Mixed Frequency Approach
DEFF Research Database (Denmark)
Halbleib, Roxana; Voev, Valeri
This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows for flexi......This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows...... for flexible dependence patterns for volatilities and correlations, and can be applied to covariance matrices of large dimensions. The separate modeling of volatility and correlation forecasts considerably reduces the estimation and measurement error implied by the joint estimation and modeling of covariance...
Covariance data evaluation for experimental data
International Nuclear Information System (INIS)
Liu Tingjin
1993-01-01
Some methods and codes have been developed and utilized for covariance data evaluation of experimental data, including parameter analysis, physical analysis, Spline fitting etc.. These methods and codes can be used in many different cases
Earth Observing System Covariance Realism Updates
Ojeda Romero, Juan A.; Miguel, Fred
2017-01-01
This presentation will be given at the International Earth Science Constellation Mission Operations Working Group meetings June 13-15, 2017 to discuss the Earth Observing System Covariance Realism updates.
Laser Covariance Vibrometry for Unsymmetrical Mode Detection
National Research Council Canada - National Science Library
Kobold, Michael C
2006-01-01
Simulated cross - spectral covariance (CSC) from optical return from simulated surface vibration indicates CW phase modulation may be an appropriate phenomenology for adequate classification of vehicles by structural mode...
Error Covariance Estimation of Mesoscale Data Assimilation
National Research Council Canada - National Science Library
Xu, Qin
2005-01-01
The goal of this project is to explore and develop new methods of error covariance estimation that will provide necessary statistical descriptions of prediction and observation errors for mesoscale data assimilation...
Heteroscedasticity resistant robust covariance matrix estimator
Czech Academy of Sciences Publication Activity Database
Víšek, Jan Ámos
2010-01-01
Roč. 17, č. 27 (2010), s. 33-49 ISSN 1212-074X Grant - others:GA UK(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10750506 Keywords : Regression * Covariance matrix * Heteroscedasticity * Resistant Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/SI/visek-heteroscedasticity resistant robust covariance matrix estimator.pdf
Phase-covariant quantum cloning of qudits
International Nuclear Information System (INIS)
Fan Heng; Imai, Hiroshi; Matsumoto, Keiji; Wang, Xiang-Bin
2003-01-01
We study the phase-covariant quantum cloning machine for qudits, i.e., the input states in a d-level quantum system have complex coefficients with arbitrary phase but constant module. A cloning unitary transformation is proposed. After optimizing the fidelity between input state and single qudit reduced density operator of output state, we obtain the optimal fidelity for 1 to 2 phase-covariant quantum cloning of qudits and the corresponding cloning transformation
Noncommutative Gauge Theory with Covariant Star Product
International Nuclear Information System (INIS)
Zet, G.
2010-01-01
We present a noncommutative gauge theory with covariant star product on a space-time with torsion. In order to obtain the covariant star product one imposes some restrictions on the connection of the space-time. Then, a noncommutative gauge theory is developed applying this product to the case of differential forms. Some comments on the advantages of using a space-time with torsion to describe the gravitational field are also given.
Covariant phase difference observables in quantum mechanics
International Nuclear Information System (INIS)
Heinonen, Teiko; Lahti, Pekka; Pellonpaeae, Juha-Pekka
2003-01-01
Covariant phase difference observables are determined in two different ways, by a direct computation and by a group theoretical method. A characterization of phase difference observables which can be expressed as the difference of two phase observables is given. The classical limits of such phase difference observables are determined and the Pegg-Barnett phase difference distribution is obtained from the phase difference representation. The relation of Ban's theory to the covariant phase theories is exhibited
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-07
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-05
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Covariate analysis of bivariate survival data
Energy Technology Data Exchange (ETDEWEB)
Bennett, L.E.
1992-01-01
The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methods have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul
2015-01-01
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul
2015-01-01
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Covariant perturbations of Schwarzschild black holes
International Nuclear Information System (INIS)
Clarkson, Chris A; Barrett, Richard K
2003-01-01
We present a new covariant and gauge-invariant perturbation formalism for dealing with spacetimes having spherical symmetry (or some preferred spatial direction) in the background, and apply it to the case of gravitational wave propagation in a Schwarzschild black-hole spacetime. The 1 + 3 covariant approach is extended to a '1 + 1 + 2 covariant sheet' formalism by introducing a radial unit vector in addition to the timelike congruence, and decomposing all covariant quantities with respect to this. The background Schwarzschild solution is discussed and a covariant characterization is given. We give the full first-order system of linearized 1 + 1 + 2 covariant equations, and we show how, by introducing (time and spherical) harmonic functions, these may be reduced to a system of first-order ordinary differential equations and algebraic constraints for the 1 + 1 + 2 variables which may be solved straightforwardly. We show how both odd- and even-parity perturbations may be unified by the discovery of a covariant, frame- and gauge-invariant, transverse-traceless tensor describing gravitational waves, which satisfies a covariant wave equation equivalent to the Regge-Wheeler equation for both even- and odd-parity perturbations. We show how the Zerilli equation may be derived from this tensor, and derive a similar transverse-traceless tensor equation equivalent to this equation. The so-called special quasinormal modes with purely imaginary frequency emerge naturally. The significance of the degrees of freedom in the choice of the two frame vectors is discussed, and we demonstrate that, for a certain frame choice, the underlying dynamics is governed purely by the Regge-Wheeler tensor. The two transverse-traceless Weyl tensors which carry the curvature of gravitational waves are discussed, and we give the closed system of four first-order ordinary differential equations describing their propagation. Finally, we consider the extension of this work to the study of
Covariance J-resolved spectroscopy: Theory and application in vivo.
Iqbal, Zohaib; Verma, Gaurav; Kumar, Anand; Thomas, M Albert
2017-08-01
Magnetic resonance spectroscopy (MRS) is a powerful tool capable of investigating the metabolic status of several tissues in vivo. In particular, single-voxel-based 1 H spectroscopy provides invaluable biochemical information from a volume of interest (VOI) and has therefore been used in a variety of studies. Unfortunately, typical one-dimensional MRS data suffer from severe signal overlap and thus important metabolites are difficult to distinguish. One method that is used to disentangle overlapping resonances is the two-dimensional J-resolved spectroscopy (JPRESS) experiment. Due to the long acquisition duration of the JPRESS experiment, a limited number of points are acquired in the indirect dimension, leading to poor spectral resolution along this dimension. Poor spectral resolution is problematic because proper peak assignment may be hindered, which is why the zero-filling method is often used to improve resolution as a post-processing step. However, zero-filling leads to spectral artifacts, which may affect visualization and quantitation of spectra. A novel method utilizing a covariance transformation, called covariance J-resolved spectroscopy (CovJ), was developed in order to improve spectral resolution along the indirect dimension (F 1 ). Comparison of simulated data demonstrates that peak structures remain qualitatively similar between JPRESS and the novel method along the diagonal region (F 1 = 0 Hz), whereas differences arise in the cross-peak (F 1 ≠0 Hz) regions. In addition, quantitative results of in vivo JPRESS data acquired on a 3T scanner show significant correlations (r 2 >0.86, pCOVariance Spectral Evaluation of 1 H Acquisitions using Representative prior knowledge' (Cov-SEHAR), was developed in order to quantify γ-aminobutyric acid and glutamate from the CovJ spectra. These preliminary findings indicate that the CovJ method may be used to improve spectral resolution without hindering metabolite quantitation for J-resolved spectra
Ole E. Barndorff-Nielsen; Neil Shephard
2002-01-01
This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...
A special covariance structure for random coefficient models with both between and within covariates
International Nuclear Information System (INIS)
Riedel, K.S.
1990-07-01
We review random coefficient (RC) models in linear regression and propose a bias correction to the maximum likelihood (ML) estimator. Asymmptotic expansion of the ML equations are given when the between individual variance is much larger or smaller than the variance from within individual fluctuations. The standard model assumes all but one covariate varies within each individual, (we denote the within covariates by vector χ 1 ). We consider random coefficient models where some of the covariates do not vary in any single individual (we denote the between covariates by vector χ 0 ). The regression coefficients, vector β k , can only be estimated in the subspace X k of X. Thus the number of individuals necessary to estimate vector β and the covariance matrix Δ of vector β increases significantly in the presence of more than one between covariate. When the number of individuals is sufficient to estimate vector β but not the entire matrix Δ , additional assumptions must be imposed on the structure of Δ. A simple reduced model is that the between component of vector β is fixed and only the within component varies randomly. This model fails because it is not invariant under linear coordinate transformations and it can significantly overestimate the variance of new observations. We propose a covariance structure for Δ without these difficulties by first projecting the within covariates onto the space perpendicular to be between covariates. (orig.)
Are your covariates under control? How normalization can re-introduce covariate effects.
Pain, Oliver; Dudbridge, Frank; Ronald, Angelica
2018-04-30
Many statistical tests rely on the assumption that the residuals of a model are normally distributed. Rank-based inverse normal transformation (INT) of the dependent variable is one of the most popular approaches to satisfy the normality assumption. When covariates are included in the analysis, a common approach is to first adjust for the covariates and then normalize the residuals. This study investigated the effect of regressing covariates against the dependent variable and then applying rank-based INT to the residuals. The correlation between the dependent variable and covariates at each stage of processing was assessed. An alternative approach was tested in which rank-based INT was applied to the dependent variable before regressing covariates. Analyses based on both simulated and real data examples demonstrated that applying rank-based INT to the dependent variable residuals after regressing out covariates re-introduces a linear correlation between the dependent variable and covariates, increasing type-I errors and reducing power. On the other hand, when rank-based INT was applied prior to controlling for covariate effects, residuals were normally distributed and linearly uncorrelated with covariates. This latter approach is therefore recommended in situations were normality of the dependent variable is required.
Harden, Bradley J; Nichols, Scott R; Frueh, Dominique P
2014-09-24
Nuclear magnetic resonance (NMR) studies of larger proteins are hampered by difficulties in assigning NMR resonances. Human intervention is typically required to identify NMR signals in 3D spectra, and subsequent procedures depend on the accuracy of this so-called peak picking. We present a method that provides sequential connectivities through correlation maps constructed with covariance NMR, bypassing the need for preliminary peak picking. We introduce two novel techniques to minimize false correlations and merge the information from all original 3D spectra. First, we take spectral derivatives prior to performing covariance to emphasize coincident peak maxima. Second, we multiply covariance maps calculated with different 3D spectra to destroy erroneous sequential correlations. The maps are easy to use and can readily be generated from conventional triple-resonance experiments. Advantages of the method are demonstrated on a 37 kDa nonribosomal peptide synthetase domain subject to spectral overlap.
Nuclear data covariances in the Indian context
International Nuclear Information System (INIS)
Ganesan, S.
2014-01-01
The topic of covariances is recognized as an important part of several ongoing nuclear data science activities, since 2007, in the Nuclear Data Physics Centre of India (NDPCI). A Phase-1 project in collaboration with the Statistics department in Manipal University, Karnataka (Prof. K.M. Prasad and Prof. S. Nair) on nuclear data covariances was executed successfully during 2007-2011 period. In Phase-I, the NDPCI has conducted three national Theme meetings sponsored by the DAE-BRNS in 2008, 2010 and 2013 on nuclear data covariances. In Phase-1, the emphasis was on a thorough basic understanding of the concept of covariances including assigning uncertainties to experimental data in terms of partial errors and micro correlations, through a study and a detailed discussion of open literature. Towards the end of Phase-1, measurements and a first time covariance analysis of cross-sections for 58 Ni (n, p) 58 Co reaction measured in Mumbai Pelletron accelerator using 7 Li (p,n) reactions as neutron source in the MeV energy region were performed under a PhD programme on nuclear data covariances in which enrolled are two students, Shri B.S. Shivashankar and Ms. Shanti Sheela. India is also successfully evolving a team of young researchers to code nuclear data of uncertainties, with the perspectives on covariances, in the IAEA-EXFOR format. A Phase-II DAE-BRNS-NDPCI proposal of project at Manipal has been submitted and the proposal is undergoing a peer-review at this time. In Phase-2, modern nuclear data evaluation techniques that including covariances will be further studied as a research and development effort, as a first time effort. These efforts include the use of techniques such as that of the Kalman filter. Presently, a 48 hours lecture series on treatment of errors and their propagation is being formulated under auspices of the Homi Bhabha National Institute. The talk describes the progress achieved thus far in the learning curve of the above-mentioned and exciting
Review and Assessment of Neutron Cross Section and Nubar Covariances for Advanced Reactor Systems
Energy Technology Data Exchange (ETDEWEB)
Maslov,V.M.; Oblozinsky, P.; Herman, M.
2008-12-01
In January 2007, the National Nuclear Data Center (NNDC) produced a set of preliminary neutron covariance data for the international project 'Nuclear Data Needs for Advanced Reactor Systems'. The project was sponsored by the OECD Nuclear Energy Agency (NEA), Paris, under the Subgroup 26 of the International Working Party on Evaluation Cooperation (WPEC). These preliminary covariances are described in two recent BNL reports. The NNDC used a simplified version of the method developed by BNL and LANL that combines the recent Atlas of Neutron Resonances, the nuclear reaction model code EMPIRE and the Bayesian code KALMAN with the experimental data used as guidance. There are numerous issues involved in these estimates of covariances and it was decided to perform an independent review and assessment of these results so that better covariances can be produced for the revised version in future. Reviewed and assessed are uncertainties for fission, capture, elastic scattering, inelastic scattering and (n,2n) cross sections as well as prompt nubars for 15 minor actinides ({sup 233,234,236}U, {sup 237}Np, {sup 238,240,241,242}Pu, {sup 241,242m,243}Am and {sup 242,243,244,245}Cm) and 4 major actinides ({sup 232}Th, {sup 235,238}U and {sup 239}Pu). We examined available evaluations, performed comparison with experimental data, taken into account uncertainties in model parameterization and made use state-of-the-art nuclear reaction theory to produce the uncertainty assessment.
Cross-covariance functions for multivariate geostatistics
Genton, Marc G.
2015-05-01
Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
Schroedinger covariance states in anisotropic waveguides
International Nuclear Information System (INIS)
Angelow, A.; Trifonov, D.
1995-03-01
In this paper Squeezed and Covariance States based on Schroedinger inequality and their connection with other nonclassical states are considered for particular case of anisotropic waveguide in LiNiO 3 . Here, the problem of photon creation and generation of squeezed and Schroedinger covariance states in optical waveguides is solved in two steps: 1. Quantization of electromagnetic field is provided in the presence of dielectric waveguide using normal-mode expansion. The photon creation and annihilation operators are introduced, expanding the solution A-vector(r-vector,t) in a series in terms of the Sturm - Liouville mode-functions. 2. In terms of these operators the Hamiltonian of the field in a nonlinear waveguide is derived. For such Hamiltonian we construct the covariance states as stable (with nonzero covariance), which minimize the Schroedinger uncertainty relation. The evolutions of the three second momenta of q-circumflex j and p-circumflex j are calculated. For this Hamiltonian all three momenta are expressed in terms of one real parameters s only. It is found out how covariance, via this parameter s, depends on the waveguide profile n(x,y), on the mode-distributions u-vector j (x,y), and on the waveguide phase mismatching Δβ. (author). 37 refs
Form of the manifestly covariant Lagrangian
Johns, Oliver Davis
1985-10-01
The preferred form for the manifestly covariant Lagrangian function of a single, charged particle in a given electromagnetic field is the subject of some disagreement in the textbooks. Some authors use a ``homogeneous'' Lagrangian and others use a ``modified'' form in which the covariant Hamiltonian function is made to be nonzero. We argue in favor of the ``homogeneous'' form. We show that the covariant Lagrangian theories can be understood only if one is careful to distinguish quantities evaluated on the varied (in the sense of the calculus of variations) world lines from quantities evaluated on the unvaried world lines. By making this distinction, we are able to derive the Hamilton-Jacobi and Klein-Gordon equations from the ``homogeneous'' Lagrangian, even though the covariant Hamiltonian function is identically zero on all world lines. The derivation of the Klein-Gordon equation in particular gives Lagrangian theoretical support to the derivations found in standard quantum texts, and is also shown to be consistent with the Feynman path-integral method. We conclude that the ``homogeneous'' Lagrangian is a completely adequate basis for covariant Lagrangian theory both in classical and quantum mechanics. The article also explores the analogy with the Fermat theorem of optics, and illustrates a simple invariant notation for the Lagrangian and other four-vector equations.
Cross-covariance functions for multivariate geostatistics
Genton, Marc G.; Kleiber, William
2015-01-01
Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
Convex Banding of the Covariance Matrix.
Bien, Jacob; Bunea, Florentina; Xiao, Luo
2016-01-01
We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which tapers the sample covariance matrix by a Toeplitz, sparsely-banded, data-adaptive matrix. As a result of this adaptivity, the convex banding estimator enjoys theoretical optimality properties not attained by previous banding or tapered estimators. In particular, our convex banding estimator is minimax rate adaptive in Frobenius and operator norms, up to log factors, over commonly-studied classes of covariance matrices, and over more general classes. Furthermore, it correctly recovers the bandwidth when the true covariance is exactly banded. Our convex formulation admits a simple and efficient algorithm. Empirical studies demonstrate its practical effectiveness and illustrate that our exactly-banded estimator works well even when the true covariance matrix is only close to a banded matrix, confirming our theoretical results. Our method compares favorably with all existing methods, in terms of accuracy and speed. We illustrate the practical merits of the convex banding estimator by showing that it can be used to improve the performance of discriminant analysis for classifying sound recordings.
Progress on Nuclear Data Covariances: AFCI-1.2 Covariance Library
International Nuclear Information System (INIS)
Oblozinsky, P.; Oblozinsky, P.; Mattoon, C.M.; Herman, M.; Mughabghab, S.F.; Pigni, M.T.; Talou, P.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Young, P.G
2009-01-01
Improved neutron cross section covariances were produced for 110 materials including 12 light nuclei (coolants and moderators), 78 structural materials and fission products, and 20 actinides. Improved covariances were organized into AFCI-1.2 covariance library in 33-energy groups, from 10 -5 eV to 19.6 MeV. BNL contributed improved covariance data for the following materials: 23 Na and 55 Mn where more detailed evaluation was done; improvements in major structural materials 52 Cr, 56 Fe and 58 Ni; improved estimates for remaining structural materials and fission products; improved covariances for 14 minor actinides, and estimates of mubar covariances for 23 Na and 56 Fe. LANL contributed improved covariance data for 235 U and 239 Pu including prompt neutron fission spectra and completely new evaluation for 240 Pu. New R-matrix evaluation for 16 O including mubar covariances is under completion. BNL assembled the library and performed basic testing using improved procedures including inspection of uncertainty and correlation plots for each material. The AFCI-1.2 library was released to ANL and INL in August 2009.
ACORNS, Covariance and Correlation Matrix Diagonalization
International Nuclear Information System (INIS)
Szondi, E.J.
1990-01-01
1 - Description of program or function: The program allows the user to verify the different types of covariance/correlation matrices used in the activation neutron spectrometry. 2 - Method of solution: The program performs the diagonalization of the input covariance/relative covariance/correlation matrices. The Eigen values are then analyzed to determine the rank of the matrices. If the Eigen vectors of the pertinent correlation matrix have also been calculated, the program can perform a complete factor analysis (generation of the factor matrix and its rotation in Kaiser's 'varimax' sense to select the origin of the correlations). 3 - Restrictions on the complexity of the problem: Matrix size is limited to 60 on PDP and to 100 on IBM PC/AT
Group covariant protocols for quantum string commitment
International Nuclear Information System (INIS)
Tsurumaru, Toyohiro
2006-01-01
We study the security of quantum string commitment (QSC) protocols with group covariant encoding scheme. First we consider a class of QSC protocol, which is general enough to incorporate all the QSC protocols given in the preceding literatures. Then among those protocols, we consider group covariant protocols and show that the exact upperbound on the binding condition can be calculated. Next using this result, we prove that for every irreducible representation of a finite group, there always exists a corresponding nontrivial QSC protocol which reaches a level of security impossible to achieve classically
The covariant entropy bound in gravitational collapse
International Nuclear Information System (INIS)
Gao, Sijie; Lemos, Jose P. S.
2004-01-01
We study the covariant entropy bound in the context of gravitational collapse. First, we discuss critically the heuristic arguments advanced by Bousso. Then we solve the problem through an exact model: a Tolman-Bondi dust shell collapsing into a Schwarzschild black hole. After the collapse, a new black hole with a larger mass is formed. The horizon, L, of the old black hole then terminates at the singularity. We show that the entropy crossing L does not exceed a quarter of the area of the old horizon. Therefore, the covariant entropy bound is satisfied in this process. (author)
Modular invariance and covariant loop calculus
International Nuclear Information System (INIS)
Petersen, J.L.; Roland, K.O.; Sidenius, J.R.
1988-01-01
The covariant loop calculus provides and efficient technique for computing explicit expressions for the density on moduli space corresponding to arbitrary (bosonic string) loop diagrams. Since modular invariance is not manifest, however, we carry out a detailed comparison with known explicit 2- and 3- loop results derived using analytic geometry (1 loop is known to be ok). We establish identity to 'high' order in some moduli and exactly in others. Agreement is found as a result of various non-trivial cancellations, in part related to number theory. We feel our results provide very strong support for the correctness of the covariant loop calculus approach. (orig.)
Remarks on Bousso's covariant entropy bound
Mayo, A E
2002-01-01
Bousso's covariant entropy bound is put to the test in the context of a non-singular cosmological solution of general relativity found by Bekenstein. Although the model complies with every assumption made in Bousso's original conjecture, the entropy bound is violated due to the occurrence of negative energy density associated with the interaction of some the matter components in the model. We demonstrate how this property allows for the test model to 'elude' a proof of Bousso's conjecture which was given recently by Flanagan, Marolf and Wald. This corroborates the view that the covariant entropy bound should be applied only to stable systems for which every matter component carries positive energy density.
Modular invariance and covariant loop calculus
International Nuclear Information System (INIS)
Petersen, J.L.; Roland, K.O.; Sidenius, J.R.
1988-01-01
The covariant loop calculus provides an efficient technique for computing explicit expressions for the density on moduli space corresponding to arbitrary (bosonic string) loop diagrams. Since modular invariance is not manifest, however, we carry out a detailed comparison with known explicit two- and three-loop results derived using analytic geometry (one loop is known to be okay). We establish identity to 'high' order in some moduli and exactly in others. Agreement is found as a result of various nontrivial cancellations, in part related to number theory. We feel our results provide very strong support for the correctness of the covariant loop calculus approach. (orig.)
Covariant n2-plet mass formulas
International Nuclear Information System (INIS)
Davidson, A.
1979-01-01
Using a generalized internal symmetry group analogous to the Lorentz group, we have constructed a covariant n 2 -plet mass operator. This operator is built as a scalar matrix in the (n;n*) representation, and its SU(n) breaking parameters are identified as intrinsic boost ones. Its basic properties are: covariance, Hermiticity, positivity, charge conjugation, quark contents, and a self-consistent n 2 -1, 1 mixing. The GMO and the Okubo formulas are obtained by considering two different limits of the same generalized mass formula
Parametric number covariance in quantum chaotic spectra.
Vinayak; Kumar, Sandeep; Pandey, Akhilesh
2016-03-01
We study spectral parametric correlations in quantum chaotic systems and introduce the number covariance as a measure of such correlations. We derive analytic results for the classical random matrix ensembles using the binary correlation method and obtain compact expressions for the covariance. We illustrate the universality of this measure by presenting the spectral analysis of the quantum kicked rotors for the time-reversal invariant and time-reversal noninvariant cases. A local version of the parametric number variance introduced earlier is also investigated.
Activities on covariance estimation in Japanese Nuclear Data Committee
Energy Technology Data Exchange (ETDEWEB)
Shibata, Keiichi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1997-03-01
Described are activities on covariance estimation in the Japanese Nuclear Data Committee. Covariances are obtained from measurements by using the least-squares methods. A simultaneous evaluation was performed to deduce covariances of fission cross sections of U and Pu isotopes. A code system, KALMAN, is used to estimate covariances of nuclear model calculations from uncertainties in model parameters. (author)
Covariant canonical quantization of fields and Bohmian mechanics
International Nuclear Information System (INIS)
Nikolic, H.
2005-01-01
We propose a manifestly covariant canonical method of field quantization based on the classical De Donder-Weyl covariant canonical formulation of field theory. Owing to covariance, the space and time arguments of fields are treated on an equal footing. To achieve both covariance and consistency with standard non-covariant canonical quantization of fields in Minkowski spacetime, it is necessary to adopt a covariant Bohmian formulation of quantum field theory. A preferred foliation of spacetime emerges dynamically owing to a purely quantum effect. The application to a simple time-reparametrization invariant system and quantum gravity is discussed and compared with the conventional non-covariant Wheeler-DeWitt approach. (orig.)
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander; Genton, Marc G.; Sun, Ying
2015-01-01
We approximate large non-structured Matérn covariance matrices of size n×n in the H-matrix format with a log-linear computational cost and storage O(kn log n), where rank k ≪ n is a small integer. Applications are: spatial statistics, machine learning and image analysis, kriging and optimal design.
Zero curvature conditions and conformal covariance
International Nuclear Information System (INIS)
Akemann, G.; Grimm, R.
1992-05-01
Two-dimensional zero curvature conditions were investigated in detail, with special emphasis on conformal properties, and the appearance of covariant higher order differential operators constructed in terms of a projective connection was elucidated. The analysis is based on the Kostant decomposition of simple Lie algebras in terms of representations with respect to their 'principal' SL(2) subalgebra. (author) 27 refs
On superfield covariant quantization in general coordinates
International Nuclear Information System (INIS)
Gitman, D.M.; Moshin, P. Yu.; Tomazelli, J.L.
2005-01-01
We propose a natural extension of the BRST-antiBRST superfield covariant scheme in general coordinates. Thus, the coordinate dependence of the basic tensor fields and scalar density of the formalism is extended from the base supermanifold to the complete set of superfield variables. (orig.)
On superfield covariant quantization in general coordinates
Energy Technology Data Exchange (ETDEWEB)
Gitman, D.M. [Universidade de Sao Paulo, Instituto de Fisica, Sao Paulo, S.P (Brazil); Moshin, P. Yu. [Universidade de Sao Paulo, Instituto de Fisica, Sao Paulo, S.P (Brazil); Tomsk State Pedagogical University, Tomsk (Russian Federation); Tomazelli, J.L. [UNESP, Departamento de Fisica e Quimica, Campus de Guaratingueta (Brazil)
2005-12-01
We propose a natural extension of the BRST-antiBRST superfield covariant scheme in general coordinates. Thus, the coordinate dependence of the basic tensor fields and scalar density of the formalism is extended from the base supermanifold to the complete set of superfield variables. (orig.)
Covariant field theory of closed superstrings
International Nuclear Information System (INIS)
Siopsis, G.
1989-01-01
The authors construct covariant field theories of both type-II and heterotic strings. Toroidal compactification is also considered. The interaction vertices are based on Witten's vertex representing three strings interacting at the mid-point. For closed strings, the authors thus obtain a bilocal interaction
Conformally covariant composite operators in quantum chromodynamics
International Nuclear Information System (INIS)
Craigie, N.S.; Dobrev, V.K.; Todorov, I.T.
1983-03-01
Conformal covariance is shown to determine renormalization properties of composite operators in QCD and in the C 6 3 -model at the one-loop level. Its relevance to higher order (renormalization group improved) perturbative calculations in the short distance limit is also discussed. Light cone operator product expansions and spectral representations for wave functions in QCD are derived. (author)
Soft covariant gauges on the lattice
Energy Technology Data Exchange (ETDEWEB)
Henty, D.S.; Oliveira, O.; Parrinello, C.; Ryan, S. [Department of Physics and Astronomy, University of Edinburgh, Edinburgh EH9 3JZ, Scotland (UKQCD Collaboration)
1996-12-01
We present an exploratory study of a one-parameter family of covariant, nonperturbative lattice gauge-fixing conditions that can be implemented through a simple Monte Carlo algorithm. We demonstrate that at the numerical level the procedure is feasible, and as a first application we examine the gauge dependence of the gluon propagator. {copyright} {ital 1996 The American Physical Society.}
Covariant differential calculus on the quantum hyperplane
International Nuclear Information System (INIS)
Wess, J.
1991-01-01
We develop a differential calculus on the quantum hyperplane covariant with respect to the action of the quantum group GL q (n). This is a concrete example of noncommutative differential geometry. We describe the general constraints for a noncommutative differential calculus and verify that the example given here satisfies all these constraints. We also discuss briefly the integration over the quantum plane. (orig.)
Covariant single-hole optical potential
International Nuclear Information System (INIS)
Kam, J. de
1982-01-01
In this investigation a covariant optical potential model is constructed for scattering processes of mesons from nuclei in which the meson interacts repeatedly with one of the target nucleons. The nuclear binding interactions in the intermediate scattering state are consistently taken into account. In particular for pions and K - projectiles this is important in view of the strong energy dependence of the elementary projectile-nucleon amplitude. Furthermore, this optical potential satisfies unitarity and relativistic covariance. The starting point in our discussion is the three-body model for the optical potential. To obtain a practical covariant theory I formulate the three-body model as a relativistic quasi two-body problem. Expressions for the transition interactions and propagators in the quasi two-body equations are found by imposing the correct s-channel unitarity relations and by using dispersion integrals. This is done in such a way that the correct non-relativistic limit is obtained, avoiding clustering problems. Corrections to the quasi two-body treatment from the Pauli principle and the required ground-state exclusion are taken into account. The covariant equations that we arrive at are amenable to practical calculations. (orig.)
Nonlinear realization of general covariance group
International Nuclear Information System (INIS)
Hamamoto, Shinji
1979-01-01
The structure of the theory resulting from the nonlinear realization of general covariance group is analysed. We discuss the general form of free Lagrangian for Goldstone fields, and propose as a special choice one reasonable form which is shown to describe a gravitational theory with massless tensor graviton and massive vector tordion. (author)
Covariant quantum mechanics on a null plane
International Nuclear Information System (INIS)
Leutwyler, H.; Stern, J.
1977-03-01
Lorentz invariance implies that the null plane wave functions factorize into a kinematical part describing the motion of the system as a whole and an inner wave function that involves the specific dynamical properties of the system - in complete correspondence with the non-relativistic situation. Covariance is equivalent to an angular condition which admits non-trivial solutions
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-11-30
We approximate large non-structured Matérn covariance matrices of size n×n in the H-matrix format with a log-linear computational cost and storage O(kn log n), where rank k ≪ n is a small integer. Applications are: spatial statistics, machine learning and image analysis, kriging and optimal design.
Approximate methods for derivation of covariance data
International Nuclear Information System (INIS)
Tagesen, S.
1992-01-01
Several approaches for the derivation of covariance information for evaluated nuclear data files (EFF2 and ENDF/B-VI) have been developed and used at IRK and ORNL respectively. Considerations, governing the choice of a distinct method depending on the quantity and quality of available data are presented, advantages/disadvantages are discussed and examples of results are given
Optimal covariate designs theory and applications
Das, Premadhis; Mandal, Nripes Kumar; Sinha, Bikas Kumar
2015-01-01
This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for...
Asymptotics for the minimum covariance determinant estimator
Butler, R.W.; Davies, P.L.; Jhun, M.
1993-01-01
Consistency is shown for the minimum covariance determinant (MCD) estimators of multivariate location and scale and asymptotic normality is shown for the former. The proofs are made possible by showing a separating ellipsoid property for the MCD subset of observations. An analogous property is shown
EQUIVALENT MODELS IN COVARIANCE STRUCTURE-ANALYSIS
LUIJBEN, TCW
1991-01-01
Defining equivalent models as those that reproduce the same set of covariance matrices, necessary and sufficient conditions are stated for the local equivalence of two expanded identified models M1 and M2 when fitting the more restricted model M0. Assuming several regularity conditions, the rank
Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z
2015-11-01
Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.
ENDF-6 File 30: Data covariances obtained from parameter covariances and sensitivities
International Nuclear Information System (INIS)
Muir, D.W.
1989-01-01
File 30 is provided as a means of describing the covariances of tabulated cross sections, multiplicities, and energy-angle distributions that result from propagating the covariances of a set of underlying parameters (for example, the input parameters of a nuclear-model code), using an evaluator-supplied set of parameter covariances and sensitivities. Whenever nuclear data are evaluated primarily through the application of nuclear models, the covariances of the resulting data can be described very adequately, and compactly, by specifying the covariance matrix for the underlying nuclear parameters, along with a set of sensitivity coefficients giving the rate of change of each nuclear datum of interest with respect to each of the model parameters. Although motivated primarily by these applications of nuclear theory, use of File 30 is not restricted to any one particular evaluation methodology. It can be used to describe data covariances of any origin, so long as they can be formally separated into a set of parameters with specified covariances and a set of data sensitivities
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Shephard, N.
2004-01-01
This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing...... the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities....
Determination of covariant Schwinger terms in anomalous gauge theories
International Nuclear Information System (INIS)
Kelnhofer, G.
1991-01-01
A functional integral method is used to determine equal time commutators between the covariant currents and the covariant Gauss-law operators in theories which are affected by an anomaly. By using a differential geometrical setup we show how the derivation of consistent- and covariant Schwinger terms can be understood on an equal footing. We find a modified consistency condition for the covariant anomaly. As a by-product the Bardeen-Zumino functional, which relates consistent and covariant anomalies, can be interpreted as connection on a certain line bundle over all gauge potentials. Finally the covariant commutator anomalies are calculated for the two- and four dimensional case. (orig.)
Paragrassmann analysis and covariant quantum algebras
International Nuclear Information System (INIS)
Filippov, A.T.; Isaev, A.P.; Kurdikov, A.B.; Pyatov, P.N.
1993-01-01
This report is devoted to the consideration from the algebraic point of view the paragrassmann algebras with one and many paragrassmann generators Θ i , Θ p+1 i = 0. We construct the paragrassmann versions of the Heisenberg algebra. For the special case, this algebra is nothing but the algebra for coordinates and derivatives considered in the context of covariant differential calculus on quantum hyperplane. The parameter of deformation q in our case is (p+1)-root of unity. Our construction is nondegenerate only for even p. Taking bilinear combinations of paragrassmann derivatives and coordinates we realize generators for the covariant quantum algebras as tensor products of (p+1) x (p+1) matrices. (orig./HSI)
Covariant holography of a tachyonic accelerating universe
Energy Technology Data Exchange (ETDEWEB)
Rozas-Fernandez, Alberto [Consejo Superior de Investigaciones Cientificas, Instituto de Fisica Fundamental, Madrid (Spain); University of Portsmouth, Institute of Cosmology and Gravitation, Portsmouth (United Kingdom)
2014-08-15
We apply the holographic principle to a flat dark energy dominated Friedmann-Robertson-Walker spacetime filled with a tachyon scalar field with constant equation of state w = p/ρ, both for w > -1 and w < -1. By using a geometrical covariant procedure, which allows the construction of holographic hypersurfaces, we have obtained for each case the position of the preferred screen and have then compared these with those obtained by using the holographic dark energy model with the future event horizon as the infrared cutoff. In the phantom scenario, one of the two obtained holographic screens is placed on the big rip hypersurface, both for the covariant holographic formalism and the holographic phantom model. It is also analyzed whether the existence of these preferred screens allows a mathematically consistent formulation of fundamental theories based on the existence of an S-matrix at infinite distances. (orig.)
On covariance structure in noisy, big data
Paffenroth, Randy C.; Nong, Ryan; Du Toit, Philip C.
2013-09-01
Herein we describe theory and algorithms for detecting covariance structures in large, noisy data sets. Our work uses ideas from matrix completion and robust principal component analysis to detect the presence of low-rank covariance matrices, even when the data is noisy, distorted by large corruptions, and only partially observed. In fact, the ability to handle partial observations combined with ideas from randomized algorithms for matrix decomposition enables us to produce asymptotically fast algorithms. Herein we will provide numerical demonstrations of the methods and their convergence properties. While such methods have applicability to many problems, including mathematical finance, crime analysis, and other large-scale sensor fusion problems, our inspiration arises from applying these methods in the context of cyber network intrusion detection.
Twisted covariant noncommutative self-dual gravity
International Nuclear Information System (INIS)
Estrada-Jimenez, S.; Garcia-Compean, H.; Obregon, O.; Ramirez, C.
2008-01-01
A twisted covariant formulation of noncommutative self-dual gravity is presented. The formulation for constructing twisted noncommutative Yang-Mills theories is used. It is shown that the noncommutative torsion is solved at any order of the θ expansion in terms of the tetrad and some extra fields of the theory. In the process the first order expansion in θ for the Plebanski action is explicitly obtained.
Superfield quantization in Sp(2) covariant formalism
Lavrov, P M
2001-01-01
The rules of the superfield Sp(2) covariant quantization of the arbitrary gauge theories for the case of the introduction of the gauging with the derivative equations for the gauge functional are generalized. The possibilities of realization of the expanded anti-brackets are considered and it is shown, that only one of the realizations is compatible with the transformations of the expanded BRST-symmetry in the form of super translations along the Grassmann superspace coordinates
Torsion and geometrostasis in covariant superstrings
International Nuclear Information System (INIS)
Zachos, C.
1985-01-01
The covariant action for freely propagating heterotic superstrings consists of a metric and a torsion term with a special relative strength. It is shown that the strength for which torsion flattens the underlying 10-dimensional superspace geometry is precisely that which yields free oscillators on the light cone. This is in complete analogy with the geometrostasis of two-dimensional sigma-models with Wess-Zumino interactions. 13 refs
Covariant derivatives of the Berezin transform
Czech Academy of Sciences Publication Activity Database
Engliš, Miroslav; Otáhalová, R.
2011-01-01
Roč. 363, č. 10 (2011), s. 5111-5129 ISSN 0002-9947 R&D Projects: GA AV ČR IAA100190802 Keywords : Berezin transform * Berezin symbol * covariant derivative Subject RIV: BA - General Mathematics Impact factor: 1.093, year: 2011 http://www.ams.org/journals/tran/2011-363-10/S0002-9947-2011-05111-1/home.html
Torsion and geometrostasis in covariant superstrings
Energy Technology Data Exchange (ETDEWEB)
Zachos, C.
1985-01-01
The covariant action for freely propagating heterotic superstrings consists of a metric and a torsion term with a special relative strength. It is shown that the strength for which torsion flattens the underlying 10-dimensional superspace geometry is precisely that which yields free oscillators on the light cone. This is in complete analogy with the geometrostasis of two-dimensional sigma-models with Wess-Zumino interactions. 13 refs.
Covariance expressions for eigenvalue and eigenvector problems
Liounis, Andrew J.
There are a number of important scientific and engineering problems whose solutions take the form of an eigenvalue--eigenvector problem. Some notable examples include solutions to linear systems of ordinary differential equations, controllability of linear systems, finite element analysis, chemical kinetics, fitting ellipses to noisy data, and optimal estimation of attitude from unit vectors. In many of these problems, having knowledge of the eigenvalue and eigenvector Jacobians is either necessary or is nearly as important as having the solution itself. For instance, Jacobians are necessary to find the uncertainty in a computed eigenvalue or eigenvector estimate. This uncertainty, which is usually represented as a covariance matrix, has been well studied for problems similar to the eigenvalue and eigenvector problem, such as singular value decomposition. There has been substantially less research on the covariance of an optimal estimate originating from an eigenvalue-eigenvector problem. In this thesis we develop two general expressions for the Jacobians of eigenvalues and eigenvectors with respect to the elements of their parent matrix. The expressions developed make use of only the parent matrix and the eigenvalue and eigenvector pair under consideration. In addition, they are applicable to any general matrix (including complex valued matrices, eigenvalues, and eigenvectors) as long as the eigenvalues are simple. Alongside this, we develop expressions that determine the uncertainty in a vector estimate obtained from an eigenvalue-eigenvector problem given the uncertainty of the terms of the matrix. The Jacobian expressions developed are numerically validated with forward finite, differencing and the covariance expressions are validated using Monte Carlo analysis. Finally, the results from this work are used to determine covariance expressions for a variety of estimation problem examples and are also applied to the design of a dynamical system.
Linear Covariance Analysis for a Lunar Lander
Jang, Jiann-Woei; Bhatt, Sagar; Fritz, Matthew; Woffinden, David; May, Darryl; Braden, Ellen; Hannan, Michael
2017-01-01
A next-generation lunar lander Guidance, Navigation, and Control (GNC) system, which includes a state-of-the-art optical sensor suite, is proposed in a concept design cycle. The design goal is to allow the lander to softly land within the prescribed landing precision. The achievement of this precision landing requirement depends on proper selection of the sensor suite. In this paper, a robust sensor selection procedure is demonstrated using a Linear Covariance (LinCov) analysis tool developed by Draper.
The covariant formulation of f ( T ) gravity
International Nuclear Information System (INIS)
Krššák, Martin; Saridakis, Emmanuel N
2016-01-01
We show that the well-known problem of frame dependence and violation of local Lorentz invariance in the usual formulation of f ( T ) gravity is a consequence of neglecting the role of spin connection. We re-formulate f ( T ) gravity starting from, instead of the ‘pure tetrad’ teleparallel gravity, the covariant teleparallel gravity, using both the tetrad and the spin connection as dynamical variables, resulting in a fully covariant, consistent, and frame-independent version of f ( T ) gravity, which does not suffer from the notorious problems of the usual, pure tetrad, f ( T ) theory. We present the method to extract solutions for the most physically important cases, such as the Minkowski, the Friedmann–Robertson–Walker (FRW) and the spherically symmetric ones. We show that in covariant f ( T ) gravity we are allowed to use an arbitrary tetrad in an arbitrary coordinate system along with the corresponding spin connection, resulting always in the same physically relevant field equations. (paper)
Development of covariance capabilities in EMPIRE code
Energy Technology Data Exchange (ETDEWEB)
Herman,M.; Pigni, M.T.; Oblozinsky, P.; Mughabghab, S.F.; Mattoon, C.M.; Capote, R.; Cho, Young-Sik; Trkov, A.
2008-06-24
The nuclear reaction code EMPIRE has been extended to provide evaluation capabilities for neutron cross section covariances in the thermal, resolved resonance, unresolved resonance and fast neutron regions. The Atlas of Neutron Resonances by Mughabghab is used as a primary source of information on uncertainties at low energies. Care is taken to ensure consistency among the resonance parameter uncertainties and those for thermal cross sections. The resulting resonance parameter covariances are formatted in the ENDF-6 File 32. In the fast neutron range our methodology is based on model calculations with the code EMPIRE combined with experimental data through several available approaches. The model-based covariances can be obtained using deterministic (Kalman) or stochastic (Monte Carlo) propagation of model parameter uncertainties. We show that these two procedures yield comparable results. The Kalman filter and/or the generalized least square fitting procedures are employed to incorporate experimental information. We compare the two approaches analyzing results for the major reaction channels on {sup 89}Y. We also discuss a long-standing issue of unreasonably low uncertainties and link it to the rigidity of the model.
Covariant electrodynamics in linear media: Optical metric
Thompson, Robert T.
2018-03-01
While the postulate of covariance of Maxwell's equations for all inertial observers led Einstein to special relativity, it was the further demand of general covariance—form invariance under general coordinate transformations, including between accelerating frames—that led to general relativity. Several lines of inquiry over the past two decades, notably the development of metamaterial-based transformation optics, has spurred a greater interest in the role of geometry and space-time covariance for electrodynamics in ponderable media. I develop a generally covariant, coordinate-free framework for electrodynamics in general dielectric media residing in curved background space-times. In particular, I derive a relation for the spatial medium parameters measured by an arbitrary timelike observer. In terms of those medium parameters I derive an explicit expression for the pseudo-Finslerian optical metric of birefringent media and show how it reduces to a pseudo-Riemannian optical metric for nonbirefringent media. This formulation provides a basis for a unified approach to ray and congruence tracing through media in curved space-times that may smoothly vary among positively refracting, negatively refracting, and vacuum.
SG39 Deliverables. Comments on Covariance Data
International Nuclear Information System (INIS)
Yokoyama, Kenji
2015-01-01
The covariance matrix of a scattered data set, x_i (i=1,n), must be symmetric and positive-definite. As one of WPEC/SG39 contributions to the SG40/CIELO project, several comments or recommendations on the covariance data are described here from the viewpoint of nuclear-data users. To make the comments concrete and useful for nuclear-data evaluators, the covariance data of the latest evaluated nuclear data library, JENDL-4.0 and ENDF/B-VII.1 are treated here as the representative materials. The surveyed nuclides are five isotopes that are most important for fast reactor application. The nuclides, reactions and energy regions dealt with are followings: Pu-239: fission (2.5∼10 keV) and capture (2.5∼10 keV), U-235: fission (500 eV∼10 keV) and capture (500 eV∼30 keV), U-238: fission (1∼10 MeV), capture (below 20 keV, 20∼150 keV), inelastic (above 100 keV) and elastic (above 20 keV), Fe-56: elastic (below 850 keV) and average scattering cosine (above 10 keV), and, Na-23: capture (600 eV∼600 keV), inelastic (above 1 MeV) and elastic (around 2 keV)
Flexible Bayesian Dynamic Modeling of Covariance and Correlation Matrices
Lan, Shiwei; Holbrook, Andrew; Fortin, Norbert J.; Ombao, Hernando; Shahbaba, Babak
2017-01-01
Modeling covariance (and correlation) matrices is a challenging problem due to the large dimensionality and positive-definiteness constraint. In this paper, we propose a novel Bayesian framework based on decomposing the covariance matrix
ERRORJ. Covariance processing code. Version 2.2
International Nuclear Information System (INIS)
Chiba, Go
2004-07-01
ERRORJ is the covariance processing code that can produce covariance data of multi-group cross sections, which are essential for uncertainty analyses of nuclear parameters, such as neutron multiplication factor. The ERRORJ code can process the covariance data of cross sections including resonance parameters, angular and energy distributions of secondary neutrons. Those covariance data cannot be processed by the other covariance processing codes. ERRORJ has been modified and the version 2.2 has been developed. This document describes the modifications and how to use. The main topics of the modifications are as follows. Non-diagonal elements of covariance matrices are calculated in the resonance energy region. Option for high-speed calculation is implemented. Perturbation amount is optimized in a sensitivity calculation. Effect of the resonance self-shielding on covariance of multi-group cross section can be considered. It is possible to read a compact covariance format proposed by N.M. Larson. (author)
New perspective in covariance evaluation for nuclear data
International Nuclear Information System (INIS)
Kanda, Y.
1992-01-01
Methods of nuclear data evaluation have been highly developed during the past decade, especially after introducing the concept of covariance. This makes it utmost important how to evaluate covariance matrices for nuclear data. It can be said that covariance evaluation is just the nuclear data evaluation, because the covariance matrix has quantitatively decisive function in current evaluation methods. The covariance primarily represents experimental uncertainties. However, correlation of individual uncertainties between different data must be taken into account and it can not be conducted without detailed physical considerations on experimental conditions. This procedure depends on the evaluator and the estimated covariance does also. The mathematical properties of the covariance have been intensively discussed. Their physical properties should be studied to apply it to the nuclear data evaluation, and then, in this report, are reviewed to give the base for further development of the covariance application. (orig.)
High-dimensional covariance estimation with high-dimensional data
Pourahmadi, Mohsen
2013-01-01
Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and mac
Comparative Analyses of Phenotypic Trait Covariation within and among Populations.
Peiman, Kathryn S; Robinson, Beren W
2017-10-01
Many morphological, behavioral, physiological, and life-history traits covary across the biological scales of individuals, populations, and species. However, the processes that cause traits to covary also change over these scales, challenging our ability to use patterns of trait covariance to infer process. Trait relationships are also widely assumed to have generic functional relationships with similar evolutionary potentials, and even though many different trait relationships are now identified, there is little appreciation that these may influence trait covariation and evolution in unique ways. We use a trait-performance-fitness framework to classify and organize trait relationships into three general classes, address which ones more likely generate trait covariation among individuals in a population, and review how selection shapes phenotypic covariation. We generate predictions about how trait covariance changes within and among populations as a result of trait relationships and in response to selection and consider how these can be tested with comparative data. Careful comparisons of covariation patterns can narrow the set of hypothesized processes that cause trait covariation when the form of the trait relationship and how it responds to selection yield clear predictions about patterns of trait covariation. We discuss the opportunities and limitations of comparative approaches to evaluate hypotheses about the evolutionary causes and consequences of trait covariation and highlight the importance of evaluating patterns within populations replicated in the same and in different selective environments. Explicit hypotheses about trait relationships are key to generating effective predictions about phenotype and its evolution using covariance data.
Covariant differential calculus on quantum spheres of odd dimension
International Nuclear Information System (INIS)
Welk, M.
1998-01-01
Covariant differential calculus on the quantum spheres S q 2N-1 is studied. Two classification results for covariant first order differential calculi are proved. As an important step towards a description of the noncommutative geometry of the quantum spheres, a framework of covariant differential calculus is established, including first and higher order calculi and a symmetry concept. (author)
On the covariance matrices in the evaluated nuclear data
International Nuclear Information System (INIS)
Corcuera, R.P.
1983-05-01
The implications of the uncertainties of nuclear data on reactor calculations are shown. The concept of variance, covariance and correlation are expressed first by intuitive definitions and then through statistical theory. The format of the covariance data for ENDF/B is explained and the formulas to obtain the multigroup covariances are given. (Author) [pt
Evaluation of covariance in theoretical calculation of nuclear data
International Nuclear Information System (INIS)
Kikuchi, Yasuyuki
1981-01-01
Covariances of the cross sections are discussed on the statistical model calculations. Two categories of covariance are discussed: One is caused by the model approximation and the other by the errors in the model parameters. As an example, the covariances are calculated for 100 Ru. (author)
Covariate Imbalance and Precision in Measuring Treatment Effects
Liu, Xiaofeng Steven
2011-01-01
Covariate adjustment can increase the precision of estimates by removing unexplained variance from the error in randomized experiments, although chance covariate imbalance tends to counteract the improvement in precision. The author develops an easy measure to examine chance covariate imbalance in randomization by standardizing the average…
Earth Observation System Flight Dynamics System Covariance Realism
Zaidi, Waqar H.; Tracewell, David
2016-01-01
This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.
Evaluation of covariance for 238U cross sections
International Nuclear Information System (INIS)
Kawano, Toshihiko; Nakamura, Masahiro; Matsuda, Nobuyuki; Kanda, Yukinori
1995-01-01
Covariances of 238 U are generated using analytic functions for representation of the cross sections. The covariances of the (n,2n) and (n,3n) reactions are derived with a spline function, while the covariances of the total and the inelastic scattering cross section are estimated with a linearized nuclear model calculation. (author)
Effortless assignment with 4D covariance sequential correlation maps.
Harden, Bradley J; Mishra, Subrata H; Frueh, Dominique P
2015-11-01
Traditional Nuclear Magnetic Resonance (NMR) assignment procedures for proteins rely on preliminary peak-picking to identify and label NMR signals. However, such an approach has severe limitations when signals are erroneously labeled or completely neglected. The consequences are especially grave for proteins with substantial peak overlap, and mistakes can often thwart entire projects. To overcome these limitations, we previously introduced an assignment technique that bypasses traditional pick peaking altogether. Covariance Sequential Correlation Maps (COSCOMs) transform the indirect connectivity information provided by multiple 3D backbone spectra into direct (H, N) to (H, N) correlations. Here, we present an updated method that utilizes a single four-dimensional spectrum rather than a suite of three-dimensional spectra. We demonstrate the advantages of 4D-COSCOMs relative to their 3D counterparts. We introduce improvements accelerating their calculation. We discuss practical considerations affecting their quality. And finally we showcase their utility in the context of a 52 kDa cyclization domain from a non-ribosomal peptide synthetase. Copyright © 2015 Elsevier Inc. All rights reserved.
MATXTST, Basic Operations for Covariance Matrices
International Nuclear Information System (INIS)
Geraldo, Luiz P.; Smith, Donald
1989-01-01
1 - Description of program or function: MATXTST and MATXTST1 perform the following operations for a covariance matrix: - test for singularity; - test for positive definiteness; - compute the inverse if the matrix is non-singular; - compute the determinant; - determine the number of positive, negative, and zero eigenvalues; - examine all possible 3 X 3 cross correlations within a sub-matrix corresponding to a leading principal minor which is non-positive definite. While the two programs utilize the same input, the calculational procedures employed are somewhat different and their functions are complementary. The available input options include: i) the full covariance matrix, ii) the basic variables plus the relative covariance matrix, or iii) uncertainties in the basic variables plus the correlation matrix. 2 - Method of solution: MATXTST employs LINPACK subroutines SPOFA and SPODI to test for positive definiteness and to perform further optional calculations. Subroutine SPOFA factors a symmetric matrix M using the Cholesky algorithm to determine the elements of a matrix R which satisfies the relation M=R'R, where R' is the transposed matrix of R. Each leading principal minor of M is tested until the first one is found which is not positive definite. MATXTST1 uses LINPACK subroutines SSICO, SSIFA, and SSIDI to estimate whether the matrix is near to singularity or not (SSICO), and to perform the matrix diagonalization process (SSIFA). The algorithm used in SSIFA is generalization of the Method of Lagrange Reduction. SSIDI is used to compute the determinant and inertia of the matrix. 3 - Restrictions on the complexity of the problem: Matrices of sizes up to 50 X 50 elements can be treated by present versions of the programs
Non-evaluation applications for covariance matrices
Energy Technology Data Exchange (ETDEWEB)
Smith, D.L.
1982-05-01
The possibility for application of covariance matrix techniques to a variety of common research problems other than formal data evaluation are demonstrated by means of several examples. These examples deal with such matters as fitting spectral data, deriving uncertainty estimates for results calculated from experimental data, obtaining the best values for plurally-measured quantities, and methods for analysis of cross section errors based on properties of the experiment. The examples deal with realistic situations encountered in the laboratory, and they are treated in sufficient detail to enable a careful reader to extrapolate the methods to related problems.
Covariant, chirally symmetric, confining model of mesons
International Nuclear Information System (INIS)
Gross, F.; Milana, J.
1991-01-01
We introduce a new model of mesons as quark-antiquark bound states. The model is covariant, confining, and chirally symmetric. Our equations give an analytic solution for a zero-mass pseudoscalar bound state in the case of exact chiral symmetry, and also reduce to the familiar, highly successful nonrelativistic linear potential models in the limit of heavy-quark mass and lightly bound systems. In this fashion we are constructing a unified description of all the mesons from the π through the Υ. Numerical solutions for other cases are also presented
Cosmology of a covariant Galilean field.
De Felice, Antonio; Tsujikawa, Shinji
2010-09-10
We study the cosmology of a covariant scalar field respecting a Galilean symmetry in flat space-time. We show the existence of a tracker solution that finally approaches a de Sitter fixed point responsible for cosmic acceleration today. The viable region of model parameters is clarified by deriving conditions under which ghosts and Laplacian instabilities of scalar and tensor perturbations are absent. The field equation of state exhibits a peculiar phantomlike behavior along the tracker, which allows a possibility to observationally distinguish the Galileon gravity from the cold dark matter model with a cosmological constant.
Covariant differential complexes of quantum linear groups
International Nuclear Information System (INIS)
Isaev, A.P.; Pyatov, P.N.
1993-01-01
We consider the possible covariant external algebra structures for Cartan's 1-forms (Ω) on G L q (N) and S L q (N). Our starting point is that Ω s realize an adjoint representation of quantum group and all monomials of Ω s possess the unique ordering. For the obtained external algebras we define the differential mapping d possessing the usual nilpotence condition, and the generally deformed version of Leibnitz rules. The status of the known examples of G L q (N)-differential calculi in the proposed classification scheme and the problems of S L q (N)-reduction are discussed. (author.). 26 refs
Minimal covariant observables identifying all pure states
Energy Technology Data Exchange (ETDEWEB)
Carmeli, Claudio, E-mail: claudio.carmeli@gmail.com [D.I.M.E., Università di Genova, Via Cadorna 2, I-17100 Savona (Italy); I.N.F.N., Sezione di Genova, Via Dodecaneso 33, I-16146 Genova (Italy); Heinosaari, Teiko, E-mail: teiko.heinosaari@utu.fi [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku (Finland); Toigo, Alessandro, E-mail: alessandro.toigo@polimi.it [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); I.N.F.N., Sezione di Milano, Via Celoria 16, I-20133 Milano (Italy)
2013-09-02
It has been recently shown by Heinosaari, Mazzarella and Wolf (2013) [1] that an observable that identifies all pure states of a d-dimensional quantum system has minimally 4d−4 outcomes or slightly less (the exact number depending on d). However, no simple construction of this type of minimal observable is known. We investigate covariant observables that identify all pure states and have minimal number of outcomes. It is shown that the existence of this kind of observables depends on the dimension of the Hilbert space.
Linear Covariance Analysis and Epoch State Estimators
Markley, F. Landis; Carpenter, J. Russell
2014-01-01
This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.
Agnostic Estimation of Mean and Covariance
Lai, Kevin A.; Rao, Anup B.; Vempala, Santosh
2016-01-01
We consider the problem of estimating the mean and covariance of a distribution from iid samples in $\\mathbb{R}^n$, in the presence of an $\\eta$ fraction of malicious noise; this is in contrast to much recent work where the noise itself is assumed to be from a distribution of known type. The agnostic problem includes many interesting special cases, e.g., learning the parameters of a single Gaussian (or finding the best-fit Gaussian) when $\\eta$ fraction of data is adversarially corrupted, agn...
On the Galilean covariance of classical mechanics
International Nuclear Information System (INIS)
Horzela, A.; Kapuscik, E.; Kempczynski, J.; Joint Inst. for Nuclear Research, Dubna
1991-08-01
A Galilean covariant approach to classical mechanics of a single interacting particle is described. In this scheme constitutive relations defining forces are rejected and acting forces are determined by some fundamental differential equations. It is shown that total energy of the interacting particle transforms under Galilean transformations differently from the kinetic energy. The statement is illustrated on the exactly solvable examples of the harmonic oscillator and the case of constant forces and also, in the suitable version of the perturbation theory, for the anharmonic oscillator. (author)
Determination of covariant Schwinger terms in anomalous gauge theories
International Nuclear Information System (INIS)
Kelnhofer, G.
1991-01-01
A functional integral method is used to determine equal time commutators between the covariant currents and the covariant Gauss-law operators in theories which are affected by an anomaly. By using a differential geometrical setup we show how the derivation of consistent- and covariant Schwinger terms can be understood on an equal footing. We find a modified consistency condition for the covariant anomaly. As a by-product the Bardeen-Zumino functional, which relates consistent and covariant anomalies, can be interpreted as connection on a certain line bundle over all gauge potentials. Finally the commutator anomalies are calculated for the two- and four dimensional case. (Author) 13 refs
ERRORJ. Covariance processing code system for JENDL. Version 2
International Nuclear Information System (INIS)
Chiba, Gou
2003-09-01
ERRORJ is the covariance processing code system for Japanese Evaluated Nuclear Data Library (JENDL) that can produce group-averaged covariance data to apply it to the uncertainty analysis of nuclear characteristics. ERRORJ can treat the covariance data for cross sections including resonance parameters as well as angular distributions and energy distributions of secondary neutrons which could not be dealt with by former covariance processing codes. In addition, ERRORJ can treat various forms of multi-group cross section and produce multi-group covariance file with various formats. This document describes an outline of ERRORJ and how to use it. (author)
Piecewise linear regression splines with hyperbolic covariates
International Nuclear Information System (INIS)
Cologne, John B.; Sposto, Richard
1992-09-01
Consider the problem of fitting a curve to data that exhibit a multiphase linear response with smooth transitions between phases. We propose substituting hyperbolas as covariates in piecewise linear regression splines to obtain curves that are smoothly joined. The method provides an intuitive and easy way to extend the two-phase linear hyperbolic response model of Griffiths and Miller and Watts and Bacon to accommodate more than two linear segments. The resulting regression spline with hyperbolic covariates may be fit by nonlinear regression methods to estimate the degree of curvature between adjoining linear segments. The added complexity of fitting nonlinear, as opposed to linear, regression models is not great. The extra effort is particularly worthwhile when investigators are unwilling to assume that the slope of the response changes abruptly at the join points. We can also estimate the join points (the values of the abscissas where the linear segments would intersect if extrapolated) if their number and approximate locations may be presumed known. An example using data on changing age at menarche in a cohort of Japanese women illustrates the use of the method for exploratory data analysis. (author)
Hierarchical multivariate covariance analysis of metabolic connectivity.
Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J
2014-12-01
Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).
Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data
International Nuclear Information System (INIS)
Jun, Sung C; Plis, Sergey M; Ranken, Doug M; Schmidt, David M
2006-01-01
The performance of parametric magnetoencephalography (MEG) and electroencephalography (EEG) source localization approaches can be degraded by the use of poor background noise covariance estimates. In general, estimation of the noise covariance for spatiotemporal analysis is difficult mainly due to the limited noise information available. Furthermore, its estimation requires a large amount of storage and a one-time but very large (and sometimes intractable) calculation or its inverse. To overcome these difficulties, noise covariance models consisting of one pair or a sum of multi-pairs of Kronecker products of spatial covariance and temporal covariance have been proposed. However, these approaches cannot be applied when the noise information is very limited, i.e., the amount of noise information is less than the degrees of freedom of the noise covariance models. A common example of this is when only averaged noise data are available for a limited prestimulus region (typically at most a few hundred milliseconds duration). For such cases, a diagonal spatiotemporal noise covariance model consisting of sensor variances with no spatial or temporal correlation has been the common choice for spatiotemporal analysis. In this work, we propose a different noise covariance model which consists of diagonal spatial noise covariance and Toeplitz temporal noise covariance. It can easily be estimated from limited noise information, and no time-consuming optimization and data-processing are required. Thus, it can be used as an alternative choice when one-pair or multi-pair noise covariance models cannot be estimated due to lack of noise information. To verify its capability we used Bayesian inference dipole analysis and a number of simulated and empirical datasets. We compared this covariance model with other existing covariance models such as conventional diagonal covariance, one-pair and multi-pair noise covariance models, when noise information is sufficient to estimate them. We
Gaskins, J T; Daniels, M J
2016-01-02
The estimation of the covariance matrix is a key concern in the analysis of longitudinal data. When data consists of multiple groups, it is often assumed the covariance matrices are either equal across groups or are completely distinct. We seek methodology to allow borrowing of strength across potentially similar groups to improve estimation. To that end, we introduce a covariance partition prior which proposes a partition of the groups at each measurement time. Groups in the same set of the partition share dependence parameters for the distribution of the current measurement given the preceding ones, and the sequence of partitions is modeled as a Markov chain to encourage similar structure at nearby measurement times. This approach additionally encourages a lower-dimensional structure of the covariance matrices by shrinking the parameters of the Cholesky decomposition toward zero. We demonstrate the performance of our model through two simulation studies and the analysis of data from a depression study. This article includes Supplementary Material available online.
Noisy covariance matrices and portfolio optimization II
Pafka, Szilárd; Kondor, Imre
2003-03-01
Recent studies inspired by results from random matrix theory (Galluccio et al.: Physica A 259 (1998) 449; Laloux et al.: Phys. Rev. Lett. 83 (1999) 1467; Risk 12 (3) (1999) 69; Plerou et al.: Phys. Rev. Lett. 83 (1999) 1471) found that covariance matrices determined from empirical financial time series appear to contain such a high amount of noise that their structure can essentially be regarded as random. This seems, however, to be in contradiction with the fundamental role played by covariance matrices in finance, which constitute the pillars of modern investment theory and have also gained industry-wide applications in risk management. Our paper is an attempt to resolve this embarrassing paradox. The key observation is that the effect of noise strongly depends on the ratio r= n/ T, where n is the size of the portfolio and T the length of the available time series. On the basis of numerical experiments and analytic results for some toy portfolio models we show that for relatively large values of r (e.g. 0.6) noise does, indeed, have the pronounced effect suggested by Galluccio et al. (1998), Laloux et al. (1999) and Plerou et al. (1999) and illustrated later by Laloux et al. (Int. J. Theor. Appl. Finance 3 (2000) 391), Plerou et al. (Phys. Rev. E, e-print cond-mat/0108023) and Rosenow et al. (Europhys. Lett., e-print cond-mat/0111537) in a portfolio optimization context, while for smaller r (around 0.2 or below), the error due to noise drops to acceptable levels. Since the length of available time series is for obvious reasons limited in any practical application, any bound imposed on the noise-induced error translates into a bound on the size of the portfolio. In a related set of experiments we find that the effect of noise depends also on whether the problem arises in asset allocation or in a risk measurement context: if covariance matrices are used simply for measuring the risk of portfolios with a fixed composition rather than as inputs to optimization, the
Computing more proper covariances of energy dependent nuclear data
International Nuclear Information System (INIS)
Vanhanen, R.
2016-01-01
Highlights: • We present conditions for covariances of energy dependent nuclear data to be proper. • We provide methods to detect non-positive and inconsistent covariances in ENDF-6 format. • We propose methods to find nearby more proper covariances. • The methods can be used as a part of a quality assurance program. - Abstract: We present conditions for covariances of energy dependent nuclear data to be proper in the sense that the covariances are positive, i.e., its eigenvalues are non-negative, and consistent with respect to the sum rules of nuclear data. For the ENDF-6 format covariances we present methods to detect non-positive and inconsistent covariances. These methods would be useful as a part of a quality assurance program. We also propose methods that can be used to find nearby more proper energy dependent covariances. These methods can be used to remove unphysical components, while preserving most of the physical components. We consider several different senses in which the nearness can be measured. These methods could be useful if a re-evaluation of improper covariances is not feasible. Two practical examples are processed and analyzed. These demonstrate some of the properties of the methods. We also demonstrate that the ENDF-6 format covariances of linearly dependent nuclear data should usually be encoded with the derivation rules.
Impact of the 235U Covariance Data in Benchmark Calculations
International Nuclear Information System (INIS)
Leal, Luiz C.; Mueller, D.; Arbanas, G.; Wiarda, D.; Derrien, H.
2008-01-01
The error estimation for calculated quantities relies on nuclear data uncertainty information available in the basic nuclear data libraries such as the U.S. Evaluated Nuclear Data File (ENDF/B). The uncertainty files (covariance matrices) in the ENDF/B library are generally obtained from analysis of experimental data. In the resonance region, the computer code SAMMY is used for analyses of experimental data and generation of resonance parameters. In addition to resonance parameters evaluation, SAMMY also generates resonance parameter covariance matrices (RPCM). SAMMY uses the generalized least-squares formalism (Bayes method) together with the resonance formalism (R-matrix theory) for analysis of experimental data. Two approaches are available for creation of resonance-parameter covariance data. (1) During the data-evaluation process, SAMMY generates both a set of resonance parameters that fit the experimental data and the associated resonance-parameter covariance matrix. (2) For existing resonance-parameter evaluations for which no resonance-parameter covariance data are available, SAMMY can retroactively create a resonance-parameter covariance matrix. The retroactive method was used to generate covariance data for 235U. The resulting 235U covariance matrix was then used as input to the PUFF-IV code, which processed the covariance data into multigroup form, and to the TSUNAMI code, which calculated the uncertainty in the multiplication factor due to uncertainty in the experimental cross sections. The objective of this work is to demonstrate the use of the 235U covariance data in calculations of critical benchmark systems
Development of covariance date for fast reactor cores. 3
International Nuclear Information System (INIS)
Shibata, Keiichi; Hasegawa, Akira
1999-03-01
Covariances have been estimated for nuclear data contained in JENDL-3.2. As for Cr and Ni, the physical quantities for which covariances are deduced are cross sections and the first order Legendre-polynomial coefficient for the angular distribution of elastically scattered neutrons. The covariances were estimated by using the same methodology that had been used in the JENDL-3.2 evaluation in order to keep a consistency between mean values and their covariances. In a case where evaluated data were based on experimental data, the covariances were estimated from the same experimental data. For cross section that had been evaluated by nuclear model calculations, the same model was applied to generate the covariances. The covariances obtained were compiled into ENDF-6 format files. The covariances, which had been prepared by the previous fiscal year, were re-examined, and some improvements were performed. Parts of Fe and 235 U covariances were updated. Covariances of nu-p and nu-d for 241 Pu and of fission neutron spectra for 233,235,238 U and 239,240 Pu were newly added to data files. (author)
Anomalous current from the covariant Wigner function
Prokhorov, George; Teryaev, Oleg
2018-04-01
We consider accelerated and rotating media of weakly interacting fermions in local thermodynamic equilibrium on the basis of kinetic approach. Kinetic properties of such media can be described by covariant Wigner function incorporating the relativistic distribution functions of particles with spin. We obtain the formulae for axial current by summation of the terms of all orders of thermal vorticity tensor, chemical potential, both for massive and massless particles. In the massless limit all the terms of fourth and higher orders of vorticity and third order of chemical potential and temperature equal zero. It is shown, that axial current gets a topological component along the 4-acceleration vector. The similarity between different approaches to baryon polarization is established.
Covariant non-commutative space–time
Directory of Open Access Journals (Sweden)
Jonathan J. Heckman
2015-05-01
Full Text Available We introduce a covariant non-commutative deformation of 3+1-dimensional conformal field theory. The deformation introduces a short-distance scale ℓp, and thus breaks scale invariance, but preserves all space–time isometries. The non-commutative algebra is defined on space–times with non-zero constant curvature, i.e. dS4 or AdS4. The construction makes essential use of the representation of CFT tensor operators as polynomials in an auxiliary polarization tensor. The polarization tensor takes active part in the non-commutative algebra, which for dS4 takes the form of so(5,1, while for AdS4 it assembles into so(4,2. The structure of the non-commutative correlation functions hints that the deformed theory contains gravitational interactions and a Regge-like trajectory of higher spin excitations.
Covariant entropy bound and loop quantum cosmology
International Nuclear Information System (INIS)
Ashtekar, Abhay; Wilson-Ewing, Edward
2008-01-01
We examine Bousso's covariant entropy bound conjecture in the context of radiation filled, spatially flat, Friedmann-Robertson-Walker models. The bound is violated near the big bang. However, the hope has been that quantum gravity effects would intervene and protect it. Loop quantum cosmology provides a near ideal setting for investigating this issue. For, on the one hand, quantum geometry effects resolve the singularity and, on the other hand, the wave function is sharply peaked at a quantum corrected but smooth geometry, which can supply the structure needed to test the bound. We find that the bound is respected. We suggest that the bound need not be an essential ingredient for a quantum gravity theory but may emerge from it under suitable circumstances.
Nonparametric Bayesian models for a spatial covariance.
Reich, Brian J; Fuentes, Montserrat
2012-01-01
A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.
Covariant Derivatives and the Renormalization Group Equation
Dolan, Brian P.
The renormalization group equation for N-point correlation functions can be interpreted in a geometrical manner as an equation for Lie transport of amplitudes in the space of couplings. The vector field generating the diffeomorphism has components given by the β functions of the theory. It is argued that this simple picture requires modification whenever any one of the points at which the amplitude is evaluated becomes close to any other. This modification necessitates the introduction of a connection on the space of couplings and new terms appear in the renormalization group equation involving covariant derivatives of the β function and the curvature associated with the connection. It is shown how the connection is related to the operator product expansion coefficients, but there remains an arbitrariness in its definition.
Generation of phase-covariant quantum cloning
International Nuclear Information System (INIS)
Karimipour, V.; Rezakhani, A.T.
2002-01-01
It is known that in phase-covariant quantum cloning, the equatorial states on the Bloch sphere can be cloned with a fidelity higher than the optimal bound established for universal quantum cloning. We generalize this concept to include other states on the Bloch sphere with a definite z component of spin. It is shown that once we know the z component, we can always clone a state with a fidelity higher than the universal value and that of equatorial states. We also make a detailed study of the entanglement properties of the output copies and show that the equatorial states are the only states that give rise to a separable density matrix for the outputs
Covariant formulation of scalar-torsion gravity
Hohmann, Manuel; Järv, Laur; Ualikhanova, Ulbossyn
2018-05-01
We consider a generalized teleparallel theory of gravitation, where the action contains an arbitrary function of the torsion scalar and a scalar field, f (T ,ϕ ) , thus encompassing the cases of f (T ) gravity and a nonminimally coupled scalar field as subclasses. The action is manifestly Lorentz invariant when besides the tetrad one allows for a flat but nontrivial spin connection. We derive the field equations and demonstrate how the antisymmetric part of the tetrad equations is automatically satisfied when the spin connection equation holds. The spin connection equation is a vital part of the covariant formulation, since it determines the spin connection associated with a given tetrad. We discuss how the spin connection equation can be solved in general and provide the cosmological and spherically symmetric examples. Finally, we generalize the theory to an arbitrary number of scalar fields.
Introduction to covariant formulation of superstring (field) theory
International Nuclear Information System (INIS)
Anon.
1987-01-01
The author discusses covariant formulation of superstring theories based on BRS invariance. New formulation of superstring was constructed by Green and Schwarz in the light-cone gauge first and then a covariant action was discovered. The covariant action has some interesting geometrical interpretation, however, covariant quantizations are difficult to perform because of existence of local supersymmetries. Introducing extra variables into the action, a modified action has been proposed. However, it would be difficult to prescribe constraints to define a physical subspace, or to reproduce the correct physical spectrum. Hence the old formulation, i.e., the Neveu-Schwarz-Ramond (NSR) model for covariant quantization is used. The author begins by quantizing the NSR model in a covariant way using BRS charges. Then the author discusses the field theory of (free) superstring
The method of covariant symbols in curved space-time
International Nuclear Information System (INIS)
Salcedo, L.L.
2007-01-01
Diagonal matrix elements of pseudodifferential operators are needed in order to compute effective Lagrangians and currents. For this purpose the method of symbols is often used, which however lacks manifest covariance. In this work the method of covariant symbols, introduced by Pletnev and Banin, is extended to curved space-time with arbitrary gauge and coordinate connections. For the Riemannian connection we compute the covariant symbols corresponding to external fields, the covariant derivative and the Laplacian, to fourth order in a covariant derivative expansion. This allows one to obtain the covariant symbol of general operators to the same order. The procedure is illustrated by computing the diagonal matrix element of a nontrivial operator to second order. Applications of the method are discussed. (orig.)
Physical properties of the Schur complement of local covariance matrices
International Nuclear Information System (INIS)
Haruna, L F; Oliveira, M C de
2007-01-01
General properties of global covariance matrices representing bipartite Gaussian states can be decomposed into properties of local covariance matrices and their Schur complements. We demonstrate that given a bipartite Gaussian state ρ 12 described by a 4 x 4 covariance matrix V, the Schur complement of a local covariance submatrix V 1 of it can be interpreted as a new covariance matrix representing a Gaussian operator of party 1 conditioned to local parity measurements on party 2. The connection with a partial parity measurement over a bipartite quantum state and the determination of the reduced Wigner function is given and an operational process of parity measurement is developed. Generalization of this procedure to an n-partite Gaussian state is given, and it is demonstrated that the n - 1 system state conditioned to a partial parity projection is given by a covariance matrix such that its 2 x 2 block elements are Schur complements of special local matrices
Fermionic covariant prolongation structure theory for supernonlinear evolution equation
International Nuclear Information System (INIS)
Cheng Jipeng; Wang Shikun; Wu Ke; Zhao Weizhong
2010-01-01
We investigate the superprincipal bundle and its associated superbundle. The super(nonlinear)connection on the superfiber bundle is constructed. Then by means of the connection theory, we establish the fermionic covariant prolongation structure theory of the supernonlinear evolution equation. In this geometry theory, the fermionic covariant fundamental equations determining the prolongation structure are presented. As an example, the supernonlinear Schroedinger equation is analyzed in the framework of this fermionic covariant prolongation structure theory. We obtain its Lax pairs and Baecklund transformation.
Bayesian hierarchical model for large-scale covariance matrix estimation.
Zhu, Dongxiao; Hero, Alfred O
2007-12-01
Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.
Some remarks on general covariance of quantum theory
International Nuclear Information System (INIS)
Schmutzer, E.
1977-01-01
If one accepts Einstein's general principle of relativity (covariance principle) also for the sphere of microphysics (quantum, mechanics, quantum field theory, theory of elemtary particles), one has to ask how far the fundamental laws of traditional quantum physics fulfil this principle. Attention is here drawn to a series of papers that have appeared during the last years, in which the author criticized the usual scheme of quantum theory (Heisenberg picture, Schroedinger picture etc.) and presented a new foundation of the basic laws of quantum physics, obeying the 'principle of fundamental covariance' (Einstein's covariance principle in space-time and covariance principle in Hilbert space of quantum operators and states). (author)
How much do genetic covariances alter the rate of adaptation?
Agrawal, Aneil F; Stinchcombe, John R
2009-03-22
Genetically correlated traits do not evolve independently, and the covariances between traits affect the rate at which a population adapts to a specified selection regime. To measure the impact of genetic covariances on the rate of adaptation, we compare the rate fitness increases given the observed G matrix to the expected rate if all the covariances in the G matrix are set to zero. Using data from the literature, we estimate the effect of genetic covariances in real populations. We find no net tendency for covariances to constrain the rate of adaptation, though the quality and heterogeneity of the data limit the certainty of this result. There are some examples in which covariances strongly constrain the rate of adaptation but these are balanced by counter examples in which covariances facilitate the rate of adaptation; in many cases, covariances have little or no effect. We also discuss how our metric can be used to identify traits or suites of traits whose genetic covariances to other traits have a particularly large impact on the rate of adaptation.
Summary report of technical meeting on neutron cross section covariances
International Nuclear Information System (INIS)
Trkov, A.; Smith, D.L.; Capote Noy, R.
2011-01-01
A summary is given of the Technical Meeting on Neutron Cross Section Covariances. The meeting goal was to assess covariance data needs and recommend appropriate methodologies to address those needs. Discussions on covariance data focused on three general topics: 1) Resonance and unresolved resonance regions; 2) Fast neutron region; and 3) Users' perspective: benchmarks' uncertainty and reactor dosimetry. A number of recommendations for further work were generated and the important work that remains to be done in the field of covariances was identified. (author)
Smooth individual level covariates adjustment in disease mapping.
Huque, Md Hamidul; Anderson, Craig; Walton, Richard; Woolford, Samuel; Ryan, Louise
2018-05-01
Spatial models for disease mapping should ideally account for covariates measured both at individual and area levels. The newly available "indiCAR" model fits the popular conditional autoregresssive (CAR) model by accommodating both individual and group level covariates while adjusting for spatial correlation in the disease rates. This algorithm has been shown to be effective but assumes log-linear associations between individual level covariates and outcome. In many studies, the relationship between individual level covariates and the outcome may be non-log-linear, and methods to track such nonlinearity between individual level covariate and outcome in spatial regression modeling are not well developed. In this paper, we propose a new algorithm, smooth-indiCAR, to fit an extension to the popular conditional autoregresssive model that can accommodate both linear and nonlinear individual level covariate effects while adjusting for group level covariates and spatial correlation in the disease rates. In this formulation, the effect of a continuous individual level covariate is accommodated via penalized splines. We describe a two-step estimation procedure to obtain reliable estimates of individual and group level covariate effects where both individual and group level covariate effects are estimated separately. This distributed computing framework enhances its application in the Big Data domain with a large number of individual/group level covariates. We evaluate the performance of smooth-indiCAR through simulation. Our results indicate that the smooth-indiCAR method provides reliable estimates of all regression and random effect parameters. We illustrate our proposed methodology with an analysis of data on neutropenia admissions in New South Wales (NSW), Australia. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Central subspace dimensionality reduction using covariance operators.
Kim, Minyoung; Pavlovic, Vladimir
2011-04-01
We consider the task of dimensionality reduction informed by real-valued multivariate labels. The problem is often treated as Dimensionality Reduction for Regression (DRR), whose goal is to find a low-dimensional representation, the central subspace, of the input data that preserves the statistical correlation with the targets. A class of DRR methods exploits the notion of inverse regression (IR) to discover central subspaces. Whereas most existing IR techniques rely on explicit output space slicing, we propose a novel method called the Covariance Operator Inverse Regression (COIR) that generalizes IR to nonlinear input/output spaces without explicit target slicing. COIR's unique properties make DRR applicable to problem domains with high-dimensional output data corrupted by potentially significant amounts of noise. Unlike recent kernel dimensionality reduction methods that employ iterative nonconvex optimization, COIR yields a closed-form solution. We also establish the link between COIR, other DRR techniques, and popular supervised dimensionality reduction methods, including canonical correlation analysis and linear discriminant analysis. We then extend COIR to semi-supervised settings where many of the input points lack their labels. We demonstrate the benefits of COIR on several important regression problems in both fully supervised and semi-supervised settings.
The covariance of GPS coordinates and frames
International Nuclear Information System (INIS)
Lachieze-Rey, Marc
2006-01-01
We explore, in the general relativistic context, the properties of the recently introduced global positioning system (GPS) coordinates, as well as those of the associated frames and coframes that they define. We show that they are covariant and completely independent of any observer. We show that standard spectroscopic and astrometric observations allow any observer to measure (i) the values of the GPS coordinates at his position (ii) the components of his 4-velocity and (iii) the components of the metric in the GPS frame. This provides this system with a unique value both for conceptual discussion (no frame dependence) and for practical use (involved quantities are directly measurable): localization, motion monitoring, astrometry, cosmography and tests of gravitation theories. We show explicitly, in the general relativistic context, how an observer may estimate his position and motion, and reconstruct the components of the metric. This arises from two main results: the extension of the velocity fields of the probes to the whole (curved) spacetime, and the identification of the components of the observer's velocity in the GPS frame with the (inversed) observed redshifts of the probes. Specific cases (non-relativistic velocities, Minkowski and Friedmann-Lemaitre spacetimes, geodesic motions) are studied in detail
Covariant path integrals on hyperbolic surfaces
Schaefer, Joe
1997-11-01
DeWitt's covariant formulation of path integration [B. De Witt, "Dynamical theory in curved spaces. I. A review of the classical and quantum action principles," Rev. Mod. Phys. 29, 377-397 (1957)] has two practical advantages over the traditional methods of "lattice approximations;" there is no ordering problem, and classical symmetries are manifestly preserved at the quantum level. Applying the spectral theorem for unbounded self-adjoint operators, we provide a rigorous proof of the convergence of certain path integrals on Riemann surfaces of constant curvature -1. The Pauli-DeWitt curvature correction term arises, as in DeWitt's work. Introducing a Fuchsian group Γ of the first kind, and a continuous, bounded, Γ-automorphic potential V, we obtain a Feynman-Kac formula for the automorphic Schrödinger equation on the Riemann surface ΓH. We analyze the Wick rotation and prove the strong convergence of the so-called Feynman maps [K. D. Elworthy, Path Integration on Manifolds, Mathematical Aspects of Superspace, edited by Seifert, Clarke, and Rosenblum (Reidel, Boston, 1983), pp. 47-90] on a dense set of states. Finally, we give a new proof of some results in C. Grosche and F. Steiner, "The path integral on the Poincare upper half plane and for Liouville quantum mechanics," Phys. Lett. A 123, 319-328 (1987).
Spinors, tensors and the covariant form of Dirac's equation
International Nuclear Information System (INIS)
Chen, W.Q.; Cook, A.H.
1986-01-01
The relations between tensors and spinors are used to establish the form of the covariant derivative of a spinor, making use of the fact that certain bilinear combinations of spinors are vectors. The covariant forms of Dirac's equation are thus obtained and examples in specific coordinate systems are displayed. (author)
A scale invariant covariance structure on jet space
DEFF Research Database (Denmark)
Pedersen, Kim Steenstrup; Loog, Marco; Markussen, Bo
2005-01-01
This paper considers scale invariance of statistical image models. We study statistical scale invariance of the covariance structure of jet space under scale space blurring and derive the necessary structure and conditions of the jet covariance matrix in order for it to be scale invariant. As par...
Transformation of covariant quark Wigner operator to noncovariant one
International Nuclear Information System (INIS)
Selikhov, A.V.
1989-01-01
The gauge in which covariant and noncovariant quark Wigner operators coincide has been found. In this gauge the representations of vector potential via field strength tensor is valid. The system of equations for the coefficients of covariant Wigner operator expansion in the basis γ-matrices algebra is obtained. 12 refs.; 3 figs
Covariance as input to and output from resonance analyses
International Nuclear Information System (INIS)
Larson, N.M.
1992-01-01
Accurate data analysis requires understanding of the roles played by both data and parameter covariance matrices. In this paper the entire data reduction/analysis process is examined, for neutron-induced reactions in the resonance region. Interrelationships between data and parameter covariance matrices are examined and alternative reduction/analysis methods discussed
A three domain covariance framework for EEG/MEG data
Ros, B.P.; Bijma, F.; de Gunst, M.C.M.; de Munck, J.C.
2015-01-01
In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three
application of covariance analysis to feed/ ration experimental data
African Journals Online (AJOL)
Prince Acheampong
ABSTRACT. The use Analysis of Covariance (ANOCOVA) to feed/ration experimental data for birds was examined. Correlation and Regression analyses were used to adjust for the covariate – initial weight of the experimental birds. The Fisher's F statistic for the straight forward Analysis of Variance (ANOVA) showed ...
Covariant Theory of Gravitation in the Spacetime with Finsler Structure
Huang, Xin-Bing
2007-01-01
The theory of gravitation in the spacetime with Finsler structure is constructed. It is shown that the theory keeps general covariance. Such theory reduces to Einstein's general relativity when the Finsler structure is Riemannian. Therefore, this covariant theory of gravitation is an elegant realization of Einstein's thoughts on gravitation in the spacetime with Finsler structure.
Some observations on interpolating gauges and non-covariant gauges
Indian Academy of Sciences (India)
We discuss the viability of using interpolating gauges to deﬁne the non-covariant gauges starting from the covariant ones. We draw attention to the need for a very careful treatment of boundary condition deﬁning term. We show that the boundary condition needed to maintain gauge-invariance as the interpolating parameter ...
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
DEFF Research Database (Denmark)
Andersen, P.; Brincker, Rune; Kirkegaard, Poul Henning
1996-01-01
In this paper the theoretical background for using covariance equivalent ARMAV models in modal analysis is discussed. It is shown how to obtain a covariance equivalent ARMA model for a univariate linear second order continous-time system excited by Gaussian white noise. This result is generalized...
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
DEFF Research Database (Denmark)
Andersen, P.; Brincker, Rune; Kirkegaard, Poul Henning
In this paper the theoretical background for using covariance equivalent ARMAV models in modal analysis is discussed. It is shown how to obtain a covariance equivalent ARMA model for a univariate linear second order continuous-time system excited by Gaussian white noise. This result is generalize...
Validity of covariance models for the analysis of geographical variation
DEFF Research Database (Denmark)
Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio
2014-01-01
1. Due to the availability of large molecular data-sets, covariance models are increasingly used to describe the structure of genetic variation as an alternative to more heavily parametrised biological models. 2. We focus here on a class of parametric covariance models that received sustained att...
The K-Step Spatial Sign Covariance Matrix
Croux, C.; Dehon, C.; Yadine, A.
2010-01-01
The Sign Covariance Matrix is an orthogonal equivariant estimator of mul- tivariate scale. It is often used as an easy-to-compute and highly robust estimator. In this paper we propose a k-step version of the Sign Covariance Matrix, which improves its e±ciency while keeping the maximal breakdown
On the bilinear covariants associated to mass dimension one spinors
Energy Technology Data Exchange (ETDEWEB)
Silva, J.M.H. da; Villalobos, C.H.C.; Rogerio, R.J.B. [DFQ, UNESP, Guaratingueta, SP (Brazil); Scatena, E. [Universidade Federal de Santa Catarina-CEE, Blumenau, SC (Brazil)
2016-10-15
In this paper we approach the issue of Clifford algebra basis deformation, allowing for bilinear covariants associated to Elko spinors which satisfy the Fierz-Pauli-Kofink identities. We present a complete analysis of covariance, taking into account the involved dual structure associated to Elko spinors. Moreover, the possible generalizations to the recently presented new dual structure are performed. (orig.)
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
Positive semidefinite integrated covariance estimation, factorizations and asynchronicity
DEFF Research Database (Denmark)
Boudt, Kris; Laurent, Sébastien; Lunde, Asger
2017-01-01
An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization of the covariance matrix in order to exploit the heterogeneity in trading intensities to estimate the different parameters sequentially with as many...
Precomputing Process Noise Covariance for Onboard Sequential Filters
Olson, Corwin G.; Russell, Ryan P.; Carpenter, J. Russell
2017-01-01
Process noise is often used in estimation filters to account for unmodeled and mismodeled accelerations in the dynamics. The process noise covariance acts to inflate the state covariance over propagation intervals, increasing the uncertainty in the state. In scenarios where the acceleration errors change significantly over time, the standard process noise covariance approach can fail to provide effective representation of the state and its uncertainty. Consider covariance analysis techniques provide a method to precompute a process noise covariance profile along a reference trajectory using known model parameter uncertainties. The process noise covariance profile allows significantly improved state estimation and uncertainty representation over the traditional formulation. As a result, estimation performance on par with the consider filter is achieved for trajectories near the reference trajectory without the additional computational cost of the consider filter. The new formulation also has the potential to significantly reduce the trial-and-error tuning currently required of navigation analysts. A linear estimation problem as described in several previous consider covariance analysis studies is used to demonstrate the effectiveness of the precomputed process noise covariance, as well as a nonlinear descent scenario at the asteroid Bennu with optical navigation.
Cross-population myelination covariance of human cerebral cortex.
Ma, Zhiwei; Zhang, Nanyin
2017-09-01
Cross-population covariance of brain morphometric quantities provides a measure of interareal connectivity, as it is believed to be determined by the coordinated neurodevelopment of connected brain regions. Although useful, structural covariance analysis predominantly employed bulky morphological measures with mixed compartments, whereas studies of the structural covariance of any specific subdivisions such as myelin are rare. Characterizing myelination covariance is of interest, as it will reveal connectivity patterns determined by coordinated development of myeloarchitecture between brain regions. Using myelin content MRI maps from the Human Connectome Project, here we showed that the cortical myelination covariance was highly reproducible, and exhibited a brain organization similar to that previously revealed by other connectivity measures. Additionally, the myelination covariance network shared common topological features of human brain networks such as small-worldness. Furthermore, we found that the correlation between myelination covariance and resting-state functional connectivity (RSFC) was uniform within each resting-state network (RSN), but could considerably vary across RSNs. Interestingly, this myelination covariance-RSFC correlation was appreciably stronger in sensory and motor networks than cognitive and polymodal association networks, possibly due to their different circuitry structures. This study has established a new brain connectivity measure specifically related to axons, and this measure can be valuable to investigating coordinated myeloarchitecture development. Hum Brain Mapp 38:4730-4743, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2011-01-01
The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.
Covariate-adjusted measures of discrimination for survival data
DEFF Research Database (Denmark)
White, Ian R; Rapsomaniki, Eleni; Frikke-Schmidt, Ruth
2015-01-01
by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination...... statistics in censored survival data. OBJECTIVE: To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s). METHOD: We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators......, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration. RESULTS: The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were...
Multiple feature fusion via covariance matrix for visual tracking
Jin, Zefenfen; Hou, Zhiqiang; Yu, Wangsheng; Wang, Xin; Sun, Hui
2018-04-01
Aiming at the problem of complicated dynamic scenes in visual target tracking, a multi-feature fusion tracking algorithm based on covariance matrix is proposed to improve the robustness of the tracking algorithm. In the frame-work of quantum genetic algorithm, this paper uses the region covariance descriptor to fuse the color, edge and texture features. It also uses a fast covariance intersection algorithm to update the model. The low dimension of region covariance descriptor, the fast convergence speed and strong global optimization ability of quantum genetic algorithm, and the fast computation of fast covariance intersection algorithm are used to improve the computational efficiency of fusion, matching, and updating process, so that the algorithm achieves a fast and effective multi-feature fusion tracking. The experiments prove that the proposed algorithm can not only achieve fast and robust tracking but also effectively handle interference of occlusion, rotation, deformation, motion blur and so on.
Parametric Covariance Model for Horizon-Based Optical Navigation
Hikes, Jacob; Liounis, Andrew J.; Christian, John A.
2016-01-01
This Note presents an entirely parametric version of the covariance for horizon-based optical navigation measurements. The covariance can be written as a function of only the spacecraft position, two sensor design parameters, the illumination direction, the size of the observed planet, the size of the lit arc to be used, and the total number of observed horizon points. As a result, one may now more clearly understand the sensitivity of horizon-based optical navigation performance as a function of these key design parameters, which is insight that was obscured in previous (and nonparametric) versions of the covariance. Finally, the new parametric covariance is shown to agree with both the nonparametric analytic covariance and results from a Monte Carlo analysis.
Structural covariance networks in the mouse brain.
Pagani, Marco; Bifone, Angelo; Gozzi, Alessandro
2016-04-01
The presence of networks of correlation between regional gray matter volume as measured across subjects in a group of individuals has been consistently described in several human studies, an approach termed structural covariance MRI (scMRI). Complementary to prevalent brain mapping modalities like functional and diffusion-weighted imaging, the approach can provide precious insights into the mutual influence of trophic and plastic processes in health and pathological states. To investigate whether analogous scMRI networks are present in lower mammal species amenable to genetic and experimental manipulation such as the laboratory mouse, we employed high resolution morphoanatomical MRI in a large cohort of genetically-homogeneous wild-type mice (C57Bl6/J) and mapped scMRI networks using a seed-based approach. We show that the mouse brain exhibits robust homotopic scMRI networks in both primary and associative cortices, a finding corroborated by independent component analyses of cortical volumes. Subcortical structures also showed highly symmetric inter-hemispheric correlations, with evidence of distributed antero-posterior networks in diencephalic regions of the thalamus and hypothalamus. Hierarchical cluster analysis revealed six identifiable clusters of cortical and sub-cortical regions corresponding to previously described neuroanatomical systems. Our work documents the presence of homotopic cortical and subcortical scMRI networks in the mouse brain, thus supporting the use of this species to investigate the elusive biological and neuroanatomical underpinnings of scMRI network development and its derangement in neuropathological states. The identification of scMRI networks in genetically homogeneous inbred mice is consistent with the emerging view of a key role of environmental factors in shaping these correlational networks. Copyright © 2016 Elsevier Inc. All rights reserved.
Covariant path integrals on hyperbolic surfaces
International Nuclear Information System (INIS)
Schaefer, J.
1997-01-01
DeWitt close-quote s covariant formulation of path integration [B. De Witt, open-quotes Dynamical theory in curved spaces. I. A review of the classical and quantum action principles,close quotes Rev. Mod. Phys. 29, 377 endash 397 (1957)] has two practical advantages over the traditional methods of open-quotes lattice approximations;close quotes there is no ordering problem, and classical symmetries are manifestly preserved at the quantum level. Applying the spectral theorem for unbounded self-adjoint operators, we provide a rigorous proof of the convergence of certain path integrals on Riemann surfaces of constant curvature -1. The Pauli endash DeWitt curvature correction term arises, as in DeWitt close-quote s work. Introducing a Fuchsian group Γ of the first kind, and a continuous, bounded, Γ-automorphic potential V, we obtain a Feynman endash Kac formula for the automorphic Schroedinger equation on the Riemann surface Γ backslash H. We analyze the Wick rotation and prove the strong convergence of the so-called Feynman maps [K. D. Elworthy, Path Integration on Manifolds, Mathematical Aspects of Superspace, edited by Seifert, Clarke, and Rosenblum (Reidel, Boston, 1983), pp. 47 endash 90] on a dense set of states. Finally, we give a new proof of some results in C. Grosche and F. Steiner, open-quotes The path integral on the Poincare upper half plane and for Liouville quantum mechanics,close quotes Phys. Lett. A 123, 319 endash 328 (1987). copyright 1997 American Institute of Physics
Schwinger mechanism in linear covariant gauges
Aguilar, A. C.; Binosi, D.; Papavassiliou, J.
2017-02-01
In this work we explore the applicability of a special gluon mass generating mechanism in the context of the linear covariant gauges. In particular, the implementation of the Schwinger mechanism in pure Yang-Mills theories hinges crucially on the inclusion of massless bound-state excitations in the fundamental nonperturbative vertices of the theory. The dynamical formation of such excitations is controlled by a homogeneous linear Bethe-Salpeter equation, whose nontrivial solutions have been studied only in the Landau gauge. Here, the form of this integral equation is derived for general values of the gauge-fixing parameter, under a number of simplifying assumptions that reduce the degree of technical complexity. The kernel of this equation consists of fully dressed gluon propagators, for which recent lattice data are used as input, and of three-gluon vertices dressed by a single form factor, which is modeled by means of certain physically motivated Ansätze. The gauge-dependent terms contributing to this kernel impose considerable restrictions on the infrared behavior of the vertex form factor; specifically, only infrared finite Ansätze are compatible with the existence of nontrivial solutions. When such Ansätze are employed, the numerical study of the integral equation reveals a continuity in the type of solutions as one varies the gauge-fixing parameter, indicating a smooth departure from the Landau gauge. Instead, the logarithmically divergent form factor displaying the characteristic "zero crossing," while perfectly consistent in the Landau gauge, has to undergo a dramatic qualitative transformation away from it, in order to yield acceptable solutions. The possible implications of these results are briefly discussed.
Impact of the 235U covariance data in benchmark calculations
International Nuclear Information System (INIS)
Leal, Luiz; Mueller, Don; Arbanas, Goran; Wiarda, Dorothea; Derrien, Herve
2008-01-01
The error estimation for calculated quantities relies on nuclear data uncertainty information available in the basic nuclear data libraries such as the U.S. Evaluated Nuclear Data File (ENDF/B). The uncertainty files (covariance matrices) in the ENDF/B library are generally obtained from analysis of experimental data. In the resonance region, the computer code SAMMY is used for analyses of experimental data and generation of resonance parameters. In addition to resonance parameters evaluation, SAMMY also generates resonance parameter covariance matrices (RPCM). SAMMY uses the generalized least-squares formalism (Bayes' method) together with the resonance formalism (R-matrix theory) for analysis of experimental data. Two approaches are available for creation of resonance-parameter covariance data. (1) During the data-evaluation process, SAMMY generates both a set of resonance parameters that fit the experimental data and the associated resonance-parameter covariance matrix. (2) For existing resonance-parameter evaluations for which no resonance-parameter covariance data are available, SAMMY can retroactively create a resonance-parameter covariance matrix. The retroactive method was used to generate covariance data for 235 U. The resulting 235 U covariance matrix was then used as input to the PUFF-IV code, which processed the covariance data into multigroup form, and to the TSUNAMI code, which calculated the uncertainty in the multiplication factor due to uncertainty in the experimental cross sections. The objective of this work is to demonstrate the use of the 235 U covariance data in calculations of critical benchmark systems. (authors)
A New Approach for Nuclear Data Covariance and Sensitivity Generation
International Nuclear Information System (INIS)
Leal, L.C.; Larson, N.M.; Derrien, H.; Kawano, T.; Chadwick, M.B.
2005-01-01
Covariance data are required to correctly assess uncertainties in design parameters in nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the U.S. Evaluated Nuclear Data File, ENDF/B. The uncertainty files in the ENDF/B library are obtained from the analysis of experimental data and are stored as variance and covariance data. The computer code SAMMY is used in the analysis of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on generalized least-squares formalism (Bayes' theory) together with the resonance formalism described by R-matrix theory. Two approaches are used in SAMMY for the generation of resonance-parameter covariance data. In the evaluation process SAMMY generates a set of resonance parameters that fit the data, and, in addition, it also provides the resonance-parameter covariances. For existing resonance-parameter evaluations where no resonance-parameter covariance data are available, the alternative is to use an approach called the 'retroactive' resonance-parameter covariance generation. In the high-energy region the methodology for generating covariance data consists of least-squares fitting and model parameter adjustment. The least-squares fitting method calculates covariances directly from experimental data. The parameter adjustment method employs a nuclear model calculation such as the optical model and the Hauser-Feshbach model, and estimates a covariance for the nuclear model parameters. In this paper we describe the application of the retroactive method and the parameter adjustment method to generate covariance data for the gadolinium isotopes
Galaxy-galaxy lensing estimators and their covariance properties
Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uroš; Slosar, Anže; Vazquez Gonzalez, Jose
2017-11-01
We study the covariance properties of real space correlation function estimators - primarily galaxy-shear correlations, or galaxy-galaxy lensing - using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.
Graphical representation of covariant-contravariant modal formulae
Directory of Open Access Journals (Sweden)
Miguel Palomino
2011-08-01
Full Text Available Covariant-contravariant simulation is a combination of standard (covariant simulation, its contravariant counterpart and bisimulation. We have previously studied its logical characterization by means of the covariant-contravariant modal logic. Moreover, we have investigated the relationships between this model and that of modal transition systems, where two kinds of transitions (the so-called may and must transitions were combined in order to obtain a simple framework to express a notion of refinement over state-transition models. In a classic paper, Boudol and Larsen established a precise connection between the graphical approach, by means of modal transition systems, and the logical approach, based on Hennessy-Milner logic without negation, to system specification. They obtained a (graphical representation theorem proving that a formula can be represented by a term if, and only if, it is consistent and prime. We show in this paper that the formulae from the covariant-contravariant modal logic that admit a "graphical" representation by means of processes, modulo the covariant-contravariant simulation preorder, are also the consistent and prime ones. In order to obtain the desired graphical representation result, we first restrict ourselves to the case of covariant-contravariant systems without bivariant actions. Bivariant actions can be incorporated later by means of an encoding that splits each bivariant action into its covariant and its contravariant parts.
Using machine learning to assess covariate balance in matching studies.
Linden, Ariel; Yarnold, Paul R
2016-12-01
In order to assess the effectiveness of matching approaches in observational studies, investigators typically present summary statistics for each observed pre-intervention covariate, with the objective of showing that matching reduces the difference in means (or proportions) between groups to as close to zero as possible. In this paper, we introduce a new approach to distinguish between study groups based on their distributions of the covariates using a machine-learning algorithm called optimal discriminant analysis (ODA). Assessing covariate balance using ODA as compared with the conventional method has several key advantages: the ability to ascertain how individuals self-select based on optimal (maximum-accuracy) cut-points on the covariates; the application to any variable metric and number of groups; its insensitivity to skewed data or outliers; and the use of accuracy measures that can be widely applied to all analyses. Moreover, ODA accepts analytic weights, thereby extending the assessment of covariate balance to any study design where weights are used for covariate adjustment. By comparing the two approaches using empirical data, we are able to demonstrate that using measures of classification accuracy as balance diagnostics produces highly consistent results to those obtained via the conventional approach (in our matched-pairs example, ODA revealed a weak statistically significant relationship not detected by the conventional approach). Thus, investigators should consider ODA as a robust complement, or perhaps alternative, to the conventional approach for assessing covariate balance in matching studies. © 2016 John Wiley & Sons, Ltd.
Galaxy–galaxy lensing estimators and their covariance properties
International Nuclear Information System (INIS)
Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uros; Slosar, Anze; Gonzalez, Jose Vazquez
2017-01-01
Here, we study the covariance properties of real space correlation function estimators – primarily galaxy–shear correlations, or galaxy–galaxy lensing – using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.
Covarient quantization of heterotic strings in supersymmetric chiral boson formulation
International Nuclear Information System (INIS)
Yu, F.
1992-01-01
This dissertation presents the covariant supersymmetric chiral boson formulation of the heterotic strings. The main feature of this formulation is the covariant quantization of the so-called leftons and rightons -- the (1,0) supersymmetric generalizations of the world-sheet chiral bosons -- that constitute basic building blocks of general heterotic-type string models. Although the (Neveu-Schwarz-Ramond or Green-Schwarz) heterotic strings provide the most realistic string models, their covariant quantization, with the widely-used Siegel formalism, has never been rigorously carried out. It is clarified in this dissertation that the covariant Siegel formalism is pathological upon quantization. As a test, a general classical covariant (NSR) heterotic string action that has the Siegel symmetry is constructed in arbitrary curved space-time coupled to (1,0) world-sheet super-gravity. In the light-cone gauge quantization, the critical dimensions are derived for such an action with leftons and rightons compactified on group manifolds G L x G R . The covariant quantization of this action does not agree with the physical results in the light-cone gauge quantization. This dissertation establishes a new formalism for the covariant quantization of heterotic strings. The desired consistent covariant path integral quantization of supersymmetric chiral bosons, and thus the general (NSR) heterotic-type strings with leftons and rightons compactified on torus circle-times d L S 1 x circle-times d R S 1 are carried out. An infinite set of auxiliary (1,0) scalar superfields is introduced to convert the second-class chiral constraint into first-class ones. The covariant gauge-fixed action has an extended BRST symmetry described by the graded algebra GL(1/1). A regularization respecting this symmetry is proposed to deal with the contributions of the infinite towers of auxiliary fields and associated ghosts
More on Estimation of Banded and Banded Toeplitz Covariance Matrices
Berntsson, Fredrik; Ohlson, Martin
2017-01-01
In this paper we consider two different linear covariance structures, e.g., banded and bended Toeplitz, and how to estimate them using different methods, e.g., by minimizing different norms. One way to estimate the parameters in a linear covariance structure is to use tapering, which has been shown to be the solution to a universal least squares problem. We know that tapering not always guarantee the positive definite constraints on the estimated covariance matrix and may not be a suitable me...
Covariance matrices and applications to the field of nuclear data
International Nuclear Information System (INIS)
Smith, D.L.
1981-11-01
A student's introduction to covariance error analysis and least-squares evaluation of data is provided. It is shown that the basic formulas used in error propagation can be derived from a consideration of the geometry of curvilinear coordinates. Procedures for deriving covariances for scaler and vector functions of several variables are presented. Proper methods for reporting experimental errors and for deriving covariance matrices from these errors are indicated. The generalized least-squares method for evaluating experimental data is described. Finally, the use of least-squares techniques in data fitting applications is discussed. Specific examples of the various procedures are presented to clarify the concepts
The utility of covariance of combining ability in plant breeding.
Arunachalam, V
1976-11-01
The definition of covariances of half- and full sibs, and hence that of variances of general and specific combining ability with regard to a quantitative character, is extended to take into account the respective covariances between a pair of characters. The interpretation of the dispersion and correlation matrices of general and specific combining ability is discussed by considering a set of single, three- and four-way crosses, made using diallel and line × tester mating systems in Pennisetum typhoides. The general implications of the concept of covariance of combining ability in plant breeding are discussed.
Asset allocation with different covariance/correlation estimators
Μανταφούνη, Σοφία
2007-01-01
The subject of the study is to test whether the use of different covariance – correlation estimators than the historical covariance matrix that is widely used, would help in portfolio optimization through the mean-variance analysis. In other words, if an investor would like to use the mean-variance analysis in order to invest in assets like stocks or indices, would it be of some help to use more sophisticated estimators for the covariance matrix of the returns of his portfolio? The procedure ...
Covariant effective action for loop quantum cosmology from order reduction
International Nuclear Information System (INIS)
Sotiriou, Thomas P.
2009-01-01
Loop quantum cosmology (LQC) seems to be predicting modified effective Friedmann equations without extra degrees of freedom. A puzzle arises if one decides to seek for a covariant effective action which would lead to the given Friedmann equation: The Einstein-Hilbert action is the only action that leads to second order field equations and, hence, there exists no covariant action which, under metric variation, leads to a modified Friedmann equation without extra degrees of freedom. It is shown that, at least for isotropic models in LQC, this issue is naturally resolved and a covariant effective action can be found if one considers higher order theories of gravity but faithfully follows effective field theory techniques. However, our analysis also raises doubts on whether a covariant description without background structures can be found for anisotropic models.
Nonrelativistic fluids on scale covariant Newton-Cartan backgrounds
Mitra, Arpita
2017-12-01
The nonrelativistic covariant framework for fields is extended to investigate fields and fluids on scale covariant curved backgrounds. The scale covariant Newton-Cartan background is constructed using the localization of space-time symmetries of nonrelativistic fields in flat space. Following this, we provide a Weyl covariant formalism which can be used to study scale invariant fluids. By considering ideal fluids as an example, we describe its thermodynamic and hydrodynamic properties and explicitly demonstrate that it satisfies the local second law of thermodynamics. As a further application, we consider the low energy description of Hall fluids. Specifically, we find that the gauge fields for scale transformations lead to corrections of the Wen-Zee and Berry phase terms contained in the effective action.
Partially linear varying coefficient models stratified by a functional covariate
Maity, Arnab; Huang, Jianhua Z.
2012-01-01
We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric
Coherent states and covariant semi-spectral measures
International Nuclear Information System (INIS)
Scutaru, H.
1976-01-01
The close connection between Mackey's theory of imprimitivity systems and the so called generalized coherent states introduced by Perelomov is established. Coherent states give a covariant description of the ''localization'' of a quantum system in the phase space in a similar way as the imprimitivity systems give a covariant description of the localization of a quantum system in the configuration space. The observation that for any system of coherent states one can define a covariant semi-spectral measure made possible a rigurous formulation of this idea. A generalization of the notion of coherent states is given. Covariant semi-spectral measures associated with systems of coherent states are defined and characterized. Necessary and sufficient conditions for a unitary representation of a Lie group to be i) a subrepresentation of an induced one and ii) a representation with coherent states are given (author)
The critical dimensions of parastrings from the covariant formalism
International Nuclear Information System (INIS)
Belyea, C.I.; Warner, R.C.
1989-10-01
The critical dimensions of first-quantized parastrings by the covariant method is presented. An apparent disagreement with previous light-cone results of Mansouri and coworkers was found. A possible interpretation of the discrepancy is offered. 11 refs
Revealing hidden covariation detection: evidence for implicit abstraction at study.
Rossnagel, C S
2001-09-01
Four experiments in the brain scans paradigm (P. Lewicki, T. Hill, & I. Sasaki, 1989) investigated hidden covariation detection (HCD). In Experiment 1 HCD was found in an implicit- but not in an explicit-instruction group. In Experiment 2 HCD was impaired by nonholistic perception of stimuli but not by divided attention. In Experiment 3 HCD was eliminated by interspersing stimuli that deviated from the critical covariation. In Experiment 4 a transfer procedure was used. HCD was found with dissimilar test stimuli that preserved the covariation but was almost eliminated with similar stimuli that were neutral as to the covariation. Awareness was assessed both by objective and subjective tests in all experiments. Results suggest that HCD is an effect of implicit rule abstraction and that similarity processing plays only a minor role. HCD might be suppressed by intentional search strategies that induce inappropriate aggregation of stimulus information.
Using Covariant Lyapunov Vectors to Understand Spatiotemporal Chaos in Fluids
Paul, Mark; Xu, Mu; Barbish, Johnathon; Mukherjee, Saikat
2017-11-01
The spatiotemporal chaos of fluids present many difficult and fascinating challenges. Recent progress in computing covariant Lyapunov vectors for a variety of model systems has made it possible to probe fundamental ideas from dynamical systems theory including the degree of hyperbolicity, the fractal dimension, the dimension of the inertial manifold, and the decomposition of the dynamics into a finite number of physical modes and spurious modes. We are interested in building upon insights such as these for fluid systems. We first demonstrate the power of covariant Lyapunov vectors using a system of maps on a lattice with a nonlinear coupling. We then compute the covariant Lyapunov vectors for chaotic Rayleigh-Bénard convection for experimentally accessible conditions. We show that chaotic convection is non-hyperbolic and we quantify the spatiotemporal features of the spectrum of covariant Lyapunov vectors. NSF DMS-1622299 and DARPA/DSO Models, Dynamics, and Learning (MoDyL).
Visualization and assessment of spatio-temporal covariance properties
Huang, Huang; Sun, Ying
2017-01-01
approach that constructs test functions using the cross-covariances from time series observed at each pair of spatial locations. These test functions of temporal lags summarize the properties of separability or symmetry for the given spatial pairs. We use
Lorentz covariant canonical symplectic algorithms for dynamics of charged particles
Wang, Yulei; Liu, Jian; Qin, Hong
2016-12-01
In this paper, the Lorentz covariance of algorithms is introduced. Under Lorentz transformation, both the form and performance of a Lorentz covariant algorithm are invariant. To acquire the advantages of symplectic algorithms and Lorentz covariance, a general procedure for constructing Lorentz covariant canonical symplectic algorithms (LCCSAs) is provided, based on which an explicit LCCSA for dynamics of relativistic charged particles is built. LCCSA possesses Lorentz invariance as well as long-term numerical accuracy and stability, due to the preservation of a discrete symplectic structure and the Lorentz symmetry of the system. For situations with time-dependent electromagnetic fields, which are difficult to handle in traditional construction procedures of symplectic algorithms, LCCSA provides a perfect explicit canonical symplectic solution by implementing the discretization in 4-spacetime. We also show that LCCSA has built-in energy-based adaptive time steps, which can optimize the computation performance when the Lorentz factor varies.
Representation of Gaussian semimartingales with applications to the covariance function
DEFF Research Database (Denmark)
Basse-O'Connor, Andreas
2010-01-01
stationary Gaussian semimartingales and their canonical decomposition. Thirdly, we give a new characterization of the covariance function of Gaussian semimartingales, which enable us to characterize the class of martingales and the processes of bounded variation among the Gaussian semimartingales. We...
An Information-Theoretic Justification for Covariance Intersectionand Its Generalization
National Research Council Canada - National Science Library
Hurley, Michael
2001-01-01
.... that addresses the problems that arise from fusing correlated measurements. The researchers have named this technique 'covariance intersection' and have presented papers on it at several robotics and control theory conferences...
Video based object representation and classification using multiple covariance matrices.
Zhang, Yurong; Liu, Quan
2017-01-01
Video based object recognition and classification has been widely studied in computer vision and image processing area. One main issue of this task is to develop an effective representation for video. This problem can generally be formulated as image set representation. In this paper, we present a new method called Multiple Covariance Discriminative Learning (MCDL) for image set representation and classification problem. The core idea of MCDL is to represent an image set using multiple covariance matrices with each covariance matrix representing one cluster of images. Firstly, we use the Nonnegative Matrix Factorization (NMF) method to do image clustering within each image set, and then adopt Covariance Discriminative Learning on each cluster (subset) of images. At last, we adopt KLDA and nearest neighborhood classification method for image set classification. Promising experimental results on several datasets show the effectiveness of our MCDL method.
Generalized Extreme Value model with Cyclic Covariate Structure ...
Indian Academy of Sciences (India)
48
enhances the estimation of the return period; however, its application is ...... Cohn T A and Lins H F 2005 Nature's style: Naturally trendy; GEOPHYSICAL ..... Final non-stationary GEV models with covariate structures shortlisted based on.
Optimal covariance selection for estimation using graphical models
Vichik, Sergey; Oshman, Yaakov
2011-01-01
We consider a problem encountered when trying to estimate a Gaussian random field using a distributed estimation approach based on Gaussian graphical models. Because of constraints imposed by estimation tools used in Gaussian graphical models, the a priori covariance of the random field is constrained to embed conditional independence constraints among a significant number of variables. The problem is, then: given the (unconstrained) a priori covariance of the random field, and the conditiona...
Astrophysical tests of scale-covariant gravity theories
International Nuclear Information System (INIS)
Mansfield, V.N.; Malin, S.
1980-01-01
Starting from the most general form of the conservation laws in scale-covariant gravitation theory, a conservation of energy equation appropriate for stars is derived. Applications to white dwarfs and neutron stars reveal serious difficulties for some choices of gauge that have been frequently employed in the literature on scale-covariant gravity. We also show how to restrict some of the possible gauges that result from theories which are independent of the Large Numbers Hypothesis
Abnormalities in structural covariance of cortical gyrification in schizophrenia
Palaniyappan, Lena; Park, Bert; Balain, Vijender; Dangi, Raj; Liddle, Peter
2014-01-01
The highly convoluted shape of the adult human brain results from several well-coordinated maturational events that start from embryonic development and extend through the adult life span. Disturbances in these maturational events can result in various neurological and psychiatric disorders, resulting in abnormal patterns of morphological relationship among cortical structures (structural covariance). Structural covariance can be studied using graph theory-based approaches that evaluate topol...
Are the invariance principles really truly Lorentz covariant?
International Nuclear Information System (INIS)
Arunasalam, V.
1994-02-01
It is shown that some sections of the invariance (or symmetry) principles such as the space reversal symmetry (or parity P) and time reversal symmetry T (of elementary particle and condensed matter physics, etc.) are not really truly Lorentz covariant. Indeed, I find that the Dirac-Wigner sense of Lorentz invariance is not in full compliance with the Einstein-Minkowski reguirements of the Lorentz covariance of all physical laws (i.e., the world space Mach principle)
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
A Generalized Autocovariance Least-Squares Method for Covariance Estimation
DEFF Research Database (Denmark)
Åkesson, Bernt Magnus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad
2007-01-01
A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter.......A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter....
The Performance Analysis Based on SAR Sample Covariance Matrix
Directory of Open Access Journals (Sweden)
Esra Erten
2012-03-01
Full Text Available Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given.
Conformally covariant massless spin-two field equations
International Nuclear Information System (INIS)
Drew, M.S.; Gegenberg, J.D.
1980-01-01
An explicit proof is constructed to show that the field equations for a symmetric tensor field hsub(ab) describing massless spin-2 particles in Minkowski space-time are not covariant under the 15-parameter group SOsub(4,2); this group is usually associated with conformal transformations on flat space, and here it will be considered as a global gauge group which acts upon matter fields defined on space-time. Notwithstanding the above noncovariance, the equations governing the rank-4 tensor Ssub(abcd) constructed from hsub(ab) are shown to be covariant provided the contraction Ssub(ab) vanishes. Conformal covariance is proved by demonstrating the covariance of the equations for the equivalent 5-component complex field; in fact, covariance is proved for a general field equation applicable to massless particles of any spin >0. It is shown that the noncovariance of the hsub(ab) equations may be ascribed to the fact that the transformation behaviour of hsub(ab) is not the same as that of a field consisting of a gauge only. Since this is in contradistinction to the situation for the electromagnetic-field equations, the vector form of the electromagnetic equations is cast into a form which can be duplicated for the hsub(ab)-field. This procedure results in an alternative, covariant, field equation for hsub(ab). (author)
Large Covariance Estimation by Thresholding Principal Orthogonal Complements
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2012-01-01
This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented. PMID:24348088
Visualization and assessment of spatio-temporal covariance properties
Huang, Huang
2017-11-23
Spatio-temporal covariances are important for describing the spatio-temporal variability of underlying random fields in geostatistical data. For second-order stationary random fields, there exist subclasses of covariance functions that assume a simpler spatio-temporal dependence structure with separability and full symmetry. However, it is challenging to visualize and assess separability and full symmetry from spatio-temporal observations. In this work, we propose a functional data analysis approach that constructs test functions using the cross-covariances from time series observed at each pair of spatial locations. These test functions of temporal lags summarize the properties of separability or symmetry for the given spatial pairs. We use functional boxplots to visualize the functional median and the variability of the test functions, where the extent of departure from zero at all temporal lags indicates the degree of non-separability or asymmetry. We also develop a rank-based nonparametric testing procedure for assessing the significance of the non-separability or asymmetry. Essentially, the proposed methods only require the analysis of temporal covariance functions. Thus, a major advantage over existing approaches is that there is no need to estimate any covariance matrix for selected spatio-temporal lags. The performances of the proposed methods are examined by simulations with various commonly used spatio-temporal covariance models. To illustrate our methods in practical applications, we apply it to real datasets, including weather station data and climate model outputs.
Covariance fitting of highly-correlated data in lattice QCD
Yoon, Boram; Jang, Yong-Chull; Jung, Chulwoo; Lee, Weonjong
2013-07-01
We address a frequently-asked question on the covariance fitting of highly-correlated data such as our B K data based on the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have a fitting function accurate enough to fit extremely precise data. When eigenvalues of the covariance matrix are small, even a tiny error in the fitting function yields a large chi-square value and spoils the fitting procedure. We have applied a number of prescriptions available in the market, such as the cut-off method, modified covariance matrix method, and Bayesian method. We also propose a brand new method, the eigenmode shift (ES) method, which allows a full covariance fitting without modifying the covariance matrix at all. We provide a pedagogical example of data analysis in which the cut-off method manifestly fails in fitting, but the rest work well. In our case of the B K fitting, the diagonal approximation, the cut-off method, the ES method, and the Bayesian method work reasonably well in an engineering sense. However, interpreting the meaning of χ 2 is easier in the case of the ES method and the Bayesian method in a theoretical sense aesthetically. Hence, the ES method can be a useful alternative optional tool to check the systematic error caused by the covariance fitting procedure.
Massive data compression for parameter-dependent covariance matrices
Heavens, Alan F.; Sellentin, Elena; de Mijolla, Damien; Vianello, Alvise
2017-12-01
We show how the massive data compression algorithm MOPED can be used to reduce, by orders of magnitude, the number of simulated data sets which are required to estimate the covariance matrix required for the analysis of Gaussian-distributed data. This is relevant when the covariance matrix cannot be calculated directly. The compression is especially valuable when the covariance matrix varies with the model parameters. In this case, it may be prohibitively expensive to run enough simulations to estimate the full covariance matrix throughout the parameter space. This compression may be particularly valuable for the next generation of weak lensing surveys, such as proposed for Euclid and Large Synoptic Survey Telescope, for which the number of summary data (such as band power or shear correlation estimates) is very large, ∼104, due to the large number of tomographic redshift bins which the data will be divided into. In the pessimistic case where the covariance matrix is estimated separately for all points in an Monte Carlo Markov Chain analysis, this may require an unfeasible 109 simulations. We show here that MOPED can reduce this number by a factor of 1000, or a factor of ∼106 if some regularity in the covariance matrix is assumed, reducing the number of simulations required to a manageable 103, making an otherwise intractable analysis feasible.
Large Covariance Estimation by Thresholding Principal Orthogonal Complements.
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2013-09-01
This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented.
Real-time probabilistic covariance tracking with efficient model update.
Wu, Yi; Cheng, Jian; Wang, Jinqiao; Lu, Hanqing; Wang, Jun; Ling, Haibin; Blasch, Erik; Bai, Li
2012-05-01
The recently proposed covariance region descriptor has been proven robust and versatile for a modest computational cost. The covariance matrix enables efficient fusion of different types of features, where the spatial and statistical properties, as well as their correlation, are characterized. The similarity between two covariance descriptors is measured on Riemannian manifolds. Based on the same metric but with a probabilistic framework, we propose a novel tracking approach on Riemannian manifolds with a novel incremental covariance tensor learning (ICTL). To address the appearance variations, ICTL incrementally learns a low-dimensional covariance tensor representation and efficiently adapts online to appearance changes of the target with only O(1) computational complexity, resulting in a real-time performance. The covariance-based representation and the ICTL are then combined with the particle filter framework to allow better handling of background clutter, as well as the temporary occlusions. We test the proposed probabilistic ICTL tracker on numerous benchmark sequences involving different types of challenges including occlusions and variations in illumination, scale, and pose. The proposed approach demonstrates excellent real-time performance, both qualitatively and quantitatively, in comparison with several previously proposed trackers.
A three domain covariance framework for EEG/MEG data.
Roś, Beata P; Bijma, Fetsje; de Gunst, Mathisca C M; de Munck, Jan C
2015-10-01
In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three components that correspond to space, time and epochs/trials, and consider maximum likelihood estimation of the unknown parameter values. An iterative algorithm that finds approximations of the maximum likelihood estimates is proposed. Our covariance model is applicable in a variety of cases where spontaneous EEG or MEG acts as source of noise and realistic noise covariance estimates are needed, such as in evoked activity studies, or where the properties of spontaneous EEG or MEG are themselves the topic of interest, like in combined EEG-fMRI experiments in which the correlation between EEG and fMRI signals is investigated. We use a simulation study to assess the performance of the estimator and investigate the influence of different assumptions about the covariance factors on the estimated covariance matrix and on its components. We apply our method to real EEG and MEG data sets. Copyright © 2015 Elsevier Inc. All rights reserved.
Summary of the Workshop on Neutron Cross Section Covariances
International Nuclear Information System (INIS)
Smith, Donald L.
2008-01-01
A Workshop on Neutron Cross Section Covariances was held from June 24-27, 2008, in Port Jefferson, New York. This Workshop was organized by the National Nuclear Data Center, Brookhaven National Laboratory, to provide a forum for reporting on the status of the growing field of neutron cross section covariances for applications and for discussing future directions of the work in this field. The Workshop focused on the following four major topical areas: covariance methodology, recent covariance evaluations, covariance applications, and user perspectives. Attention was given to the entire spectrum of neutron cross section covariance concerns ranging from light nuclei to the actinides, and from the thermal energy region to 20 MeV. The papers presented at this conference explored topics ranging from fundamental nuclear physics concerns to very specific applications in advanced reactor design and nuclear criticality safety. This paper provides a summary of this workshop. Brief comments on the highlights of each Workshop contribution are provided. In addition, a perspective on the achievements and shortcomings of the Workshop as well as on the future direction of research in this field is offered
Updated Covariance Processing Capabilities in the AMPX Code System
International Nuclear Information System (INIS)
Wiarda, Dorothea; Dunn, Michael E.
2007-01-01
A concerted effort is in progress within the nuclear data community to provide new cross-section covariance data evaluations to support sensitivity/uncertainty analyses of fissionable systems. The objective of this work is to update processing capabilities of the AMPX library to process the latest Evaluated Nuclear Data File (ENDF)/B formats to generate covariance data libraries for radiation transport software such as SCALE. The module PUFF-IV was updated to allow processing of new ENDF covariance formats in the resolved resonance region. In the resolved resonance region, covariance matrices are given in terms of resonance parameters, which need to be processed into covariance matrices with respect to the group-averaged cross-section data. The parameter covariance matrix can be quite large if the evaluation has many resonances. The PUFF-IV code has recently been used to process an evaluation of 235U, which was prepared in collaboration between Oak Ridge National Laboratory and Los Alamos National Laboratory.
Alterations in Anatomical Covariance in the Prematurely Born.
Scheinost, Dustin; Kwon, Soo Hyun; Lacadie, Cheryl; Vohr, Betty R; Schneider, Karen C; Papademetris, Xenophon; Constable, R Todd; Ment, Laura R
2017-01-01
Preterm (PT) birth results in long-term alterations in functional and structural connectivity, but the related changes in anatomical covariance are just beginning to be explored. To test the hypothesis that PT birth alters patterns of anatomical covariance, we investigated brain volumes of 25 PTs and 22 terms at young adulthood using magnetic resonance imaging. Using regional volumetrics, seed-based analyses, and whole brain graphs, we show that PT birth is associated with reduced volume in bilateral temporal and inferior frontal lobes, left caudate, left fusiform, and posterior cingulate for prematurely born subjects at young adulthood. Seed-based analyses demonstrate altered patterns of anatomical covariance for PTs compared with terms. PTs exhibit reduced covariance with R Brodmann area (BA) 47, Broca's area, and L BA 21, Wernicke's area, and white matter volume in the left prefrontal lobe, but increased covariance with R BA 47 and left cerebellum. Graph theory analyses demonstrate that measures of network complexity are significantly less robust in PTs compared with term controls. Volumes in regions showing group differences are significantly correlated with phonological awareness, the fundamental basis for reading acquisition, for the PTs. These data suggest both long-lasting and clinically significant alterations in the covariance in the PTs at young adulthood. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Covariance NMR Processing and Analysis for Protein Assignment.
Harden, Bradley J; Frueh, Dominique P
2018-01-01
During NMR resonance assignment it is often necessary to relate nuclei to one another indirectly, through their common correlations to other nuclei. Covariance NMR has emerged as a powerful technique to correlate such nuclei without relying on error-prone peak peaking. However, false-positive artifacts in covariance spectra have impeded a general application to proteins. We recently introduced pre- and postprocessing steps to reduce the prevalence of artifacts in covariance spectra, allowing for the calculation of a variety of 4D covariance maps obtained from diverse combinations of pairs of 3D spectra, and we have employed them to assign backbone and sidechain resonances in two large and challenging proteins. In this chapter, we present a detailed protocol describing how to (1) properly prepare existing 3D spectra for covariance, (2) understand and apply our processing script, and (3) navigate and interpret the resulting 4D spectra. We also provide solutions to a number of errors that may occur when using our script, and we offer practical advice when assigning difficult signals. We believe such 4D spectra, and covariance NMR in general, can play an integral role in the assignment of NMR signals.
Covariant description of Hamiltonian form for field dynamics
International Nuclear Information System (INIS)
Ozaki, Hiroshi
2005-01-01
Hamiltonian form of field dynamics is developed on a space-like hypersurface in space-time. A covariant Poisson bracket on the space-like hypersurface is defined and it plays a key role to describe every algebraic relation into a covariant form. It is shown that the Poisson bracket has the same symplectic structure that was brought in the covariant symplectic approach. An identity invariant under the canonical transformations is obtained. The identity follows a canonical equation in which the interaction Hamiltonian density generates a deformation of the space-like hypersurface. The equation just corresponds to the Yang-Feldman equation in the Heisenberg pictures in quantum field theory. By converting the covariant Poisson bracket on the space-like hypersurface to four-dimensional commutator, we can pass over to quantum field theory in the Heisenberg picture without spoiling the explicit relativistic covariance. As an example the canonical QCD is displayed in a covariant way on a space-like hypersurface
Matérn-based nonstationary cross-covariance models for global processes
Jun, Mikyoung
2014-01-01
-covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters
Quarkonia and heavy-light mesons in a covariant quark model
Directory of Open Access Journals (Sweden)
Leitão Sofia
2016-01-01
Full Text Available Preliminary calculations using the Covariant Spectator Theory (CST employed a scalar linear confining interaction and an additional constant vector potential to compute the mesonic mass spectra. In this work we generalize the confining interaction to include more general structures, in particular a vector and also a pseudoscalar part, as suggested by a recent study [1]. A one-gluon-exchange kernel is also implemented to describe the short-range part of the interaction. We solve the simplest CST approximation to the complete Bethe-Salpeter equation, the one-channel spectator equation, using a numerical technique that eliminates all singularities from the kernel. The parameters of the model are determined through a fit to the experimental pseudoscalar meson spectra, with a good agreement for both quarkonia and heavy-light states.
Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity.
Chang, Jinyuan; Zheng, Chao; Zhou, Wen-Xin; Zhou, Wen
2017-12-01
In this article, we study the problem of testing the mean vectors of high dimensional data in both one-sample and two-sample cases. The proposed testing procedures employ maximum-type statistics and the parametric bootstrap techniques to compute the critical values. Different from the existing tests that heavily rely on the structural conditions on the unknown covariance matrices, the proposed tests allow general covariance structures of the data and therefore enjoy wide scope of applicability in practice. To enhance powers of the tests against sparse alternatives, we further propose two-step procedures with a preliminary feature screening step. Theoretical properties of the proposed tests are investigated. Through extensive numerical experiments on synthetic data sets and an human acute lymphoblastic leukemia gene expression data set, we illustrate the performance of the new tests and how they may provide assistance on detecting disease-associated gene-sets. The proposed methods have been implemented in an R-package HDtest and are available on CRAN. © 2017, The International Biometric Society.
An Empirical State Error Covariance Matrix for Batch State Estimation
Frisbee, Joseph H., Jr.
2011-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the
Covariance problem in two-dimensional quantum chromodynamics
International Nuclear Information System (INIS)
Hagen, C.R.
1979-01-01
The problem of covariance in the field theory of a two-dimensional non-Abelian gauge field is considered. Since earlier work has shown that covariance fails (in charged sectors) for the Schwinger model, particular attention is given to an evaluation of the role played by the non-Abelian nature of the fields. In contrast to all earlier attempts at this problem, it is found that the potential covariance-breaking terms are identical to those found in the Abelian theory provided that one expresses them in terms of the total (i.e., conserved) current operator. The question of covariance is thus seen to reduce in all cases to a determination as to whether there exists a conserved global charge in the theory. Since the charge operator in the Schwinger model is conserved only in neutral sectors, one is thereby led to infer a probable failure of covariance in the non-Abelian theory, but one which is identical to that found for the U(1) case
Cross-covariance based global dynamic sensitivity analysis
Shi, Yan; Lu, Zhenzhou; Li, Zhao; Wu, Mengmeng
2018-02-01
For identifying the cross-covariance source of dynamic output at each time instant for structural system involving both input random variables and stochastic processes, a global dynamic sensitivity (GDS) technique is proposed. The GDS considers the effect of time history inputs on the dynamic output. In the GDS, the cross-covariance decomposition is firstly developed to measure the contribution of the inputs to the output at different time instant, and an integration of the cross-covariance change over the specific time interval is employed to measure the whole contribution of the input to the cross-covariance of output. Then, the GDS main effect indices and the GDS total effect indices can be easily defined after the integration, and they are effective in identifying the important inputs and the non-influential inputs on the cross-covariance of output at each time instant, respectively. The established GDS analysis model has the same form with the classical ANOVA when it degenerates to the static case. After degeneration, the first order partial effect can reflect the individual effects of inputs to the output variance, and the second order partial effect can reflect the interaction effects to the output variance, which illustrates the consistency of the proposed GDS indices and the classical variance-based sensitivity indices. The MCS procedure and the Kriging surrogate method are developed to solve the proposed GDS indices. Several examples are introduced to illustrate the significance of the proposed GDS analysis technique and the effectiveness of the proposed solution.
Structural and Maturational Covariance in Early Childhood Brain Development.
Geng, Xiujuan; Li, Gang; Lu, Zhaohua; Gao, Wei; Wang, Li; Shen, Dinggang; Zhu, Hongtu; Gilmore, John H
2017-03-01
Brain structural covariance networks (SCNs) composed of regions with correlated variation are altered in neuropsychiatric disease and change with age. Little is known about the development of SCNs in early childhood, a period of rapid cortical growth. We investigated the development of structural and maturational covariance networks, including default, dorsal attention, primary visual and sensorimotor networks in a longitudinal population of 118 children after birth to 2 years old and compared them with intrinsic functional connectivity networks. We found that structural covariance of all networks exhibit strong correlations mostly limited to their seed regions. By Age 2, default and dorsal attention structural networks are much less distributed compared with their functional maps. The maturational covariance maps, however, revealed significant couplings in rates of change between distributed regions, which partially recapitulate their functional networks. The structural and maturational covariance of the primary visual and sensorimotor networks shows similar patterns to the corresponding functional networks. Results indicate that functional networks are in place prior to structural networks, that correlated structural patterns in adult may arise in part from coordinated cortical maturation, and that regional co-activation in functional networks may guide and refine the maturation of SCNs over childhood development. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Criteria of the validation of experimental and evaluated covariance data
International Nuclear Information System (INIS)
Badikov, S.
2008-01-01
The criteria of the validation of experimental and evaluated covariance data are reviewed. In particular: a) the criterion of the positive definiteness for covariance matrices, b) the relationship between the 'integral' experimental and estimated uncertainties, c) the validity of the statistical invariants, d) the restrictions imposed to correlations between experimental errors, are described. Applying these criteria in nuclear data evaluation was considered and 4 particular points have been examined. First preserving positive definiteness of covariance matrices in case of arbitrary transformation of a random vector was considered, properties of the covariance matrices in operations widely used in neutron and reactor physics (splitting and collapsing energy groups, averaging the physical values over energy groups, estimation parameters on the basis of measurements by means of generalized least squares method) were studied. Secondly, an algorithm for comparison of experimental and estimated 'integral' uncertainties was developed, square root of determinant of a covariance matrix is recommended for use in nuclear data evaluation as a measure of 'integral' uncertainty for vectors of experimental and estimated values. Thirdly, a set of statistical invariants-values which are preserved in statistical processing was presented. And fourthly, the inequality that signals a correlation between experimental errors that leads to unphysical values is given. An application is given concerning the cross-section of the (n,t) reaction on Li 6 with a neutron incident energy comprised between 1 and 100 keV
Covariance and correlation estimation in electron-density maps.
Altomare, Angela; Cuocci, Corrado; Giacovazzo, Carmelo; Moliterni, Anna; Rizzi, Rosanna
2012-03-01
Quite recently two papers have been published [Giacovazzo & Mazzone (2011). Acta Cryst. A67, 210-218; Giacovazzo et al. (2011). Acta Cryst. A67, 368-382] which calculate the variance in any point of an electron-density map at any stage of the phasing process. The main aim of the papers was to associate a standard deviation to each pixel of the map, in order to obtain a better estimate of the map reliability. This paper deals with the covariance estimate between points of an electron-density map in any space group, centrosymmetric or non-centrosymmetric, no matter the correlation between the model and target structures. The aim is as follows: to verify if the electron density in one point of the map is amplified or depressed as an effect of the electron density in one or more other points of the map. High values of the covariances are usually connected with undesired features of the map. The phases are the primitive random variables of our probabilistic model; the covariance changes with the quality of the model and therefore with the quality of the phases. The conclusive formulas show that the covariance is also influenced by the Patterson map. Uncertainty on measurements may influence the covariance, particularly in the final stages of the structure refinement; a general formula is obtained taking into account both phase and measurement uncertainty, valid at any stage of the crystal structure solution.
Bayes Factor Covariance Testing in Item Response Models.
Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip
2017-12-01
Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.
Fast Component Pursuit for Large-Scale Inverse Covariance Estimation.
Han, Lei; Zhang, Yu; Zhang, Tong
2016-08-01
The maximum likelihood estimation (MLE) for the Gaussian graphical model, which is also known as the inverse covariance estimation problem, has gained increasing interest recently. Most existing works assume that inverse covariance estimators contain sparse structure and then construct models with the ℓ 1 regularization. In this paper, different from existing works, we study the inverse covariance estimation problem from another perspective by efficiently modeling the low-rank structure in the inverse covariance, which is assumed to be a combination of a low-rank part and a diagonal matrix. One motivation for this assumption is that the low-rank structure is common in many applications including the climate and financial analysis, and another one is that such assumption can reduce the computational complexity when computing its inverse. Specifically, we propose an efficient COmponent Pursuit (COP) method to obtain the low-rank part, where each component can be sparse. For optimization, the COP method greedily learns a rank-one component in each iteration by maximizing the log-likelihood. Moreover, the COP algorithm enjoys several appealing properties including the existence of an efficient solution in each iteration and the theoretical guarantee on the convergence of this greedy approach. Experiments on large-scale synthetic and real-world datasets including thousands of millions variables show that the COP method is faster than the state-of-the-art techniques for the inverse covariance estimation problem when achieving comparable log-likelihood on test data.
Beamforming using subspace estimation from a diagonally averaged sample covariance.
Quijano, Jorge E; Zurk, Lisa M
2017-08-01
The potential benefit of a large-aperture sonar array for high resolution target localization is often challenged by the lack of sufficient data required for adaptive beamforming. This paper introduces a Toeplitz-constrained estimator of the clairvoyant signal covariance matrix corresponding to multiple far-field targets embedded in background isotropic noise. The estimator is obtained by averaging along subdiagonals of the sample covariance matrix, followed by covariance extrapolation using the method of maximum entropy. The sample covariance is computed from limited data snapshots, a situation commonly encountered with large-aperture arrays in environments characterized by short periods of local stationarity. Eigenvectors computed from the Toeplitz-constrained covariance are used to construct signal-subspace projector matrices, which are shown to reduce background noise and improve detection of closely spaced targets when applied to subspace beamforming. Monte Carlo simulations corresponding to increasing array aperture suggest convergence of the proposed projector to the clairvoyant signal projector, thereby outperforming the classic projector obtained from the sample eigenvectors. Beamforming performance of the proposed method is analyzed using simulated data, as well as experimental data from the Shallow Water Array Performance experiment.
Modelling the Covariance Structure in Marginal Multivariate Count Models
DEFF Research Database (Denmark)
Bonat, W. H.; Olivero, J.; Grande-Vega, M.
2017-01-01
The main goal of this article is to present a flexible statistical modelling framework to deal with multivariate count data along with longitudinal and repeated measures structures. The covariance structure for each response variable is defined in terms of a covariance link function combined...... be used to indicate whether there was statistical evidence of a decline in blue duikers and other species hunted during the study period. Determining whether observed drops in the number of animals hunted are indeed true is crucial to assess whether species depletion effects are taking place in exploited...... with a matrix linear predictor involving known matrices. In order to specify the joint covariance matrix for the multivariate response vector, the generalized Kronecker product is employed. We take into account the count nature of the data by means of the power dispersion function associated with the Poisson...
Covariate selection for the semiparametric additive risk model
DEFF Research Database (Denmark)
Martinussen, Torben; Scheike, Thomas
2009-01-01
This paper considers covariate selection for the additive hazards model. This model is particularly simple to study theoretically and its practical implementation has several major advantages to the similar methodology for the proportional hazards model. One complication compared...... and study their large sample properties for the situation where the number of covariates p is smaller than the number of observations. We also show that the adaptive Lasso has the oracle property. In many practical situations, it is more relevant to tackle the situation with large p compared with the number...... of observations. We do this by studying the properties of the so-called Dantzig selector in the setting of the additive risk model. Specifically, we establish a bound on how close the solution is to a true sparse signal in the case where the number of covariates is large. In a simulation study, we also compare...
Sparse reduced-rank regression with covariance estimation
Chen, Lisha
2014-12-08
Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.
Quasi-local mass in the covariant Newtonian spacetime
International Nuclear Information System (INIS)
Wu, Y-H; Wang, C-H
2008-01-01
In general relativity, quasi-local energy-momentum expressions have been constructed from various formulae. However, the Newtonian theory of gravity gives a well-known and a unique quasi-local mass expression (surface integration). Since geometrical formulation of Newtonian gravity has been established in the covariant Newtonian spacetime, it provides a covariant approximation from relativistic to Newtonian theories. By using this approximation, we calculate the Komar integral, the Brown-York quasi-local energy and the Dougan-Mason quasi-local mass in the covariant Newtonian spacetime. It turns out that the Komar integral naturally gives the Newtonian quasi-local mass expression; however, further conditions (spherical symmetry) need to be made for Brown-York and Dougan-Mason expressions
Covariant fields on anti-de Sitter spacetimes
Cotăescu, Ion I.
2018-02-01
The covariant free fields of any spin on anti-de Sitter (AdS) spacetimes are studied, pointing out that these transform under isometries according to covariant representations (CRs) of the AdS isometry group, induced by those of the Lorentz group. Applying the method of ladder operators, it is shown that the CRs with unique spin are equivalent with discrete unitary irreducible representations (UIRs) of positive energy of the universal covering group of the isometry one. The action of the Casimir operators is studied finding how the weights of these representations (reps.) may depend on the mass and spin of the covariant field. The conclusion is that on AdS spacetime, one cannot formulate a universal mass condition as in special relativity.
Spatial implications of covariate adjustment on patterns of risk
DEFF Research Database (Denmark)
Sabel, Clive Eric; Wilson, Jeff Gaines; Kingham, Simon
2007-01-01
Epidemiological studies that examine the relationship between environmental exposures and health often address other determinants of health that may influence the relationship being studied by adjusting for these factors as covariates. While disease surveillance methods routinely control...... for covariates such as deprivation, there has been limited investigative work on the spatial movement of risk at the intraurban scale due to the adjustment. It is important that the nature of any spatial relocation be well understood as a relocation to areas of increased risk may also introduce additional...... localised factors that influence the exposure-response relationship. This paper examines the spatial patterns of relative risk and clusters of hospitalisations based on an illustrative small-area example from Christchurch, New Zealand. A four-stage test of the spatial relocation effects of covariate...
Preparation of covariance data for the fast reactor. 2
International Nuclear Information System (INIS)
Shibata, Keiichi; Hasagawa, Akira
1998-03-01
For some isotopes important for core analysis of the fast reactor, covariance data of neutron nuclear data in the evaluated nuclear data library (JENDL-3.2) were presumed to file. Objected isotopes were 10-B, 11-B, 55-Mn, 240-Pu and 241-Pu. Physical amounts presumed on covariance were cross section, isolated and unisolated resonance parameters and first order Legendre coefficient of elastic scattering angle distribution. Presumption of the covariance was conducted in accordance with the data estimation method of JENDL-3.2 as possible. In other ward, when the estimated value was based on the experimental one, error of the experimental value was calculated, and when based on the calculated value, error of the calculated one was obtained. Their estimated results were prepared with ENDF-6 format. (G.K.)
Sparse reduced-rank regression with covariance estimation
Chen, Lisha; Huang, Jianhua Z.
2014-01-01
Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.
A covariant canonical description of Liouville field theory
International Nuclear Information System (INIS)
Papadopoulos, G.; Spence, B.
1993-03-01
This paper presents a new parametrisation of the space of solutions of Liouville field theory on a cylinder. In this parametrisation, the solutions are well-defined and manifestly real functions over all space-time and all of parameter space. It is shown that the resulting covariant phase space of the Liouville theory is diffeomorphic to the Hamiltonian one, and to the space of initial data of the theory. The Poisson brackets are derived and shown to be those of the co-tangent bundle of the loop group of the real line. Using Hamiltonian reduction, it is shown that this covariant phase space formulation of Liouville theory may also be obtained from the covariant phase space formulation of the Wess-Zumino-Witten model. 19 refs
Improving chemical species tomography of turbulent flows using covariance estimation.
Grauer, Samuel J; Hadwin, Paul J; Daun, Kyle J
2017-05-01
Chemical species tomography (CST) experiments can be divided into limited-data and full-rank cases. Both require solving ill-posed inverse problems, and thus the measurement data must be supplemented with prior information to carry out reconstructions. The Bayesian framework formalizes the role of additive information, expressed as the mean and covariance of a joint-normal prior probability density function. We present techniques for estimating the spatial covariance of a flow under limited-data and full-rank conditions. Our results show that incorporating a covariance estimate into CST reconstruction via a Bayesian prior increases the accuracy of instantaneous estimates. Improvements are especially dramatic in real-time limited-data CST, which is directly applicable to many industrially relevant experiments.
Covariant conserved currents for scalar-tensor Horndeski theory
Schmidt, J.; Bičák, J.
2018-04-01
The scalar-tensor theories have become popular recently in particular in connection with attempts to explain present accelerated expansion of the universe, but they have been considered as a natural extension of general relativity long time ago. The Horndeski scalar-tensor theory involving four invariantly defined Lagrangians is a natural choice since it implies field equations involving at most second derivatives. Following the formalisms of defining covariant global quantities and conservation laws for perturbations of spacetimes in standard general relativity, we extend these methods to the general Horndeski theory and find the covariant conserved currents for all four Lagrangians. The current is also constructed in the case of linear perturbations involving both metric and scalar fields. As a specific illustration, we derive a superpotential that leads to the covariantly conserved current in the Branse-Dicke theory.
Abnormalities in structural covariance of cortical gyrification in schizophrenia.
Palaniyappan, Lena; Park, Bert; Balain, Vijender; Dangi, Raj; Liddle, Peter
2015-07-01
The highly convoluted shape of the adult human brain results from several well-coordinated maturational events that start from embryonic development and extend through the adult life span. Disturbances in these maturational events can result in various neurological and psychiatric disorders, resulting in abnormal patterns of morphological relationship among cortical structures (structural covariance). Structural covariance can be studied using graph theory-based approaches that evaluate topological properties of brain networks. Covariance-based graph metrics allow cross-sectional study of coordinated maturational relationship among brain regions. Disrupted gyrification of focal brain regions is a consistent feature of schizophrenia. However, it is unclear if these localized disturbances result from a failure of coordinated development of brain regions in schizophrenia. We studied the structural covariance of gyrification in a sample of 41 patients with schizophrenia and 40 healthy controls by constructing gyrification-based networks using a 3-dimensional index. We found that several key regions including anterior insula and dorsolateral prefrontal cortex show increased segregation in schizophrenia, alongside reduced segregation in somato-sensory and occipital regions. Patients also showed a lack of prominence of the distributed covariance (hubness) of cingulate cortex. The abnormal segregated folding pattern in the right peri-sylvian regions (insula and fronto-temporal cortex) was associated with greater severity of illness. The study of structural covariance in cortical folding supports the presence of subtle deviation in the coordinated development of cortical convolutions in schizophrenia. The heterogeneity in the severity of schizophrenia could be explained in part by aberrant trajectories of neurodevelopment.
Structural Covariance Networks in Children with Autism or ADHD.
Bethlehem, R A I; Romero-Garcia, R; Mak, E; Bullmore, E T; Baron-Cohen, S
2017-08-01
While autism and attention-deficit/hyperactivity disorder (ADHD) are considered distinct conditions from a diagnostic perspective, clinically they share some phenotypic features and have high comorbidity. Regardless, most studies have focused on only one condition, with considerable heterogeneity in their results. Taking a dual-condition approach might help elucidate shared and distinct neural characteristics. Graph theory was used to analyse topological properties of structural covariance networks across both conditions and relative to a neurotypical (NT; n = 87) group using data from the ABIDE (autism; n = 62) and ADHD-200 datasets (ADHD; n = 69). Regional cortical thickness was used to construct the structural covariance networks. This was analysed in a theoretical framework examining potential differences in long and short-range connectivity, with a specific focus on relation between central graph measures and cortical thickness. We found convergence between autism and ADHD, where both conditions show an overall decrease in CT covariance with increased Euclidean distance between centroids compared with a NT population. The 2 conditions also show divergence. Namely, there is less modular overlap between the 2 conditions than there is between each condition and the NT group. The ADHD group also showed reduced cortical thickness and lower degree in hub regions than the autism group. Lastly, the ADHD group also showed reduced wiring costs compared with the autism groups. Our results indicate a need for taking an integrated approach when considering highly comorbid conditions such as autism and ADHD. Furthermore, autism and ADHD both showed alterations in the relation between inter-regional covariance and centroid distance, where both groups show a steeper decline in covariance as a function of distance. The 2 groups also diverge on modular organization, cortical thickness of hub regions and wiring cost of the covariance network. Thus, on some network features the
Relativistic covariant wave equations and acausality in external fields
International Nuclear Information System (INIS)
Pijlgroms, R.B.J.
1980-01-01
The author considers linear, finite dimensional, first order relativistic wave equations: (βsup(μ)ideltasub(μ)-β)PSI(x) = 0 with βsup(μ) and β constant matrices. Firstly , the question of the relativistic covariance conditions on these equations is considered. Then the theory of these equations with β non-singular is summarized. Theories with βsup(μ), β square matrices and β singular are also discussed. Non-square systems of covariant relativistic wave equations for arbitrary spin > 1 are then considered. Finally, the interaction with external fields and the acausality problem are discussed. (G.T.H.)
On spectral distribution of high dimensional covariation matrices
DEFF Research Database (Denmark)
Heinrich, Claudio; Podolskij, Mark
In this paper we present the asymptotic theory for spectral distributions of high dimensional covariation matrices of Brownian diffusions. More specifically, we consider N-dimensional Itô integrals with time varying matrix-valued integrands. We observe n equidistant high frequency data points...... of the underlying Brownian diffusion and we assume that N/n -> c in (0,oo). We show that under a certain mixed spectral moment condition the spectral distribution of the empirical covariation matrix converges in distribution almost surely. Our proof relies on method of moments and applications of graph theory....
Quantum mechanics vs. general covariance in gravity and string models
International Nuclear Information System (INIS)
Martinec, E.J.
1984-01-01
Quantization of simple low-dimensional systems embodying general covariance is studied. Functional methods are employed in the calculation of effective actions for fermionic strings and 1 + 1 dimensional gravity. The author finds that regularization breaks apparent symmetries of the theory, providing new dynamics for the string and non-trivial dynamics for 1 + 1 gravity. The author moves on to consider the quantization of some generally covariant systems with a finite number of physical degrees of freedom, assuming the existence of an invariant cutoff. The author finds that the wavefunction of the universe in these cases is given by the solution to simple quantum mechanics problems
Some Algorithms for the Conditional Mean Vector and Covariance Matrix
Directory of Open Access Journals (Sweden)
John F. Monahan
2006-08-01
Full Text Available We consider here the problem of computing the mean vector and covariance matrix for a conditional normal distribution, considering especially a sequence of problems where the conditioning variables are changing. The sweep operator provides one simple general approach that is easy to implement and update. A second, more goal-oriented general method avoids explicit computation of the vector and matrix, while enabling easy evaluation of the conditional density for likelihood computation or easy generation from the conditional distribution. The covariance structure that arises from the special case of an ARMA(p, q time series can be exploited for substantial improvements in computational efficiency.
Robust Covariance Estimators Based on Information Divergences and Riemannian Manifold
Directory of Open Access Journals (Sweden)
Xiaoqiang Hua
2018-03-01
Full Text Available This paper proposes a class of covariance estimators based on information divergences in heterogeneous environments. In particular, the problem of covariance estimation is reformulated on the Riemannian manifold of Hermitian positive-definite (HPD matrices. The means associated with information divergences are derived and used as the estimators. Without resorting to the complete knowledge of the probability distribution of the sample data, the geometry of the Riemannian manifold of HPD matrices is considered in mean estimators. Moreover, the robustness of mean estimators is analyzed using the influence function. Simulation results indicate the robustness and superiority of an adaptive normalized matched filter with our proposed estimators compared with the existing alternatives.
Rotational covariance and light-front current matrix elements
International Nuclear Information System (INIS)
Keister, B.D.
1994-01-01
Light-front current matrix elements for elastic scattering from hadrons with spin 1 or greater must satisfy a nontrivial constraint associated with the requirement of rotational covariance for the current operator. Using a model ρ meson as a prototype for hadronic quark models, this constraint and its implications are studied at both low and high momentum transfers. In the kinematic region appropriate for asymptotic QCD, helicity rules, together with the rotational covariance condition, yield an additional relation between the light-front current matrix elements
ICTP lectures on covariant quantization of the superstring
International Nuclear Information System (INIS)
Berkovits, N.
2003-01-01
These ICTP Trieste lecture notes review the pure spinor approach to quantizing the superstring with manifest D=10 super-Poincare invariance. The first section discusses covariant quantization of the superparticle and gives a new proof of equivalence with the Brink-Schwarz superparticle. The second section discusses the superstring in a flat background and shows how to construct vertex operators and compute tree amplitudes in a manifestly super-Poincare covariant manner. And the third section discusses quantization of the superstring in curved backgrounds which can include Ramond-Ramond flux. (author)
Undesirable effects of covariance matrix techniques for error analysis
International Nuclear Information System (INIS)
Seibert, D.
1994-01-01
Regression with χ 2 constructed from covariance matrices should not be used for some combinations of covariance matrices and fitting functions. Using the technique for unsuitable combinations can amplify systematic errors. This amplification is uncontrolled, and can produce arbitrarily inaccurate results that might not be ruled out by a χ 2 test. In addition, this technique can give incorrect (artificially small) errors for fit parameters. I give a test for this instability and a more robust (but computationally more intensive) method for fitting correlated data
Sp(2) covariant quantisation of general gauge theories
Energy Technology Data Exchange (ETDEWEB)
Vazquez-Bello, J L
1994-11-01
The Sp(2) covariant quantization of gauge theories is studied. The geometrical interpretation of gauge theories in terms of quasi principal fibre bundles Q(M{sub s}, G{sub s}) is reviewed. It is then described the Sp(2) algebra of ordinary Yang-Mills theory. A consistent formulation of covariant Lagrangian quantisation for general gauge theories based on Sp(2) BRST symmetry is established. The original N = 1, ten dimensional superparticle is considered as an example of infinitely reducible gauge algebras, and given explicitly its Sp(2) BRST invariant action. (author). 18 refs.
Sp(2) covariant quantisation of general gauge theories
International Nuclear Information System (INIS)
Vazquez-Bello, J.L.
1994-11-01
The Sp(2) covariant quantization of gauge theories is studied. The geometrical interpretation of gauge theories in terms of quasi principal fibre bundles Q(M s , G s ) is reviewed. It is then described the Sp(2) algebra of ordinary Yang-Mills theory. A consistent formulation of covariant Lagrangian quantisation for general gauge theories based on Sp(2) BRST symmetry is established. The original N = 1, ten dimensional superparticle is considered as an example of infinitely reducible gauge algebras, and given explicitly its Sp(2) BRST invariant action. (author). 18 refs
Portfolio management using realized covariances: Evidence from Brazil
Directory of Open Access Journals (Sweden)
João F. Caldeira
2017-09-01
Full Text Available It is often argued that intraday returns can be used to construct covariance estimates that are more accurate than those based on daily returns. However, it is still unclear whether high frequency data provide more precise covariance estimates in markets more contaminated from microstructure noise such as higher bid-ask spreads and lower liquidity. We address this question by investigating the benefits of using high frequency data in the Brazilian equities market to construct optimal minimum variance portfolios. We implement alternative realized covariance estimators based on intraday returns sampled at alternative frequencies and obtain their dynamic versions using a multivariate GARCH framework. Our evidence based on a high-dimensional data set suggests that realized covariance estimators performed significantly better from an economic point of view in comparison to standard estimators based on low-frequency (close-to-close data as they delivered less risky portfolios. Resumo: Argumenta-se frequentemente que retornos intradiários podem ser usados para construir estimativas de covariâncias mais precisas em relação àquelas obtidas com retornos diários. No entanto, ainda não está claro se os dados de alta freqüência fornecem estimativas de covariância mais precisas em mercados mais contaminados pelo ruído da microestrutura, como maiores spreads entre ofertas de compra e venda e baixa liquidez. Abordamos essa questão investigando os benefícios do uso de dados de alta freqüência no mercado de ações brasileiro através da construção de portfólios ótimos de variância mínima. Implementamos diversos estimadores de covariâncias realizadas com base em retornos intradiários amostrados em diferentes frequências e obtemos suas versões dinâmicas usando uma estrutura GARCH multivariada. Nossa evidência baseada em um conjunto de dados de alta dimensão sugere que os estimadores de covariâncias realizadas obtiveram um desempenho
The covariance matrix of derived quantities and their combination
International Nuclear Information System (INIS)
Zhao, Z.; Perey, F.G.
1992-06-01
The covariance matrix of quantities derived from measured data via nonlinear relations are only approximate since they are functions of the measured data taken as estimates for the true values of the measured quantities. The evaluation of such derived quantities entails new estimates for the true values of the measured quantities and consequently implies a modification of the covariance matrix of the derived quantities that was used in the evaluation process. Failure to recognize such an implication can lead to inconsistencies between the results of different evaluation strategies. In this report we show that an iterative procedure can eliminate such inconsistencies
Estimating surface fluxes using eddy covariance and numerical ogive optimization
DEFF Research Database (Denmark)
Sievers, J.; Papakyriakou, T.; Larsen, Søren Ejling
2015-01-01
Estimating representative surface fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modelling efforts, low-frequency con......Estimating representative surface fluxes using eddy covariance leads invariably to questions concerning inclusion or exclusion of low-frequency flux contributions. For studies where fluxes are linked to local physical parameters and up-scaled through numerical modelling efforts, low...
ICTP lectures on covariant quantization of the superstring
Energy Technology Data Exchange (ETDEWEB)
Berkovits, N [Instituto de Fisica Teorica, Universidade Estadual Paulista, Sao Paulo, SP (Brazil)
2003-08-15
These ICTP Trieste lecture notes review the pure spinor approach to quantizing the superstring with manifest D=10 super-Poincare invariance. The first section discusses covariant quantization of the superparticle and gives a new proof of equivalence with the Brink-Schwarz superparticle. The second section discusses the superstring in a flat background and shows how to construct vertex operators and compute tree amplitudes in a manifestly super-Poincare covariant manner. And the third section discusses quantization of the superstring in curved backgrounds which can include Ramond-Ramond flux. (author)
Covariance measurement in the presence of non-synchronous trading and market microstructure noise
Griffin, J.E.; Oomen, R.C.A.
2011-01-01
This paper studies the problem of covariance estimation when prices are observed non-synchronously and contaminated by i.i.d. microstructure noise. We derive closed form expressions for the bias and variance of three popular covariance estimators, namely realised covariance, realised covariance plus
An Empirical State Error Covariance Matrix Orbit Determination Example
Frisbee, Joseph H., Jr.
2015-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. First, consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. Then it follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix of the estimate will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully include all of the errors in the state estimate. The empirical error covariance matrix is determined from a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm. It is a formally correct, empirical state error covariance matrix obtained through use of the average form of the weighted measurement residual variance performance index rather than the usual total weighted residual form. Based on its formulation, this matrix will contain the total uncertainty in the state estimate, regardless as to the source of the uncertainty and whether the source is anticipated or not. It is expected that the empirical error covariance matrix will give a better, statistical representation of the state error in poorly modeled systems or when sensor performance
Energy Technology Data Exchange (ETDEWEB)
Leitão, Sofia, E-mail: sofia.leitao@tecnico.ulisboa.pt [CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Stadler, Alfred, E-mail: stadler@uevora.pt [Departamento de Física, Universidade de Évora, 7000-671 Évora (Portugal); CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Peña, M.T., E-mail: teresa.pena@tecnico.ulisboa.pt [Departamento de Física, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Biernat, Elmar P., E-mail: elmar.biernat@tecnico.ulisboa.pt [CFTP, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)
2017-01-10
The Covariant Spectator Theory (CST) is used to calculate the mass spectrum and vertex functions of heavy–light and heavy mesons in Minkowski space. The covariant kernel contains Lorentz scalar, pseudoscalar, and vector contributions. The numerical calculations are performed in momentum space, where special care is taken to treat the strong singularities present in the confining kernel. The observed meson spectrum is very well reproduced after fitting a small number of model parameters. Remarkably, a fit to a few pseudoscalar meson states only, which are insensitive to spin–orbit and tensor forces and do not allow to separate the spin–spin from the central interaction, leads to essentially the same model parameters as a more general fit. This demonstrates that the covariance of the chosen interaction kernel is responsible for the very accurate prediction of the spin-dependent quark–antiquark interactions.
International Nuclear Information System (INIS)
Fu, C.Y.; Hetrick, D.M.
1982-01-01
Recent ratio data, with carefully evaluated covariances, were combined with eleven of the ENDF/B-V dosimetry cross sections using the generalized least-squares method. The purpose was to improve these evaluated cross sections and covariances, as well as to generate values for the cross-reaction covariances. The results represent improved cross sections as well as realistic and usable covariances. The latter are necessary for meaningful intergral-differential comparisons and for spectrum unfolding
Some remarks on estimating a covariance structure model from a sample correlation matrix
Maydeu Olivares, Alberto; Hernández Estrada, Adolfo
2000-01-01
A popular model in structural equation modeling involves a multivariate normal density with a structured covariance matrix that has been categorized according to a set of thresholds. In this setup one may estimate the covariance structure parameters from the sample tetrachoricl polychoric correlations but only if the covariance structure is scale invariant. Doing so when the covariance structure is not scale invariant results in estimating a more restricted covariance structure than the one i...
Preliminary Monthly Climatological Summaries
National Oceanic and Atmospheric Administration, Department of Commerce — Preliminary Local Climatological Data, recorded since 1970 on Weather Burean Form 1030 and then National Weather Service Form F-6. The preliminary climate data pages...
Nonlinear wave mechanics from classical dynamics and scale covariance
International Nuclear Information System (INIS)
Hammad, F.
2007-01-01
Nonlinear Schroedinger equations proposed by Kostin and by Doebner and Goldin are rederived from Nottale's prescription for obtaining quantum mechanics from classical mechanics in nondifferentiable spaces; i.e., from hydrodynamical concepts and scale covariance. Some soliton and plane wave solutions are discussed
Merons in a generally covariant model with Gursey term
International Nuclear Information System (INIS)
Akdeniz, K.G.; Smailagic, A.
1982-10-01
We study meron solutions of the generally covariant and Weyl invariant fermionic model with Gursey term. We find that, due to the presence of this term, merons can exist even without the cosmological constant. This is a new feature compared to previously studied models. (author)
Dynamical affine symmetry and covariant perturbation theory for gravity
International Nuclear Information System (INIS)
Pervushin, V.N.
1975-01-01
The covariant perturbation theory for gravity with the simplest reduction properties is formulated. The main points are as follows: fundamental fields are the normal coordinates of ten-dimensional space of the gravitational field, and the fields are separated into the classical (background) and quantum ones in the generating functional along geodesics of this space
Phenotypic Covariation and Morphological Diversification in the Ruminant Skull.
Haber, Annat
2016-05-01
Differences among clades in their diversification patterns result from a combination of extrinsic and intrinsic factors. In this study, I examined the role of intrinsic factors in the morphological diversification of ruminants, in general, and in the differences between bovids and cervids, in particular. Using skull morphology, which embodies many of the adaptations that distinguish bovids and cervids, I examined 132 of the 200 extant ruminant species. As a proxy for intrinsic constraints, I quantified different aspects of the phenotypic covariation structure within species and compared them with the among-species divergence patterns, using phylogenetic comparative methods. My results show that for most species, divergence is well aligned with their phenotypic covariance matrix and that those that are better aligned have diverged further away from their ancestor. Bovids have dispersed into a wider range of directions in morphospace than cervids, and their overall disparity is higher. This difference is best explained by the lower eccentricity of bovids' within-species covariance matrices. These results are consistent with the role of intrinsic constraints in determining amount, range, and direction of dispersion and demonstrate that intrinsic constraints can influence macroevolutionary patterns even as the covariance structure evolves.
Covariation of Color and Luminance Facilitate Object Individuation in Infancy
Woods, Rebecca J.; Wilcox, Teresa
2010-01-01
The ability to individuate objects is one of our most fundamental cognitive capacities. Recent research has revealed that when objects vary in color or luminance alone, infants fail to individuate those objects until 11.5 months. However, color and luminance frequently covary in the natural environment, thus providing a more salient and reliable…
Flexible Bayesian Dynamic Modeling of Covariance and Correlation Matrices
Lan, Shiwei
2017-11-08
Modeling covariance (and correlation) matrices is a challenging problem due to the large dimensionality and positive-definiteness constraint. In this paper, we propose a novel Bayesian framework based on decomposing the covariance matrix into variance and correlation matrices. The highlight is that the correlations are represented as products of vectors on unit spheres. We propose a variety of distributions on spheres (e.g. the squared-Dirichlet distribution) to induce flexible prior distributions for covariance matrices that go beyond the commonly used inverse-Wishart prior. To handle the intractability of the resulting posterior, we introduce the adaptive $\\\\Delta$-Spherical Hamiltonian Monte Carlo. We also extend our structured framework to dynamic cases and introduce unit-vector Gaussian process priors for modeling the evolution of correlation among multiple time series. Using an example of Normal-Inverse-Wishart problem, a simulated periodic process, and an analysis of local field potential data (collected from the hippocampus of rats performing a complex sequence memory task), we demonstrated the validity and effectiveness of our proposed framework for (dynamic) modeling covariance and correlation matrices.
Co-variations of Cholera with Climatic and Environmental ...
African Journals Online (AJOL)
Significant co-variations were found between seasonally adjusted cases and coastal ocean chlorophyll a and to some degree sea surface temperature, both lagged by one to four months. Cholera cases in Dar es Salaam were also weakly related to the Indian Ocean Dipole Mode Index lagged by 5 months, suggesting that it ...
A photon propagator on de Sitter in covariant gauges
Domazet, S.; Prokopec, T.
2014-01-01
We construct a de Sitter invariant photon propagator in general covariant gauges. Our result is a natural generalization of the Allen-Jacobson photon propagator in Feynman gauge. Our propagator reproduces the correct response to a point static charge and the one-loop electromagnetic stress-energy
Modeling and Forecasting Large Realized Covariance Matrices and Portfolio Choice
Callot, Laurent A.F.; Kock, Anders B.; Medeiros, Marcelo C.
2017-01-01
We consider modeling and forecasting large realized covariance matrices by penalized vector autoregressive models. We consider Lasso-type estimators to reduce the dimensionality and provide strong theoretical guarantees on the forecast capability of our procedure. We show that we can forecast
Semiparametric estimation of covariance matrices for longitudinal data.
Fan, Jianqing; Wu, Yichao
2008-12-01
Estimation of longitudinal data covariance structure poses significant challenges because the data are usually collected at irregular time points. A viable semiparametric model for covariance matrices was proposed in Fan, Huang and Li (2007) that allows one to estimate the variance function nonparametrically and to estimate the correlation function parametrically via aggregating information from irregular and sparse data points within each subject. However, the asymptotic properties of their quasi-maximum likelihood estimator (QMLE) of parameters in the covariance model are largely unknown. In the current work, we address this problem in the context of more general models for the conditional mean function including parametric, nonparametric, or semi-parametric. We also consider the possibility of rough mean regression function and introduce the difference-based method to reduce biases in the context of varying-coefficient partially linear mean regression models. This provides a more robust estimator of the covariance function under a wider range of situations. Under some technical conditions, consistency and asymptotic normality are obtained for the QMLE of the parameters in the correlation function. Simulation studies and a real data example are used to illustrate the proposed approach.
Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)
DEFF Research Database (Denmark)
Agosto, Arianna; Cavaliere, Guiseppe; Kristensen, Dennis
We develop a class of Poisson autoregressive models with additional covariates (PARX) that can be used to model and forecast time series of counts. We establish the time series properties of the models, including conditions for stationarity and existence of moments. These results are in turn used...
Improved forecasting with leading indicators: the principal covariate index
C. Heij (Christiaan)
2007-01-01
textabstractWe propose a new method of leading index construction that combines the need for data compression with the objective of forecasting. This so-called principal covariate index is constructed to forecast growth rates of the Composite Coincident Index. The forecast performance is compared
On covariant quantization of massive superparticle with first class constraints
International Nuclear Information System (INIS)
Huq, M.
1990-02-01
We use the technique of Batalin and Fradkin to convert the second class fermionic constraints of the massive superparticle into first class constraints. Then the Batalin-Vilkovisky formalism has been used to quantize covariantly the resulting theory. Appropriate gauge fixing conditions lead to a completely quadratic action. Some interesting properties of the physical space wave functions are discussed. (author). 16 refs
Eddy Covariance Measurements of the Sea-Spray Aerosol Flu
Brooks, I. M.; Norris, S. J.; Yelland, M. J.; Pascal, R. W.; Prytherch, J.
2015-12-01
Historically, almost all estimates of the sea-spray aerosol source flux have been inferred through various indirect methods. Direct estimates via eddy covariance have been attempted by only a handful of studies, most of which measured only the total number flux, or achieved rather coarse size segregation. Applying eddy covariance to the measurement of sea-spray fluxes is challenging: most instrumentation must be located in a laboratory space requiring long sample lines to an inlet collocated with a sonic anemometer; however, larger particles are easily lost to the walls of the sample line. Marine particle concentrations are generally low, requiring a high sample volume to achieve adequate statistics. The highly hygroscopic nature of sea salt means particles change size rapidly with fluctuations in relative humidity; this introduces an apparent bias in flux measurements if particles are sized at ambient humidity. The Compact Lightweight Aerosol Spectrometer Probe (CLASP) was developed specifically to make high rate measurements of aerosol size distributions for use in eddy covariance measurements, and the instrument and data processing and analysis techniques have been refined over the course of several projects. Here we will review some of the issues and limitations related to making eddy covariance measurements of the sea spray source flux over the open ocean, summarise some key results from the last decade, and present new results from a 3-year long ship-based measurement campaign as part of the WAGES project. Finally we will consider requirements for future progress.
Covariant heterotic strings and odd self-dual lattices
International Nuclear Information System (INIS)
Lerche, W.; Luest, D.
1987-01-01
We investigate the implications of modular invariance for covariantly formulated heterotic strings. It is shown that modular invariant heterotic strings are characterized by odd self-dual lorentzian lattices which include charges of the bosonized superconformal ghosts. The proof of modular invariance involves the anomaly in the ghost number current in a crucial way. (orig.)
Modeling the Conditional Covariance between Stock and Bond Returns
P. de Goeij (Peter); W.A. Marquering (Wessel)
2002-01-01
textabstractTo analyze the intertemporal interaction between the stock and bond market returns, we allow the conditional covariance matrix to vary over time according to a multivariate GARCH model similar to Bollerslev, Engle and Wooldridge (1988). We extend the model such that it allows for
Conservation laws and covariant equations of motion for spinning particles
Obukhov, Yuri N.; Puetzfeld, Dirk
2015-01-01
We derive the Noether identities and the conservation laws for general gravitational models with arbitrarily interacting matter and gravitational fields. These conservation laws are used for the construction of the covariant equations of motion for test bodies with minimal and nonminimal coupling.
Unified Approach to Universal Cloning and Phase-Covariant Cloning
Hu, Jia-Zhong; Yu, Zong-Wen; Wang, Xiang-Bin
2008-01-01
We analyze the problem of approximate quantum cloning when the quantum state is between two latitudes on the Bloch's sphere. We present an analytical formula for the optimized 1-to-2 cloning. The formula unifies the universal quantum cloning (UQCM) and the phase covariant quantum cloning.
Covariance, correlation matrix, and the multiscale community structure of networks.
Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing
2010-07-01
Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.
Effect on Prediction when Modeling Covariates in Bayesian Nonparametric Models.
Cruz-Marcelo, Alejandro; Rosner, Gary L; Müller, Peter; Stewart, Clinton F
2013-04-01
In biomedical research, it is often of interest to characterize biologic processes giving rise to observations and to make predictions of future observations. Bayesian nonparametric methods provide a means for carrying out Bayesian inference making as few assumptions about restrictive parametric models as possible. There are several proposals in the literature for extending Bayesian nonparametric models to include dependence on covariates. Limited attention, however, has been directed to the following two aspects. In this article, we examine the effect on fitting and predictive performance of incorporating covariates in a class of Bayesian nonparametric models by one of two primary ways: either in the weights or in the locations of a discrete random probability measure. We show that different strategies for incorporating continuous covariates in Bayesian nonparametric models can result in big differences when used for prediction, even though they lead to otherwise similar posterior inferences. When one needs the predictive density, as in optimal design, and this density is a mixture, it is better to make the weights depend on the covariates. We demonstrate these points via a simulated data example and in an application in which one wants to determine the optimal dose of an anticancer drug used in pediatric oncology.
Bayesian tests on components of the compound symmetry covariance matrix
Mulder, J.; Fox, J.P.
2013-01-01
Complex dependency structures are often conditionally modeled, where random effects parameters are used to specify the natural heterogeneity in the population. When interest is focused on the dependency structure, inferences can be made from a complex covariance matrix using a marginal modeling
Globally covering a-priori regional gravity covariance models
Directory of Open Access Journals (Sweden)
D. Arabelos
2003-01-01
Full Text Available Gravity anomaly data generated using Wenzel’s GPM98A model complete to degree 1800, from which OSU91A has been subtracted, have been used to estimate covariance functions for a set of globally covering equal-area blocks of size 22.5° × 22.5° at Equator, having a 2.5° overlap. For each block an analytic covariance function model was determined. The models are based on 4 parameters: the depth to the Bjerhammar sphere (determines correlation, the free-air gravity anomaly variance, a scale factor of the OSU91A error degree-variances and a maximal summation index, N, of the error degree-variances. The depth of Bjerhammar-sphere varies from -134km to nearly zero, N varies from 360 to 40, the scale factor from 0.03 to 38.0 and the gravity variance from 1081 to 24(10µms-22. The parameters are interpreted in terms of the quality of the data used to construct OSU91A and GPM98A and general conditions such as the occurrence of mountain chains. The variation of the parameters show that it is necessary to use regional covariance models in order to obtain a realistic signal to noise ratio in global applications.Key words. GOCE mission, Covariance function, Spacewise approach`
Construction of covariance matrix for absolute fission yield data measurement
International Nuclear Information System (INIS)
Liu Tingjin; Sun Zhengjun
1999-01-01
The purpose is to provide a tool for experimenters and evaluators to conveniently construct the covariance based on the information of the experiment. The method used is so called as parameter analysis one. The basic method and formula are given in the first section, a practical program is introduced in the second section, and finally, some examples are given in the third section
A reduced covariant string model for the extrinsic string
International Nuclear Information System (INIS)
Botelho, L.C.L.
1989-01-01
It is studied a reduced covariant string model for the extrinsic string by using Polyakov's path integral formalism. On the basis of this reduced model it is suggested that the extrinsic string has its critical dimension given by 13. Additionally, it is calculated in a simple way Poliakov's renormalization group law for the string rigidity coupling constants. (A.C.A.S.) [pt
Bayes factor covariance testing in item response models
Fox, J.P.; Mulder, J.; Sinharay, Sandip
2017-01-01
Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning
Comparing fixed effects and covariance structure estimators for panel data
DEFF Research Database (Denmark)
Ejrnæs, Mette; Holm, Anders
2006-01-01
In this article, the authors compare the traditional econometric fixed effect estimator with the maximum likelihood estimator implied by covariance structure models for panel data. Their findings are that the maximum like lipoid estimator is remarkably robust to certain types of misspecifications...
Distributed Remote Vector Gaussian Source Coding with Covariance Distortion Constraints
DEFF Research Database (Denmark)
Zahedi, Adel; Østergaard, Jan; Jensen, Søren Holdt
2014-01-01
In this paper, we consider a distributed remote source coding problem, where a sequence of observations of source vectors is available at the encoder. The problem is to specify the optimal rate for encoding the observations subject to a covariance matrix distortion constraint and in the presence...
Bayes Factor Covariance Testing in Item Response Models
Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip
2017-01-01
Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning
Simultaneous Mean and Covariance Correction Filter for Orbit Estimation.
Wang, Xiaoxu; Pan, Quan; Ding, Zhengtao; Ma, Zhengya
2018-05-05
This paper proposes a novel filtering design, from a viewpoint of identification instead of the conventional nonlinear estimation schemes (NESs), to improve the performance of orbit state estimation for a space target. First, a nonlinear perturbation is viewed or modeled as an unknown input (UI) coupled with the orbit state, to avoid the intractable nonlinear perturbation integral (INPI) required by NESs. Then, a simultaneous mean and covariance correction filter (SMCCF), based on a two-stage expectation maximization (EM) framework, is proposed to simply and analytically fit or identify the first two moments (FTM) of the perturbation (viewed as UI), instead of directly computing such the INPI in NESs. Orbit estimation performance is greatly improved by utilizing the fit UI-FTM to simultaneously correct the state estimation and its covariance. Third, depending on whether enough information is mined, SMCCF should outperform existing NESs or the standard identification algorithms (which view the UI as a constant independent of the state and only utilize the identified UI-mean to correct the state estimation, regardless of its covariance), since it further incorporates the useful covariance information in addition to the mean of the UI. Finally, our simulations demonstrate the superior performance of SMCCF via an orbit estimation example.
Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity
DEFF Research Database (Denmark)
Boudt, Kris; Laurent, Sébastien; Lunde, Asger
An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization on the correlation matrix in order to exploit the heterogeneity in trading intensity to estimate the different parameters sequentially with as many...
Altered Cerebral Blood Flow Covariance Network in Schizophrenia.
Liu, Feng; Zhuo, Chuanjun; Yu, Chunshui
2016-01-01
Many studies have shown abnormal cerebral blood flow (CBF) in schizophrenia; however, it remains unclear how topological properties of CBF network are altered in this disorder. Here, arterial spin labeling (ASL) MRI was employed to measure resting-state CBF in 96 schizophrenia patients and 91 healthy controls. CBF covariance network of each group was constructed by calculating across-subject CBF covariance between 90 brain regions. Graph theory was used to compare intergroup differences in global and nodal topological measures of the network. Both schizophrenia patients and healthy controls had small-world topology in CBF covariance networks, implying an optimal balance between functional segregation and integration. Compared with healthy controls, schizophrenia patients showed reduced small-worldness, normalized clustering coefficient and local efficiency of the network, suggesting a shift toward randomized network topology in schizophrenia. Furthermore, schizophrenia patients exhibited altered nodal centrality in the perceptual-, affective-, language-, and spatial-related regions, indicating functional disturbance of these systems in schizophrenia. This study demonstrated for the first time that schizophrenia patients have disrupted topological properties in CBF covariance network, which provides a new perspective (efficiency of blood flow distribution between brain regions) for understanding neural mechanisms of schizophrenia.
Scale covariant physics: a 'quantum deformation' of classical electrodynamics
International Nuclear Information System (INIS)
Knoll, Yehonatan; Yavneh, Irad
2010-01-01
We present a deformation of classical electrodynamics, continuously depending on a 'quantum parameter', featuring manifest gauge, Poincare and scale covariance. The theory, dubbed extended charge dynamics (ECD), associates a certain length scale with each charge which, due to scale covariance, is an attribute of a solution, not a parameter of the theory. When the EM field experienced by an ECD charge is slowly varying over that length scale, the dynamics of the charge reduces to classical dynamics, its emitted radiation reduces to the familiar Lienard-Wiechert potential and the above length scale is identified as the charge's Compton length. It is conjectured that quantum mechanics describes statistical aspects of ensembles of ECD solutions, much like classical thermodynamics describes statistical aspects of ensembles of classical solutions. A unique 'remote sensing' feature of ECD, supporting that conjecture, is presented, along with an explanation for the illusion of a photon within a classical treatment of the EM field. Finally, a novel conservation law associated with the scale covariance of ECD is derived, indicating that the scale of a solution may 'drift' with time at a constant rate, much like translation covariance implies a uniform drift of the (average) position.
ANGELO-LAMBDA, Covariance matrix interpolation and mathematical verification
International Nuclear Information System (INIS)
Kodeli, Ivo
2007-01-01
1 - Description of program or function: The codes ANGELO-2.3 and LAMBDA-2.3 are used for the interpolation of the cross section covariance data from the original to a user defined energy group structure, and for the mathematical tests of the matrices, respectively. The LAMBDA-2.3 code calculates the eigenvalues of the matrices (both for the original or the converted) and lists them accordingly into positive and negative matrices. This verification is strongly recommended before using any covariance matrices. These versions of the two codes are the extended versions of the previous codes available in the Packages NEA-1264 - ZZ-VITAMIN-J/COVA. They were specifically developed for the purposes of the OECD LWR UAM benchmark, in particular for the processing of the ZZ-SCALE5.1/COVA-44G cross section covariance matrix library retrieved from the SCALE-5.1 package. Either the original SCALE-5.1 libraries or the libraries separated into several files by Nuclides can be (in principle) processed by ANGELO/LAMBDA codes, but the use of the one-nuclide data is strongly recommended. Due to large deviations of the correlation matrix terms from unity observed in some SCALE5.1 covariance matrices, the previous more severe acceptance condition in the ANGELO2.3 code was released. In case the correlation coefficients exceed 1.0, only a warning message is issued, and coefficients are replaced by 1.0. 2 - Methods: ANGELO-2.3 interpolates the covariance matrices to a union grid using flat weighting. LAMBDA-2.3 code includes the mathematical routines to calculate the eigenvalues of the covariance matrices. 3 - Restrictions on the complexity of the problem: The algorithm used in ANGELO is relatively simple, therefore the interpolations involving energy group structure which are very different from the original (e.g. large difference in the number of energy groups) may not be accurate. In particular in the case of the MT=1018 data (fission spectra covariances) the algorithm may not be
Super-sample covariance approximations and partial sky coverage
Lacasa, Fabien; Lima, Marcos; Aguena, Michel
2018-04-01
Super-sample covariance (SSC) is the dominant source of statistical error on large scale structure (LSS) observables for both current and future galaxy surveys. In this work, we concentrate on the SSC of cluster counts, also known as sample variance, which is particularly useful for the self-calibration of the cluster observable-mass relation; our approach can similarly be applied to other observables, such as galaxy clustering and lensing shear. We first examined the accuracy of two analytical approximations proposed in the literature for the flat sky limit, finding that they are accurate at the 15% and 30-35% level, respectively, for covariances of counts in the same redshift bin. We then developed a harmonic expansion formalism that allows for the prediction of SSC in an arbitrary survey mask geometry, such as large sky areas of current and future surveys. We show analytically and numerically that this formalism recovers the full sky and flat sky limits present in the literature. We then present an efficient numerical implementation of the formalism, which allows fast and easy runs of covariance predictions when the survey mask is modified. We applied our method to a mask that is broadly similar to the Dark Energy Survey footprint, finding a non-negligible negative cross-z covariance, i.e. redshift bins are anti-correlated. We also examined the case of data removal from holes due to, for example bright stars, quality cuts, or systematic removals, and find that this does not have noticeable effects on the structure of the SSC matrix, only rescaling its amplitude by the effective survey area. These advances enable analytical covariances of LSS observables to be computed for current and future galaxy surveys, which cover large areas of the sky where the flat sky approximation fails.
Davies, Christopher E; Glonek, Gary Fv; Giles, Lynne C
2017-08-01
One purpose of a longitudinal study is to gain a better understanding of how an outcome of interest changes among a given population over time. In what follows, a trajectory will be taken to mean the series of measurements of the outcome variable for an individual. Group-based trajectory modelling methods seek to identify subgroups of trajectories within a population, such that trajectories that are grouped together are more similar to each other than to trajectories in distinct groups. Group-based trajectory models generally assume a certain structure in the covariances between measurements, for example conditional independence, homogeneous variance between groups or stationary variance over time. Violations of these assumptions could be expected to result in poor model performance. We used simulation to investigate the effect of covariance misspecification on misclassification of trajectories in commonly used models under a range of scenarios. To do this we defined a measure of performance relative to the ideal Bayesian correct classification rate. We found that the more complex models generally performed better over a range of scenarios. In particular, incorrectly specified covariance matrices could significantly bias the results but using models with a correct but more complicated than necessary covariance matrix incurred little cost.
Covariability in the Monthly Mean Convective and Radiative Diurnal Cycles in the Amazon
Dodson, Jason B.; Taylor, Patrick C.
2015-01-01
The diurnal cycle of convective clouds greatly influences the radiative energy balance in convectively active regions of Earth, through both direct presence, and the production of anvil and stratiform clouds. Previous studies show that the frequency and properties of convective clouds can vary on monthly timescales as a result of variability in the monthly mean atmospheric state. Furthermore, the radiative budget in convectively active regions also varies by up to 7 Wm-2 in convectively active regions. These facts suggest that convective clouds connect atmospheric state variability and radiation variability beyond clear sky effects alone. Previous research has identified monthly covariability between the diurnal cycle of CERES-observed top-of-atmosphere radiative fluxes and multiple atmospheric state variables from reanalysis over the Amazon region. ASVs that enhance (reduce) deep convection, such as CAPE (LTS), tend to shift the daily OLR and cloud albedo maxima earlier (later) in the day by 2-3 hr. We first test the analysis method using multiple reanalysis products for both the dry and wet seasons to further investigate the robustness of the preliminary results. We then use CloudSat data as an independent cloud observing system to further evaluate the relationships of cloud properties to variability in radiation and atmospheric states. While CERES can decompose OLR variability into clear sky and cloud effects, it cannot determine what variability in cloud properties lead to variability in the radiative cloud effects. Cloud frequency, cloud top height, and cloud microphysics all contribute to the cloud radiative effect, all of which are observable by CloudSat. In addition, CloudSat can also observe the presence and variability of deep convective cores responsible for the production of anvil clouds. We use these capabilities to determine the covariability of convective cloud properties and the radiative diurnal cycle.
Exploiting Data Sparsity In Covariance Matrix Computations on Heterogeneous Systems
Charara, Ali M.
2018-05-24
Covariance matrices are ubiquitous in computational sciences, typically describing the correlation of elements of large multivariate spatial data sets. For example, covari- ance matrices are employed in climate/weather modeling for the maximum likelihood estimation to improve prediction, as well as in computational ground-based astronomy to enhance the observed image quality by filtering out noise produced by the adap- tive optics instruments and atmospheric turbulence. The structure of these covariance matrices is dense, symmetric, positive-definite, and often data-sparse, therefore, hier- archically of low-rank. This thesis investigates the performance limit of dense matrix computations (e.g., Cholesky factorization) on covariance matrix problems as the number of unknowns grows, and in the context of the aforementioned applications. We employ recursive formulations of some of the basic linear algebra subroutines (BLAS) to accelerate the covariance matrix computation further, while reducing data traffic across the memory subsystems layers. However, dealing with large data sets (i.e., covariance matrices of billions in size) can rapidly become prohibitive in memory footprint and algorithmic complexity. Most importantly, this thesis investigates the tile low-rank data format (TLR), a new compressed data structure and layout, which is valuable in exploiting data sparsity by approximating the operator. The TLR com- pressed data structure allows approximating the original problem up to user-defined numerical accuracy. This comes at the expense of dealing with tasks with much lower arithmetic intensities than traditional dense computations. In fact, this thesis con- solidates the two trends of dense and data-sparse linear algebra for HPC. Not only does the thesis leverage recursive formulations for dense Cholesky-based matrix al- gorithms, but it also implements a novel TLR-Cholesky factorization using batched linear algebra operations to increase hardware occupancy and
Construction and use of gene expression covariation matrix
Directory of Open Access Journals (Sweden)
Bellis Michel
2009-07-01
Full Text Available Abstract Background One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the choice between the two available methods for calculating the coefficient has been dictated mainly by technological considerations. Specifically, in analyses based on double-channel techniques, researchers have been required to use covariation correlation, i.e. the correlation between gene expression changes measured between several pairs of biological conditions, expressed for example as fold-change. In contrast, in analyses of single-channel techniques scientists have been restricted to the use of coexpression correlation, i.e. correlation between gene expression levels. To our knowledge, nobody has ever examined the possible benefits of using covariation instead of coexpression in massive analyses of single channel microarray results. Results We describe here how single-channel techniques can be treated like double-channel techniques and used to generate both gene expression changes and covariation measures. We also present a new method that allows the calculation of both positive and negative correlation coefficients between genes. First, we perform systematic comparisons between two given biological conditions and classify, for each comparison, genes as increased (I, decreased (D, or not changed (N. As a result, the original series of n gene expression level measures assigned to each gene is replaced by an ordered string of n(n-1/2 symbols, e.g. IDDNNIDID....DNNNNNNID, with the length of the string corresponding to the number of comparisons. In a second step, positive and negative covariation matrices (CVM are constructed by calculating statistically significant positive or negative correlation scores for any pair of genes by comparing their
Effect of neural connectivity on autocovariance and cross covariance estimates
Directory of Open Access Journals (Sweden)
Stecker Mark M
2007-01-01
Full Text Available Abstract Background Measurements of auto and cross covariance functions are frequently used to investigate neural systems. In interpreting this data, it is commonly assumed that the largest contribution to the recordings comes from sources near the electrode. However, the potential recorded at an electrode represents the superimposition of the potentials generated by large numbers of active neural structures. This creates situations under which the measured auto and cross covariance functions are dominated by the activity in structures far from the electrode and in which the distance dependence of the cross-covariance function differs significantly from that describing the activity in the actual neural structures. Methods Direct application of electrostatics to calculate the theoretical auto and cross covariance functions that would be recorded from electrodes immersed in a large volume filled with active neural structures with specific statistical properties. Results It is demonstrated that the potentials recorded from a monopolar electrode surrounded by dipole sources in a uniform medium are predominantly due to activity in neural structures far from the electrode when neuronal correlations drop more slowly than 1/r3 or when the size of the neural system is much smaller than a known correlation distance. Recordings from quadrupolar sources are strongly dependent on distant neurons when correlations drop more slowly than 1/r or the size of the system is much smaller than the correlation distance. Differences between bipolar and monopolar recordings are discussed. It is also demonstrated that the cross covariance of the recorded in two spatially separated electrodes declines as a power-law function of the distance between them even when the electrical activity from different neuronal structures is uncorrelated. Conclusion When extracellular electrophysiologic recordings are made from systems containing large numbers of neural structures, it is
An alternative covariance estimator to investigate genetic heterogeneity in populations.
Heslot, Nicolas; Jannink, Jean-Luc
2015-11-26
For genomic prediction and genome-wide association studies (GWAS) using mixed models, covariance between individuals is estimated using molecular markers. Based on the properties of mixed models, using available molecular data for prediction is optimal if this covariance is known. Under this assumption, adding individuals to the analysis should never be detrimental. However, some empirical studies showed that increasing training population size decreased prediction accuracy. Recently, results from theoretical models indicated that even if marker density is high and the genetic architecture of traits is controlled by many loci with small additive effects, the covariance between individuals, which depends on relationships at causal loci, is not always well estimated by the whole-genome kinship. We propose an alternative covariance estimator named K-kernel, to account for potential genetic heterogeneity between populations that is characterized by a lack of genetic correlation, and to limit the information flow between a priori unknown populations in a trait-specific manner. This is similar to a multi-trait model and parameters are estimated by REML and, in extreme cases, it can allow for an independent genetic architecture between populations. As such, K-kernel is useful to study the problem of the design of training populations. K-kernel was compared to other covariance estimators or kernels to examine its fit to the data, cross-validated accuracy and suitability for GWAS on several datasets. It provides a significantly better fit to the data than the genomic best linear unbiased prediction model and, in some cases it performs better than other kernels such as the Gaussian kernel, as shown by an empirical null distribution. In GWAS simulations, alternative kernels control type I errors as well as or better than the classical whole-genome kinship and increase statistical power. No or small gains were observed in cross-validated prediction accuracy. This alternative
Are Low-order Covariance Estimates Useful in Error Analyses?
Baker, D. F.; Schimel, D.
2005-12-01
Atmospheric trace gas inversions, using modeled atmospheric transport to infer surface sources and sinks from measured concentrations, are most commonly done using least-squares techniques that return not only an estimate of the state (the surface fluxes) but also the covariance matrix describing the uncertainty in that estimate. Besides allowing one to place error bars around the estimate, the covariance matrix may be used in simulation studies to learn what uncertainties would be expected from various hypothetical observing strategies. This error analysis capability is routinely used in designing instrumentation, measurement campaigns, and satellite observing strategies. For example, Rayner, et al (2002) examined the ability of satellite-based column-integrated CO2 measurements to constrain monthly-average CO2 fluxes for about 100 emission regions using this approach. Exact solutions for both state vector and covariance matrix become computationally infeasible, however, when the surface fluxes are solved at finer resolution (e.g., daily in time, under 500 km in space). It is precisely at these finer scales, however, that one would hope to be able to estimate fluxes using high-density satellite measurements. Non-exact estimation methods such as variational data assimilation or the ensemble Kalman filter could be used, but they achieve their computational savings by obtaining an only approximate state estimate and a low-order approximation of the true covariance. One would like to be able to use this covariance matrix to do the same sort of error analyses as are done with the full-rank covariance, but is it correct to do so? Here we compare uncertainties and `information content' derived from full-rank covariance matrices obtained from a direct, batch least squares inversion to those from the incomplete-rank covariance matrices given by a variational data assimilation approach solved with a variable metric minimization technique (the Broyden-Fletcher- Goldfarb
Extreme eigenvalues of sample covariance and correlation matrices
DEFF Research Database (Denmark)
Heiny, Johannes
This thesis is concerned with asymptotic properties of the eigenvalues of high-dimensional sample covariance and correlation matrices under an infinite fourth moment of the entries. In the first part, we study the joint distributional convergence of the largest eigenvalues of the sample covariance...... matrix of a p-dimensional heavy-tailed time series when p converges to infinity together with the sample size n. We generalize the growth rates of p existing in the literature. Assuming a regular variation condition with tail index ... eigenvalues are essentially determined by the extreme order statistics from an array of iid random variables. The asymptotic behavior of the extreme eigenvalues is then derived routinely from classical extreme value theory. The resulting approximations are strikingly simple considering the high dimension...
Needs for evaluated covariance data for reactor pressure vessel dosimetry
International Nuclear Information System (INIS)
Maerker, R.E.; Broadhead, B.L.; Wagschal, J.J.
1992-01-01
This report discusses new methodology for quantifying and then reducing uncertainties in the calculated pressure vessel fluences of a pressurized water reactor (PWR). The technique involves combining the integral results of the calculated and measured PWR surveillance dosimetry activities with the differential data used in the calculations, along with covariances of all the quantities, into a generalized linear least-squares adjustment procedure. Based on analysis of both PWRs and test reactor benchmarks, substantial evidence now exists to support the conclusion that, of all the nuclear as well as non-nuclear differential data considered, ENDF/B-VI values of the total inelastic iron cross sections and their covariances are the most important data controlling the outcome of the adjustment procedure. Predicted adjustments in these cross sections provided the stimulus for new measurements, the results of which impacted the ENDF/B-VI evaluation of iron 56
DANTE, Activation Analysis Neutron Spectra Unfolding by Covariance Matrix Method
International Nuclear Information System (INIS)
Petilli, M.
1981-01-01
1 - Description of problem or function: The program evaluates activation measurements of reactor neutron spectra and unfolds the results for dosimetry purposes. Different evaluation options are foreseen: absolute or relative fluxes and different iteration algorithms. 2 - Method of solution: A least-square fit method is used. A correlation between available data and their uncertainties has been introduced by means of flux and activity variance-covariance matrices. Cross sections are assumed to be constant, i.e. with variance-covariance matrix equal to zero. The Lagrange multipliers method has been used for calculating the solution. 3 - Restrictions on the complexity of the problem: 9 activation experiments can be analyzed. 75 energy groups are accepted
Isotropic covariance functions on graphs and their edges
DEFF Research Database (Denmark)
Anderes, E.; Møller, Jesper; Rasmussen, Jakob Gulddahl
We develop parametric classes of covariance functions on linear networks and their extension to graphs with Euclidean edges, i.e., graphs with edges viewed as line segments or more general sets with a coordinate system allowing us to consider points on the graph which are vertices or points...... on an edge. Our covariance functions are defined on the vertices and edge points of these graphs and are isotropic in the sense that they depend only on the geodesic distance or on a new metric called the resistance metric (which extends the classical resistance metric developed in electrical network theory...... functions in the spatial statistics literature (the power exponential, Matérn, generalized Cauchy, and Dagum classes) are shown to be valid with respect to the resistance metric for any graph with Euclidean edges, whilst they are only valid with respect to the geodesic metric in more special cases....
Quantum corrections for the cubic Galileon in the covariant language
Energy Technology Data Exchange (ETDEWEB)
Saltas, Ippocratis D. [Institute of Astrophysics and Space Sciences, Faculty of Sciences, Campo Grande, PT1749-016 Lisboa (Portugal); Vitagliano, Vincenzo, E-mail: isaltas@fc.ul.pt, E-mail: vincenzo.vitagliano@ist.utl.pt [Multidisciplinary Center for Astrophysics and Department of Physics, Instituto Superior Técnico, University of Lisbon, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)
2017-05-01
We present for the first time an explicit exposition of quantum corrections within the cubic Galileon theory including the effect of quantum gravity, in a background- and gauge-invariant manner, employing the field-reparametrisation approach of the covariant effective action at 1-loop. We show that the consideration of gravitational effects in combination with the non-linear derivative structure of the theory reveals new interactions at the perturbative level, which manifest themselves as higher-operators in the associated effective action, which' relevance is controlled by appropriate ratios of the cosmological vacuum and the Galileon mass scale. The significance and concept of the covariant approach in this context is discussed, while all calculations are explicitly presented.
Markov modulated Poisson process models incorporating covariates for rainfall intensity.
Thayakaran, R; Ramesh, N I
2013-01-01
Time series of rainfall bucket tip times at the Beaufort Park station, Bracknell, in the UK are modelled by a class of Markov modulated Poisson processes (MMPP) which may be thought of as a generalization of the Poisson process. Our main focus in this paper is to investigate the effects of including covariate information into the MMPP model framework on statistical properties. In particular, we look at three types of time-varying covariates namely temperature, sea level pressure, and relative humidity that are thought to be affecting the rainfall arrival process. Maximum likelihood estimation is used to obtain the parameter estimates, and likelihood ratio tests are employed in model comparison. Simulated data from the fitted model are used to make statistical inferences about the accumulated rainfall in the discrete time interval. Variability of the daily Poisson arrival rates is studied.
Measuring covariation in RNA alignments: Physical realism improves information measures
DEFF Research Database (Denmark)
Lindgreen, Stinus; Gardner, Paul Phillip; Krogh, Anders
2006-01-01
Motivation: The importance of non-coding RNAs is becoming increasingly evident, and often the function of these molecules depends on the structure. It is common to use alignments of related RNA sequences to deduce the consensus secondary structure by detecting patterns of co-evolution. A central...... part of such an analysis is to measure covariation between two positions in an alignment. Here, we rank various measures ranging from simple mutual information to more advanced covariation measures. Results: Mutual information is still used for secondary structure prediction, but the results...... of this study indicate which measures are useful. Incorporating more structural information by considering e.g. indels and stacking improves accuracy, suggesting that physically realistic measures yield improved predictions. This can be used to improve both current and future programs for secondary structure...
On a covariant formulation of the Barbero-Immirzi connection
International Nuclear Information System (INIS)
Fatibene, L; Francaviglia, M; Rovelli, C
2007-01-01
The Barbero-Immirzi (BI) connection, as usually introduced out of a spin connection, is a global object though it does not transform properly as a genuine connection with respect to generic spin transformations, unless quite specific and suitable gauges are imposed. Here we shall investigate whether, and under which global conditions, a (properly transforming and hence global) SU(2)-connection can be canonically defined in a gauge covariant way. Such an SU(2)-connection locally agrees with the usual BI connection and it can be defined on pretty general bundles; in particular, triviality is not assumed. As a by-product we shall also introduce a global covariant SU(2)-connection over the whole spacetime (while for technical reasons the BI connection in the standard formulation is just introduced on a space slice) which restricts to the usual BI connection on a space slice
How (not) to teach Lorentz covariance of the Dirac equation
International Nuclear Information System (INIS)
Nikolić, Hrvoje
2014-01-01
In the textbook proofs of the Lorentz covariance of the Dirac equation, one treats the wave function as a spinor and gamma matrices as scalars, leading to a quite complicated formalism with several pedagogic drawbacks. As an alternative, I propose to teach the Dirac equation and its Lorentz covariance by using a much simpler, but physically equivalent formalism, in which these drawbacks do not appear. In this alternative formalism, the wave function transforms as a scalar and gamma matrices as components of a vector, such that the standard physically relevant bilinear combinations do not change their transformation properties. The alternative formalism allows also a natural construction of some additional non-standard bilinear combinations with well-defined transformation properties. (paper)
Working covariance model selection for generalized estimating equations.
Carey, Vincent J; Wang, You-Gan
2011-11-20
We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice. Copyright © 2011 John Wiley & Sons, Ltd.
Lorentz covariance ‘almost’ implies electromagnetism and more
International Nuclear Information System (INIS)
Sobouti, Y
2015-01-01
Beginning from two simple assumptions, (i) the speed of light is a universal constant, or its equivalent, the spacetime intervals are Lorentz invariant, and (ii) there are mutually interacting particles, with a covariant ‘source-field’ equation, one arrives at a class of field equations of which the standard electromagnetism (EM) and electrodynamics are special cases. The formalism, depending on how one formulates the source-field equation, allows one to speculate magnetic monopoles, massive photons, nonlinear EMs, and more. (paper)
Hydrodynamic Covariant Symplectic Structure from Bilinear Hamiltonian Functions
Directory of Open Access Journals (Sweden)
Capozziello S.
2005-07-01
Full Text Available Starting from generic bilinear Hamiltonians, constructed by covariant vector, bivector or tensor fields, it is possible to derive a general symplectic structure which leads to holonomic and anholonomic formulations of Hamilton equations of motion directly related to a hydrodynamic picture. This feature is gauge free and it seems a deep link common to all interactions, electromagnetism and gravity included. This scheme could lead toward a full canonical quantization.
Do Time-Varying Covariances, Volatility Comovement and Spillover Matter?
Lakshmi Balasubramanyan
2005-01-01
Financial markets and their respective assets are so intertwined; analyzing any single market in isolation ignores important information. We investigate whether time varying volatility comovement and spillover impact the true variance-covariance matrix under a time-varying correlation set up. Statistically significant volatility spillover and comovement between US, UK and Japan is found. To demonstrate the importance of modelling volatility comovement and spillover, we look at a simple portfo...
Testing power-law cross-correlations: Rescaled covariance test
Czech Academy of Sciences Publication Activity Database
Krištoufek, Ladislav
2013-01-01
Roč. 86, č. 10 (2013), 418-1-418-15 ISSN 1434-6028 R&D Projects: GA ČR GA402/09/0965 Institutional support: RVO:67985556 Keywords : power-law cross-correlations * testing * long-term memory Subject RIV: AH - Economics Impact factor: 1.463, year: 2013 http://library.utia.cas.cz/separaty/2013/E/kristoufek-testing power-law cross-correlations rescaled covariance test.pdf
Co-movements among financial stocks and covariance matrix analysis
Sharifi, Saba
2003-01-01
The major theories of finance leading into the main body of this research are discussed and our experiments on studying the risk and co-movements among stocks are presented. This study leads to the application of Random Matrix Theory (RMT) The idea of this theory refers to the importance of the empirically measured correlation (or covariance) matrix, C, in finance and particularly in the theory of optimal portfolios However, this matrix has recently come into question, as a large part of ...
Experimental asymmetric phase-covariant quantum cloning of polarization qubits
Czech Academy of Sciences Publication Activity Database
Soubusta, Jan; Bartůšková, L.; Černoch, Antonín; Dušek, M.; Fiurášek, J.
2008-01-01
Roč. 78, č. 5 (2008), 052323/1-052323/7 ISSN 1050-2947 R&D Projects: GA MŠk(CZ) 1M06002 Grant - others:GAMŠk(CZ) LC06007 Program:LC Institutional research plan: CEZ:AV0Z10100522 Keywords : phase-covariant cloning * quantum information processing Subject RIV: BH - Optics, Masers, Lasers Impact factor: 2.908, year: 2008
The Higgs mechanism in a covariant-gauge formalism
International Nuclear Information System (INIS)
Yokoyama, Kan-ichi; Kubo, Reijiro.
1975-02-01
In a covariant-gauge formalism for gauge fields the Higgs mechanism is investigated under a spontaneous breakdown of gauge invariance. It is shown that the Goldstone bosons are in general described by a dipole-ghost field and can be consistently eliminated from the physical state-vector space by supplementary conditions. By an asymptotic condition for the relevant fields, field equations and commutators of asymptotic fields are determined. A renormalization problem and an aspect concerning gauge transformations are also discussed. (auth.)
Covariant Bethe-Salpeter wave functions for heavy hadrons
International Nuclear Information System (INIS)
Hussain, F.
1992-09-01
In recent years the dynamics of heavy mesons and baryons has considerably simplified by the development of the so-called heavy quark effective theory (HQET). A covariant formulation of heavy meson and heavy baryon decays in the leading order of the HQET is presented. The method is based on a Bethe-Salpeter formulation in the limit of the heavy quark mass going to infinity. 15 refs, 4 figs
Bayesian source term determination with unknown covariance of measurements
Belal, Alkomiet; Tichý, Ondřej; Šmídl, Václav
2017-04-01
Determination of a source term of release of a hazardous material into the atmosphere is a very important task for emergency response. We are concerned with the problem of estimation of the source term in the conventional linear inverse problem, y = Mx, where the relationship between the vector of observations y is described using the source-receptor-sensitivity (SRS) matrix M and the unknown source term x. Since the system is typically ill-conditioned, the problem is recast as an optimization problem minR,B(y - Mx)TR-1(y - Mx) + xTB-1x. The first term minimizes the error of the measurements with covariance matrix R, and the second term is a regularization of the source term. There are different types of regularization arising for different choices of matrices R and B, for example, Tikhonov regularization assumes covariance matrix B as the identity matrix multiplied by scalar parameter. In this contribution, we adopt a Bayesian approach to make inference on the unknown source term x as well as unknown R and B. We assume prior on x to be a Gaussian with zero mean and unknown diagonal covariance matrix B. The covariance matrix of the likelihood R is also unknown. We consider two potential choices of the structure of the matrix R. First is the diagonal matrix and the second is a locally correlated structure using information on topology of the measuring network. Since the inference of the model is intractable, iterative variational Bayes algorithm is used for simultaneous estimation of all model parameters. The practical usefulness of our contribution is demonstrated on an application of the resulting algorithm to real data from the European Tracer Experiment (ETEX). This research is supported by EEA/Norwegian Financial Mechanism under project MSMT-28477/2014 Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI).
Treatment of Nuclear Data Covariance Information in Sample Generation
Energy Technology Data Exchange (ETDEWEB)
Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Adams, Brian M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wieselquist, William [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Reactor and Nuclear Systems Division
2017-10-01
This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on developing a sampling capability that can handle the challenges of generating samples from nuclear cross-section data. The covariance information between energy groups tends to be very ill-conditioned and thus poses a problem using traditional methods for generated correlated samples. This report outlines a method that addresses the sample generation from cross-section matrices.
Treatment of Nuclear Data Covariance Information in Sample Generation
International Nuclear Information System (INIS)
Swiler, Laura Painton; Adams, Brian M.; Wieselquist, William
2017-01-01
This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on developing a sampling capability that can handle the challenges of generating samples from nuclear cross-section data. The covariance information between energy groups tends to be very ill-conditioned and thus poses a problem using traditional methods for generated correlated samples. This report outlines a method that addresses the sample generation from cross-section matrices.
Solid-state NMR covariance of homonuclear correlation spectra.
Hu, Bingwen; Amoureux, Jean-Paul; Trebosc, Julien; Deschamps, Michael; Tricot, Gregory
2008-04-07
Direct covariance NMR spectroscopy, which does not involve a Fourier transformation along the indirect dimension, is demonstrated to obtain homonuclear correlation two-dimensional (2D) spectra in the solid state. In contrast to the usual 2D Fourier transform (2D-FT) NMR, in a 2D covariance (2D-Cov) spectrum the spectral resolution in the indirect dimension is determined by the resolution along the detection dimension, thereby largely reducing the time-consuming indirect sampling requirement. The covariance method does not need any separate phase correction or apodization along the indirect dimension because it uses those applied in the detection dimension. We compare in detail the specifications obtained with 2D-FT and 2D-Cov, for narrow and broad resonances. The efficiency of the covariance data treatment is demonstrated in organic and inorganic samples that are both well crystallized and amorphous, for spin -1/2 nuclei with 13C, 29Si, and 31P through-space or through-bond homonuclear 2D correlation spectra. In all cases, the experimental time has been reduced by at least a factor of 10, without any loss of resolution and signal to noise ratio, with respect to what is necessary with the 2D-FT NMR. According to this method, we have been able to study the silicate network of glasses by 2D NMR within reasonable experimental time despite the very long relaxation time of the 29Si nucleus. The main limitation of the 2D-Cov data treatment is related to the introduction of autocorrelated peaks onto the diagonal, which does not represent any actual connectivity.
The Goodness of Covariance Selection Problem from AUC Bounds
Khajavi, Navid Tafaghodi; Kuh, Anthony
2016-01-01
We conduct a study of graphical models and discuss the quality of model selection approximation by formulating the problem as a detection problem and examining the area under the curve (AUC). We are specifically looking at the model selection problem for jointly Gaussian random vectors. For Gaussian random vectors, this problem simplifies to the covariance selection problem which is widely discussed in literature by Dempster [1]. In this paper, we give the definition for the correlation appro...
Chiral phase transition in a covariant nonlocal NJL model
International Nuclear Information System (INIS)
General, I.; Scoccola, N.N.
2001-01-01
The properties of the chiral phase transition at finite temperature and chemical potential are investigated within a nonlocal covariant extension of the NJL model based on a separable quark-quark interaction. We find that for low values of T the chiral transition is always of first order and, for finite quark masses, at certain end point the transition turns into a smooth crossover. Our predictions for the position of this point is similar, although somewhat smaller, than previous estimates. (author)
Estimating correlation and covariance matrices by weighting of market similarity
Michael C. M\\"unnix; Rudi Sch\\"afer; Oliver Grothe
2010-01-01
We discuss a weighted estimation of correlation and covariance matrices from historical financial data. To this end, we introduce a weighting scheme that accounts for similarity of previous market conditions to the present one. The resulting estimators are less biased and show lower variance than either unweighted or exponentially weighted estimators. The weighting scheme is based on a similarity measure which compares the current correlation structure of the market to the structures at past ...
Evaluating dynamic covariance matrix forecasting and portfolio optimization
Sendstad, Lars Hegnes; Holten, Dag Martin
2012-01-01
In this thesis we have evaluated the covariance forecasting ability of the simple moving average, the exponential moving average and the dynamic conditional correlation models. Overall we found that a dynamic portfolio can gain significant improvements by implementing a multivariate GARCH forecast. We further divided the global investment universe into sectors and regions in order to investigate the relative portfolio performance of several asset allocation strategies with both variance and c...
OD Covariance in Conjunction Assessment: Introduction and Issues
Hejduk, M. D.; Duncan, M.
2015-01-01
Primary and secondary covariances combined and projected into conjunction plane (plane perpendicular to relative velocity vector at TCA) Primary placed on x-axis at (miss distance, 0) and represented by circle of radius equal to sum of both spacecraft circumscribing radiiZ-axis perpendicular to x-axis in conjunction plane Pc is portion of combined error ellipsoid that falls within the hard-body radius circle
Estimation of Fuzzy Measures Using Covariance Matrices in Gaussian Mixtures
Directory of Open Access Journals (Sweden)
Nishchal K. Verma
2012-01-01
Full Text Available This paper presents a novel computational approach for estimating fuzzy measures directly from Gaussian mixtures model (GMM. The mixture components of GMM provide the membership functions for the input-output fuzzy sets. By treating consequent part as a function of fuzzy measures, we derived its coefficients from the covariance matrices found directly from GMM and the defuzzified output constructed from both the premise and consequent parts of the nonadditive fuzzy rules that takes the form of Choquet integral. The computational burden involved with the solution of λ-measure is minimized using Q-measure. The fuzzy model whose fuzzy measures were computed using covariance matrices found in GMM has been successfully applied on two benchmark problems and one real-time electric load data of Indian utility. The performance of the resulting model for many experimental studies including the above-mentioned application is found to be better and comparable to recent available fuzzy models. The main contribution of this paper is the estimation of fuzzy measures efficiently and directly from covariance matrices found in GMM, avoiding the computational burden greatly while learning them iteratively and solving polynomial equations of order of the number of input-output variables.
MIMO Radar Transmit Beampattern Design Without Synthesising the Covariance Matrix
Ahmed, Sajid
2013-10-28
Compared to phased-array, multiple-input multiple-output (MIMO) radars provide more degrees-offreedom (DOF) that can be exploited for improved spatial resolution, better parametric identifiability, lower side-lobe levels at the transmitter/receiver, and design variety of transmit beampatterns. The design of the transmit beampattern generally requires the waveforms to have arbitrary auto- and crosscorrelation properties. The generation of such waveforms is a two step complicated process. In the first step a waveform covariance matrix is synthesised, which is a constrained optimisation problem. In the second step, to realise this covariance matrix actual waveforms are designed, which is also a constrained optimisation problem. Our proposed scheme converts this two step constrained optimisation problem into a one step unconstrained optimisation problem. In the proposed scheme, in contrast to synthesising the covariance matrix for the desired beampattern, nT independent finite-alphabet constantenvelope waveforms are generated and pre-processed, with weight matrix W, before transmitting from the antennas. In this work, two weight matrices are proposed that can be easily optimised for the desired symmetric and non-symmetric beampatterns and guarantee equal average power transmission from each antenna. Simulation results validate our claims.
Complete super-sample lensing covariance in the response approach
Barreira, Alexandre; Krause, Elisabeth; Schmidt, Fabian
2018-06-01
We derive the complete super-sample covariance (SSC) of the matter and weak lensing convergence power spectra using the power spectrum response formalism to accurately describe the coupling of super- to sub-survey modes. The SSC term is completely characterized by the survey window function, the nonlinear matter power spectrum and the full first-order nonlinear power spectrum response function, which describes the response to super-survey density and tidal field perturbations. Generalized separate universe simulations can efficiently measure these responses in the nonlinear regime of structure formation, which is necessary for lensing applications. We derive the lensing SSC formulae for two cases: one under the Limber and flat-sky approximations, and a more general one that goes beyond the Limber approximation in the super-survey mode and is valid for curved sky applications. Quantitatively, we find that for sky fractions fsky ≈ 0.3 and a single source redshift at zS=1, the use of the flat-sky and Limber approximation underestimates the total SSC contribution by ≈ 10%. The contribution from super-survey tidal fields to the lensing SSC, which has not been included in cosmological analyses so far, is shown to represent about 5% of the total lensing covariance on multipoles l1,l2 gtrsim 300. The SSC is the dominant off-diagonal contribution to the total lensing covariance, making it appropriate to include these tidal terms and beyond flat-sky/Limber corrections in cosmic shear analyses.
A geometric rationale for invariance, covariance and constitutive relations
Romano, Giovanni; Barretta, Raffaele; Diaco, Marina
2018-01-01
There are, in each branch of science, statements which, expressed in ambiguous or even incorrect but seemingly friendly manner, were repeated for a long time and eventually became diffusely accepted. Objectivity of physical fields and of their time rates and frame indifference of constitutive relations are among such notions. A geometric reflection on the description of frame changes as spacetime automorphisms, on induced push-pull transformations and on proper physico-mathematical definitions of material, spatial and spacetime tensor fields and of their time-derivatives along the motion, is here carried out with the aim of pointing out essential notions and of unveiling false claims. Theoretical and computational aspects of nonlinear continuum mechanics, and especially those pertaining to constitutive relations, involving material fields and their time rates, gain decisive conceptual and operative improvement from a proper geometric treatment. Outcomes of the geometric analysis are frame covariance of spacetime velocity, material stretching and material spin. A univocal and frame-covariant tool for evaluation of time rates of material fields is provided by the Lie derivative along the motion. The postulate of frame covariance of material fields is assessed to be a natural physical requirement which cannot interfere with the formulation of constitutive laws, with claims of the contrary stemming from an improper imposition of equality in place of equivalence.
Do current cosmological observations rule out all covariant Galileons?
Peirone, Simone; Frusciante, Noemi; Hu, Bin; Raveri, Marco; Silvestri, Alessandra
2018-03-01
We revisit the cosmology of covariant Galileon gravity in view of the most recent cosmological data sets, including weak lensing. As a higher derivative theory, covariant Galileon models do not have a Λ CDM limit and predict a very different structure formation pattern compared with the standard Λ CDM scenario. Previous cosmological analyses suggest that this model is marginally disfavored, yet cannot be completely ruled out. In this work we use a more recent and extended combination of data, and we allow for more freedom in the cosmology, by including a massive neutrino sector with three different mass hierarchies. We use the Planck measurements of cosmic microwave background temperature and polarization; baryonic acoustic oscillations measurements by BOSS DR12; local measurements of H0; the joint light-curve analysis supernovae sample; and, for the first time, weak gravitational lensing from the KiDS Collaboration. We find, that in order to provide a reasonable fit, a nonzero neutrino mass is indeed necessary, but we do not report any sizable difference among the three neutrino hierarchies. Finally, the comparison of the Bayesian evidence to the Λ CDM one shows that in all the cases considered, covariant Galileon models are statistically ruled out by cosmological data.
Supersymmetric gauged scale covariance in ten and lower dimensions
International Nuclear Information System (INIS)
Nishino, Hitoshi; Rajpoot, Subhash
2004-01-01
We present globally supersymmetric models of gauged scale covariance in ten, six, and four dimensions. This is an application of a recent similar gauging in three dimensions for a massive self-dual vector multiplet. In ten dimensions, we couple a single vector multiplet to another vector multiplet, where the latter gauges the scale covariance of the former. Due to scale covariance, the system does not have a Lagrangian formulation, but has only a set of field equations, like Type IIB supergravity in ten dimensions. As by-products, we construct similar models in six dimensions with N=(2,0) supersymmetry, and four dimensions with N=1 supersymmetry. We finally get a similar model with N=4 supersymmetry in four dimensions with consistent interactions that have never been known before. We expect a series of descendant theories in dimensions lower than ten by dimensional reductions. This result also indicates that similar mechanisms will work for other vector and scalar multiplets in space-time lower than ten dimensions
Propagation of nuclear data uncertainty: Exact or with covariances
Directory of Open Access Journals (Sweden)
van Veen D.
2010-10-01
Full Text Available Two distinct methods of propagation for basic nuclear data uncertainties to large scale systems will be presented and compared. The “Total Monte Carlo” method is using a statistical ensemble of nuclear data libraries randomly generated by means of a Monte Carlo approach with the TALYS system. These libraries are then directly used in a large number of reactor calculations (for instance with MCNP after which the exact probability distribution for the reactor parameter is obtained. The second method makes use of available covariance files and can be done in a single reactor calculation (by using the perturbation method. In this exercise, both methods are using consistent sets of data files, which implies that covariance files used in the second method are directly obtained from the randomly generated nuclear data libraries from the first method. This is a unique and straightforward comparison allowing to directly apprehend advantages and drawbacks of each method. Comparisons for different reactions and criticality-safety benchmarks from 19F to actinides will be presented. We can thus conclude whether current methods for using covariance data are good enough or not.
Statistical mechanics of learning orthogonal signals for general covariance models
International Nuclear Information System (INIS)
Hoyle, David C
2010-01-01
Statistical mechanics techniques have proved to be useful tools in quantifying the accuracy with which signal vectors are extracted from experimental data. However, analysis has previously been limited to specific model forms for the population covariance C, which may be inappropriate for real world data sets. In this paper we obtain new statistical mechanical results for a general population covariance matrix C. For data sets consisting of p sample points in R N we use the replica method to study the accuracy of orthogonal signal vectors estimated from the sample data. In the asymptotic limit of N,p→∞ at fixed α = p/N, we derive analytical results for the signal direction learning curves. In the asymptotic limit the learning curves follow a single universal form, each displaying a retarded learning transition. An explicit formula for the location of the retarded learning transition is obtained and we find marked variation in the location of the retarded learning transition dependent on the distribution of population covariance eigenvalues. The results of the replica analysis are confirmed against simulation
Weak lensing of the cosmic microwave background: Power spectrum covariance
International Nuclear Information System (INIS)
Cooray, Asantha
2002-01-01
We discuss the non-Gaussian contribution to the power spectrum covariance of cosmic microwave background (CMB) anisotropies resulting through weak gravitational lensing angular deflections and the correlation of deflections with secondary sources of temperature fluctuations generated by the large scale structure, such as the integrated Sachs-Wolfe effect and the Sunyaev-Zel'dovich effect. This additional contribution to the covariance of binned angular power spectrum, beyond the well known cosmic variance and any associated instrumental noise, results from a trispectrum, or a four point correlation function, in temperature anisotropy data. With substantially wide bins in multipole space, the resulting non-Gaussian contribution from lensing to the binned power spectrum variance is insignificant out to multipoles of a few thousand and is not likely to affect the cosmological parameter estimation with acoustic peaks and the damping tail. The non-Gaussian contribution to covariance, however, should be considered when interpreting binned CMB power spectrum measurements at multipoles of a few thousand corresponding to angular scales of few arcminutes and less
A Small Guide to Generating Covariances of Experimental Data
International Nuclear Information System (INIS)
Mannhart, Wolf
2011-05-01
A complete description of the uncertainties of an experiment can only be realized by a detailed list of all the uncertainty components, their value and a specification of existing correlations between the data. Based on such information the covariance matrix can be generated, which is necessary for any further proceeding with the experimental data. It is not necessary, and not recommended, that an experimenter evaluates this covariance matrix. The reason for this is that a incorrectly evaluated final covariance matrix can never be corrected if the details are not given. (Such obviously wrong covariance matrices have recently occasionally been found in the literature). Hence quotation of a covariance matrix is an additional step which should not occur without quoting a detailed list of the various uncertainty components and their correlations as well. It must be hoped that editors of journals will understand these necessary requirements. The generalized least squares procedure shown permits an easy way of interchanging data D 0 with parameter estimates P. This means new data can easily be combined with an earlier evaluation. However, it must be mentioned that this is only valid as long as the new data have no correlation with any of the older data of the prior evaluation. Otherwise the old data which show correlation with new data have to be extracted from the evaluation and then, together with the new data and taking account of the correlation, have again to be added to the reduced evaluation. In most cases this step cannot be performed and the evaluation has to be completely redone. A partial way out is given if the evaluation is performed step by step and the results of each step are stored. Then the evaluation need only be repeated from the step which contains correlated data for the first time while all earlier steps remain unchanged. Finally it should be noted that the addition of a small set of new data to a prior evaluation consisting of a large number of
ERRORJ, Multigroup covariance matrices generation from ENDF-6 format
International Nuclear Information System (INIS)
Chiba, Go
2007-01-01
1 - Description of program or function: ERRORJ produces multigroup covariance matrices from ENDF-6 format following mainly the methods of the ERRORR module in NJOY94.105. New version differs from previous version in the following features: Additional features in ERRORJ with respect to the NJOY94.105/ERRORR module: - expands processing for the covariance matrices of resolved and unresolved resonance parameters; - processes average cosine of scattering angle and fission spectrum; - treats cross-correlation between different materials and reactions; - accepts input of multigroup constants with various forms (user input, GENDF, etc.); - outputs files with various formats through utility NJOYCOVX (COVERX format, correlation matrix, relative error and standard deviation); - uses a 1% sensitivity method for processing of resonance parameters; - ERRORJ can process the JENDL-3.2 and 3.3 covariance matrices. Additional features of the version 2 with respect to the previous version of ERRORJ: - Since the release of version 2, ERRORJ has been modified to increase its reliability and stability, - calculation of the correlation coefficients in the resonance region, - Option for high-speed calculation is implemented, - Perturbation amount is optimised in a sensitivity calculation, - Effect of the resonance self-shielding can be considered, - a compact covariance format (LCOMP=2) proposed by N. M. Larson can be read. Additional features of the version 2.2.1 with respect to the previous version of ERRORJ: - Several routines were modified to reduce calculation time. The new one needs shorter calculation time (50-70%) than the old version without changing results. - In the U-233 and Pu-241 files of JENDL-3.3 an inconsistency between resonance parameters in MF=32 and those in MF=2 was corrected. NEA-1676/06: This version differs from the previous one (NEA-1676/05) in the following: ERRORJ2.2.1 was modified to treat the self-shielding effect accurately. NEA-1676/07: This version
Directory of Open Access Journals (Sweden)
Tania Dehesh
2015-01-01
Full Text Available Background. Univariate meta-analysis (UM procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS method as a multivariate meta-analysis approach. Methods. We evaluated the efficiency of four new approaches including zero correlation (ZC, common correlation (CC, estimated correlation (EC, and multivariate multilevel correlation (MMC on the estimation bias, mean square error (MSE, and 95% probability coverage of the confidence interval (CI in the synthesis of Cox proportional hazard models coefficients in a simulation study. Result. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. Conclusion. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.
Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi
2015-01-01
Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.
A cautionary note on generalized linear models for covariance of unbalanced longitudinal data
Huang, Jianhua Z.; Chen, Min; Maadooliat, Mehdi; Pourahmadi, Mohsen
2012-01-01
Missing data in longitudinal studies can create enormous challenges in data analysis when coupled with the positive-definiteness constraint on a covariance matrix. For complete balanced data, the Cholesky decomposition of a covariance matrix makes
Continuous Covariate Imbalance and Conditional Power for Clinical Trial Interim Analyses
Ciolino, Jody D.; Martin, Renee' H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.
2014-01-01
Oftentimes valid statistical analyses for clinical trials involve adjustment for known influential covariates, regardless of imbalance observed in these covariates at baseline across treatment groups. Thus, it must be the case that valid interim analyses also properly adjust for these covariates. There are situations, however, in which covariate adjustment is not possible, not planned, or simply carries less merit as it makes inferences less generalizable and less intuitive. In this case, covariate imbalance between treatment groups can have a substantial effect on both interim and final primary outcome analyses. This paper illustrates the effect of influential continuous baseline covariate imbalance on unadjusted conditional power (CP), and thus, on trial decisions based on futility stopping bounds. The robustness of the relationship is illustrated for normal, skewed, and bimodal continuous baseline covariates that are related to a normally distributed primary outcome. Results suggest that unadjusted CP calculations in the presence of influential covariate imbalance require careful interpretation and evaluation. PMID:24607294
Cross-covariance functions for multivariate random fields based on latent dimensions
Apanasovich, T. V.; Genton, M. G.
2010-01-01
The problem of constructing valid parametric cross-covariance functions is challenging. We propose a simple methodology, based on latent dimensions and existing covariance models for univariate random fields, to develop flexible, interpretable
Contributions to Estimation and Testing Block Covariance Structures in Multivariate Normal Models
Liang, Yuli
2015-01-01
This thesis concerns inference problems in balanced random effects models with a so-called block circular Toeplitz covariance structure. This class of covariance structures describes the dependency of some specific multivariate two-level data when both compound symmetry and circular symmetry appear simultaneously. We derive two covariance structures under two different invariance restrictions. The obtained covariance structures reflect both circularity and exchangeability present in the data....
Covariance of time-ordered products implies local commutativity of fields
International Nuclear Information System (INIS)
Greenberg, O.W.
2006-01-01
We formulate Lorentz covariance of a quantum field theory in terms of covariance of time-ordered products (or other Green's functions). This formulation of Lorentz covariance implies spacelike local commutativity or anticommutativity of fields, sometimes called microscopic causality or microcausality. With this formulation microcausality does not have to be taken as a separate assumption
Kiehn, R. M.
1976-01-01
With respect to irreversible, non-homeomorphic maps, contravariant and covariant tensor fields have distinctly natural covariance and transformational behavior. For thermodynamic processes which are non-adiabatic, the fact that the process cannot be represented by a homeomorphic map emphasizes the logical arrow of time, an idea which encompasses a principle of retrodictive determinism for covariant tensor fields.
Fast covariance estimation for innovations computed from a spatial Gibbs point process
DEFF Research Database (Denmark)
Coeurjolly, Jean-Francois; Rubak, Ege
In this paper, we derive an exact formula for the covariance of two innovations computed from a spatial Gibbs point process and suggest a fast method for estimating this covariance. We show how this methodology can be used to estimate the asymptotic covariance matrix of the maximum pseudo...
Scale-covariant theory of gravitation and astrophysical applications
International Nuclear Information System (INIS)
Canuto, V.; Adams, P.J.; Hsieh, S.; Tsiang, E.
1977-01-01
By associating the mathematical operation of scale transformation with the physics of using different dynamical systems to measure space-time distances, we formulate a scale-covariant theory of gravitation. Corresponding to each dynamical system of units is a gauge condition which determines the otherwise arbitrary gauge function. For gravitational units, the gauge condition is chosen so that the standard Einstein equations are recovered. Assuming the atomic units, derivable from atomic dynamics, to be distinct from the gravitational units, a different gauge condition must be imposed. It is suggested that Dirac's large-number hypothesis be used for the determination of this condition so that gravitational phenomena can be described in atomic units. The result allows a natural interpretation of the possible variation of the gravitational constant without compromising the validity of general relativity. A geometrical interpretation of the scale-covariant theory is possible if the covariant tensors in Riemannian space are replaced by cocovariant cotensors in an integrable Weyl space. A scale-invariant action principle is constructed from the metrical potentials of the integrable Weyl space. Application of the dynamical equations in atomic units to cosmology yields a family of homogeneous solutions characterized by R approx. t for large cosmological times. Equations of motion in atomic units are solved for spherically symmetric gravitational fields. Expressions for perihelion shift and light deflection are derived. They do not differ from the predictions of general relativity except for secular variations, having the age of the universe as a time scale. Similar variations of periods and radii for planetary orbits are also derived
Static and Covariant Meson-Exchange Interactions in Nuclear Matter
International Nuclear Information System (INIS)
Carlson, B.V.; Hirata, D.
2011-01-01
The Dirac version of static meson exchange interactions provides a good description of low-energy NN scattering as well as very reasonable saturation properties in Dirac-Brueckner calculations of nuclear matter. We include retardation terms to make these interactions covariant and readjust the coupling constants so as to maintain a reasonable description of NN scattering. In this case, we find the Dirac-Brueckner approximation to nuclear matter to be extremely overbound. The Bonn meson-exchange interactions provide a good fit to low-energy nucleon-nucleon scattering and the deuteron binding energy using a static interaction and the Thompson form of the reduced two-nucleon interaction. We have readjusted the coupling constants of the these interactions to obtain almost equivalent fits to the scattering data and deuteron binding energy with a static interaction and the Blankenbecler-Sugar form of the reduced two-nucleon propagator and using both forms of the propagator with a covariant interaction. Dirac-Brueckner calculations using the static interactions furnish saturation properties similar to those found for the Bonn interactions. The covariant interactions, on the contrary, yield extreme overbinding and do not show signs of saturation before our calculations diverge. One of the advantages claimed for Dirac mean field calculations over nonrelativistic ones has been the fact that they yield reasonable saturation properties without the necessity of a three-body interaction. This is usually credited to the three-body effects introduced by virtual scattering through the Dirac sea states. These are included, in part, through the Dirac form of the self-energy in our calculations. However, we have explicitly excluded their contribution to the Brueckner scattering kernel. Dirac-Brueckner calculations in which both the positive and negative energy states are included in the scattering kernel result in less binding than those that include only the positive-energy ones
Flow-covariate prediction of stream pesticide concentrations.
Mosquin, Paul L; Aldworth, Jeremy; Chen, Wenlin
2018-01-01
Potential peak functions (e.g., maximum rolling averages over a given duration) of annual pesticide concentrations in the aquatic environment are important exposure parameters (or target quantities) for ecological risk assessments. These target quantities require accurate concentration estimates on nonsampled days in a monitoring program. We examined stream flow as a covariate via universal kriging to improve predictions of maximum m-day (m = 1, 7, 14, 30, 60) rolling averages and the 95th percentiles of atrazine concentration in streams where data were collected every 7 or 14 d. The universal kriging predictions were evaluated against the target quantities calculated directly from the daily (or near daily) measured atrazine concentration at 32 sites (89 site-yr) as part of the Atrazine Ecological Monitoring Program in the US corn belt region (2008-2013) and 4 sites (62 site-yr) in Ohio by the National Center for Water Quality Research (1993-2008). Because stream flow data are strongly skewed to the right, 3 transformations of the flow covariate were considered: log transformation, short-term flow anomaly, and normalized Box-Cox transformation. The normalized Box-Cox transformation resulted in predictions of the target quantities that were comparable to those obtained from log-linear interpolation (i.e., linear interpolation on the log scale) for 7-d sampling. However, the predictions appeared to be negatively affected by variability in regression coefficient estimates across different sample realizations of the concentration time series. Therefore, revised models incorporating seasonal covariates and partially or fully constrained regression parameters were investigated, and they were found to provide much improved predictions in comparison with those from log-linear interpolation for all rolling average measures. Environ Toxicol Chem 2018;37:260-273. © 2017 SETAC. © 2017 SETAC.
Conservative Sample Size Determination for Repeated Measures Analysis of Covariance.
Morgan, Timothy M; Case, L Douglas
2013-07-05
In the design of a randomized clinical trial with one pre and multiple post randomized assessments of the outcome variable, one needs to account for the repeated measures in determining the appropriate sample size. Unfortunately, one seldom has a good estimate of the variance of the outcome measure, let alone the correlations among the measurements over time. We show how sample sizes can be calculated by making conservative assumptions regarding the correlations for a variety of covariance structures. The most conservative choice for the correlation depends on the covariance structure and the number of repeated measures. In the absence of good estimates of the correlations, the sample size is often based on a two-sample t-test, making the 'ultra' conservative and unrealistic assumption that there are zero correlations between the baseline and follow-up measures while at the same time assuming there are perfect correlations between the follow-up measures. Compared to the case of taking a single measurement, substantial savings in sample size can be realized by accounting for the repeated measures, even with very conservative assumptions regarding the parameters of the assumed correlation matrix. Assuming compound symmetry, the sample size from the two-sample t-test calculation can be reduced at least 44%, 56%, and 61% for repeated measures analysis of covariance by taking 2, 3, and 4 follow-up measures, respectively. The results offer a rational basis for determining a fairly conservative, yet efficient, sample size for clinical trials with repeated measures and a baseline value.
Rigorous covariance propagation of geoid errors to geodetic MDT estimates
Pail, R.; Albertella, A.; Fecher, T.; Savcenko, R.
2012-04-01
The mean dynamic topography (MDT) is defined as the difference between the mean sea surface (MSS) derived from satellite altimetry, averaged over several years, and the static geoid. Assuming geostrophic conditions, from the MDT the ocean surface velocities as important component of global ocean circulation can be derived from it. Due to the availability of GOCE gravity field models, for the very first time MDT can now be derived solely from satellite observations (altimetry and gravity) down to spatial length-scales of 100 km and even below. Global gravity field models, parameterized in terms of spherical harmonic coefficients, are complemented by the full variance-covariance matrix (VCM). Therefore, for the geoid component a realistic statistical error estimate is available, while the error description of the altimetric component is still an open issue and is, if at all, attacked empirically. In this study we make the attempt to perform, based on the full gravity VCM, rigorous error propagation to derived geostrophic surface velocities, thus also considering all correlations. For the definition of the static geoid we use the third release of the time-wise GOCE model, as well as the satellite-only combination model GOCO03S. In detail, we will investigate the velocity errors resulting from the geoid component in dependence of the harmonic degree, and the impact of using/no using covariances on the MDT errors and its correlations. When deriving an MDT, it is spectrally filtered to a certain maximum degree, which is usually driven by the signal content of the geoid model, by applying isotropic or non-isotropic filters. Since this filtering is acting also on the geoid component, the consistent integration of this filter process into the covariance propagation shall be performed, and its impact shall be quantified. The study will be performed for MDT estimates in specific test areas of particular oceanographic interest.
Emergent gravity on covariant quantum spaces in the IKKT model
Energy Technology Data Exchange (ETDEWEB)
Steinacker, Harold C. [Faculty of Physics, University of Vienna,Boltzmanngasse 5, A-1090 Vienna (Austria)
2016-12-30
We study perturbations of 4-dimensional fuzzy spheres as backgrounds in the IKKT or IIB matrix model. Gauge fields and metric fluctuations are identified among the excitation modes with lowest spin, supplemented by a tower of higher-spin fields. They arise from an internal structure which can be viewed as a twisted bundle over S{sup 4}, leading to a covariant noncommutative geometry. The linearized 4-dimensional Einstein equations are obtained from the classical matrix model action under certain conditions, modified by an IR cutoff. Some one-loop contributions to the effective action are computed using the formalism of string states.
Covariances for measured activation and fission ratios data
International Nuclear Information System (INIS)
Smith, D.L.; Meadows, J.W.; Watanabe, Y.
1986-01-01
Methods which are routinely used in the determination of covariance matrices for both integral and differential activation and fission-ratios data acquired at the Argonne National Laboratory Fast-Neutron Generator Facility (FNG) are discussed. Special consideration is given to problems associated with the estimation of correlations between various identified sources of experimental error. Approximation methods which are commonly used to reduce the labor involved in this analysis to manageable levels are described. Results from some experiments which have been recently carried out in this laboratory are presented to illustrate these procedures. 13 refs., 1 fig., 5 tabs
Sparse inverse covariance estimation with the graphical lasso.
Friedman, Jerome; Hastie, Trevor; Tibshirani, Robert
2008-07-01
We consider the problem of estimating sparse graphs by a lasso penalty applied to the inverse covariance matrix. Using a coordinate descent procedure for the lasso, we develop a simple algorithm--the graphical lasso--that is remarkably fast: It solves a 1000-node problem ( approximately 500,000 parameters) in at most a minute and is 30-4000 times faster than competing methods. It also provides a conceptual link between the exact problem and the approximation suggested by Meinshausen and Bühlmann (2006). We illustrate the method on some cell-signaling data from proteomics.
Partially linear varying coefficient models stratified by a functional covariate
Maity, Arnab
2012-10-01
We consider the problem of estimation in semiparametric varying coefficient models where the covariate modifying the varying coefficients is functional and is modeled nonparametrically. We develop a kernel-based estimator of the nonparametric component and a profiling estimator of the parametric component of the model and derive their asymptotic properties. Specifically, we show the consistency of the nonparametric functional estimates and derive the asymptotic expansion of the estimates of the parametric component. We illustrate the performance of our methodology using a simulation study and a real data application.
The count variance-covariance matrix in a critical reactor
International Nuclear Information System (INIS)
Carloni, F.; Giovannini, R.
1984-01-01
The present paper deals with a critical reactor containing a set of neutron detectors operating one at time in different time intervals. The analysis makes use of the Kolmogorov backward formalism for the branching processes, in the framework of the one-velocity, point reactor model, explicitly taking into account the six groups of delayed neutrons. The expression of the mean value, the covariance of the counting distribution are reported. The list of the Fortran 4. subroutine CRITIC which computes these moments is also reported
The Kaplan-Meier Integral in the Presence of Covariates
DEFF Research Database (Denmark)
Gerds, Thomas A.; Beyersmann, Jan; Starkopf, Liis
2017-01-01
In a series of papers, Winfried Stute introduced and studied the Kaplan-Meier integral as an estimator of parameters of the joint distribution of survival times and covariates based on right censored survival times. We present a review of this work and show that his estimator has an inverse...... probability of censoring weighting (IPCW) representation. We further investigate large sample bias and efficiency. As a central application in a biostatistical context, Kaplan-Meier integrals are used to estimate transition probabilities in a non-Markov illness-death model. We extend already existing...
Hawking radiation, effective actions and covariant boundary conditions
International Nuclear Information System (INIS)
Banerjee, Rabin; Kulkarni, Shailesh
2008-01-01
From an appropriate expression for the effective action, the Hawking radiation from charged black holes is derived, using only covariant boundary conditions at the event horizon. The connection of our approach with the Unruh vacuum and the recent analysis [S.P. Robinson, F. Wilczek, Phys. Rev. Lett. 95 (2005) 011303, (gr-qc/0502074); S. Iso, H. Umetsu, F. Wilczek, Phys. Rev. Lett. 96 (2006) 151302, (hep-th/0602146); R. Banerjee, S. Kulkarni, (arXiv: 0707.2449 [hep-th])] of Hawking radiation using anomalies is established
Covariant solutions of the Bethe-Salpeter equation
International Nuclear Information System (INIS)
Williams, A.G.; Kusaka, K.; Simpson, K.M.
1997-01-01
There is a need for covariant solutions of bound state equations in order to construct realistic QCD based models of mesons and baryons. Furthermore, we ideally need to know the structure of these bound states in all kinematical regimes, which makes a direct solution in Minkowski space (without any 3-dimensional reductions) desirable. The Bethe-Salpeter equation (BSE) for bound states in scalar theories is reformulated and solved for arbitrary scattering kernels in terms of a generalized spectral representation directly in Minkowski space. This differs from the conventional Euclidean approach, where the BSE can only be solved in ladder approximation after a Wick rotation. (author)
Noncommutative vector bundles over fuzzy CPN and their covariant derivatives
International Nuclear Information System (INIS)
Dolan, Brian P.; Huet, Idrish; Murray, Sean; O'Connor, Denjoe
2007-01-01
We generalise the construction of fuzzy CP N in a manner that allows us to access all noncommutative equivariant complex vector bundles over this space. We give a simplified construction of polarization tensors on S 2 that generalizes to complex projective space, identify Laplacians and natural noncommutative covariant derivative operators that map between the modules that describe noncommuative sections. In the process we find a natural generalization of the Schwinger-Jordan construction to su(n) and identify composite oscillators that obey a Heisenberg algebra on an appropriate Fock space
Nucleon Mass from a Covariant Three-Quark Faddeev Equation
International Nuclear Information System (INIS)
Eichmann, G.; Alkofer, R.; Krassnigg, A.; Nicmorus, D.
2010-01-01
We report the first study of the nucleon where the full Poincare-covariant structure of the three-quark amplitude is implemented in the Faddeev equation. We employ an interaction kernel which is consistent with contemporary studies of meson properties and aspects of chiral symmetry and its dynamical breaking, thus yielding a comprehensive approach to hadron physics. The resulting current-mass evolution of the nucleon mass compares well with lattice data and deviates only by ∼5% from the quark-diquark result obtained in previous studies.
Selecting groups of covariates in the elastic net
DEFF Research Database (Denmark)
Clemmensen, Line Katrine Harder
This paper introduces a novel method to select groups of variables in sparse regression and classication settings. The groups are formed based on the correlations between covariates and ensure that for example spatial or spectral relations are preserved without explicitly coding for these....... The preservation of relations gives increased interpretability. The method is based on the elastic net and adaptively selects highly correlated groups of variables and does therefore not waste time in grouping irrelevant variables for the problem at hand. The method is illustrated on a simulated data set...
A measure of association between vectors based on "similarity covariance"
Pascual-Marqui, Roberto D.; Lehmann, Dietrich; Kochi, Kieko; Kinoshita, Toshihiko; Yamada, Naoto
2013-01-01
The "maximum similarity correlation" definition introduced in this study is motivated by the seminal work of Szekely et al on "distance covariance" (Ann. Statist. 2007, 35: 2769-2794; Ann. Appl. Stat. 2009, 3: 1236-1265). Instead of using Euclidean distances "d" as in Szekely et al, we use "similarity", which can be defined as "exp(-d/s)", where the scaling parameter s>0 controls how rapidly the similarity falls off with distance. Scale parameters are chosen by maximizing the similarity corre...
Current status of fusion-relevant covariance data
International Nuclear Information System (INIS)
Muir, D.W.
1994-01-01
The following review of the current status of formatted data covariance files and their multigroup processing is a contribution to the IAEA Advisory Group Meeting on ''Improved Evaluations and Integral Data Testing for FENDL,'' to be held at the Max-Planck-Institut fuer Plasmaphysik, Garching, Germany, 12--16 September 1994. The draft agenda of this meeting lists as Item 6 the ''assessment of present status and role of uncertainty files, their processing and sensitivity studies related to FENDL.'' We conclude that this is an important and timely topic and recommend needed actions in this field
Covariant generalized holographic dark energy and accelerating universe
Nojiri, Shin'ichi; Odintsov, S. D.
2017-08-01
We propose the generalized holographic dark energy model where the infrared cutoff is identified with the combination of the FRW universe parameters: the Hubble rate, particle and future horizons, cosmological constant, the universe lifetime (if finite) and their derivatives. It is demonstrated that with the corresponding choice of the cutoff one can map such holographic dark energy to modified gravity or gravity with a general fluid. Explicitly, F( R) gravity and the general perfect fluid are worked out in detail and the corresponding infrared cutoff is found. Using this correspondence, we get realistic inflation or viable dark energy or a unified inflationary-dark energy universe in terms of covariant holographic dark energy.
Mean-Lagrangian formalism and covariance of fluid turbulence.
Ariki, Taketo
2017-05-01
Mean-field-based Lagrangian framework is developed for the fluid turbulence theory, which enables physically objective discussions, especially, of the history effect. Mean flow serves as a purely geometrical object of Lie group theory, providing useful operations to measure the objective rate and history integration of the general tensor field. The proposed framework is applied, on the one hand, to one-point closure model, yielding an objective expression of the turbulence viscoelastic effect. Application to two-point closure, on the other hand, is also discussed, where natural extension of known Lagrangian correlation is discovered on the basis of an extended covariance group.
Lorentz-like covariant equations of non-relativistic fluids
International Nuclear Information System (INIS)
Montigny, M de; Khanna, F C; Santana, A E
2003-01-01
We use a geometrical formalism of Galilean invariance to build various hydrodynamics models. It consists in embedding the Newtonian spacetime into a non-Euclidean 4 + 1 space and provides thereby a procedure that unifies models otherwise apparently unrelated. After expressing the Navier-Stokes equation within this framework, we show that slight modifications of its Lagrangian allow us to recover the Chaplygin equation of state as well as models of superfluids for liquid helium (with both its irrotational and rotational components). Other fluid equations are also expressed in a covariant form
Oehlert, A. M.; Swart, P. K.
2013-12-01
Covariance between inorganic and organic δ13C records has been used to determine whether a deposit has been altered by diagenesis, how the dynamics of the global carbon cycle changed during the production of the sediments in the deposit, and also for chronostratigraphic correlations. Although covariant records are observed in the ancient geologic record in a variety of depositional environments, such comparisons are not widely applied to modern deposits where definitive data regarding sediment producers, sea level fluctuations, and changes in the global carbon cycle are available. This study uses paired δ13C records from cores collected by the Ocean Drilling Program from three modern periplatform settings (the Great Bahama Bank, the Great Australian Bight, and the Great Barrier Reef), and two pelagic settings (the Walvis Ridge, and the Madingley Rise). These sites were selected in order to assess the influence of several different environmental factors including; sediment and organic matter producers, sediment mineralogy, margin architecture, sea level oscillations, and sediment transport pathways. In the three periplatform settings, multiple cores arranged in a margin to basin transect were analyzed in order to provide insights into the effects of downslope sediment transport. The preliminary results of this study suggest that sea level oscillations and margin architecture may artificially generate a covarying relationship in periplatform sediments that is unrelated to changes in the global carbon cycle. Furthermore, preliminary results from the Walvis Ridge and the Madingley Rise sediments suggest that the relationship between inorganic and organic δ13C records may not always exhibit a positive covariance as is currently assumed for pelagic carbonates.
Garcia, Tanya P; Ma, Yanyuan
2017-10-01
We develop consistent and efficient estimation of parameters in general regression models with mismeasured covariates. We assume the model error and covariate distributions are unspecified, and the measurement error distribution is a general parametric distribution with unknown variance-covariance. We construct root- n consistent, asymptotically normal and locally efficient estimators using the semiparametric efficient score. We do not estimate any unknown distribution or model error heteroskedasticity. Instead, we form the estimator under possibly incorrect working distribution models for the model error, error-prone covariate, or both. Empirical results demonstrate robustness to different incorrect working models in homoscedastic and heteroskedastic models with error-prone covariates.
Directory of Open Access Journals (Sweden)
Jean Béguinot
2014-01-01
Full Text Available Specific parameters characterising shell shape may arguably have a significant role in the adaptation of bivalve molluscs to their particular environments. Yet, such functionally relevant shape parameters (shell outline elongation, dissymmetry, and ventral convexity are not those parameters that the animal may directly control. Rather than shell shape, the animal regulates shell growth. Accordingly, an alternative, growth-based description of shell-shape is best fitted to understand how the animal may control the achieved shell shape. The key point is, in practice, to bring out the link between those two alternative modes of shell-shape descriptions, that is, to derive the set of equations which connects the growth-based shell-shape parameters to the functionally relevant shell-shape parameters. Thus, a preliminary object of this note is to derive this set of equations as a tool for further investigations. A second object of this work is to provide an illustrative example of implementation of this tool. I report on an unexpected negative covariance between growth-based parameters and show how this covariance results in a severe limitation of the range of interspecific variability of the degree of ventral convexity of the shell outline within the superfamily Tellinoidea. Hypotheses are proposed regarding the constraints possibly at the origin of this limitation of interspecific variability.
Implementing phase-covariant cloning in circuit quantum electrodynamics
Energy Technology Data Exchange (ETDEWEB)
Zhu, Meng-Zheng [School of Physics and Material Science, Anhui University, Hefei 230039 (China); School of Physics and Electronic Information, Huaibei Normal University, Huaibei 235000 (China); Ye, Liu, E-mail: yeliu@ahu.edu.cn [School of Physics and Material Science, Anhui University, Hefei 230039 (China)
2016-10-15
An efficient scheme is proposed to implement phase-covariant quantum cloning by using a superconducting transmon qubit coupled to a microwave cavity resonator in the strong dispersive limit of circuit quantum electrodynamics (QED). By solving the master equation numerically, we plot the Wigner function and Poisson distribution of the cavity mode after each operation in the cloning transformation sequence according to two logic circuits proposed. The visualizations of the quasi-probability distribution in phase-space for the cavity mode and the occupation probability distribution in the Fock basis enable us to penetrate the evolution process of cavity mode during the phase-covariant cloning (PCC) transformation. With the help of numerical simulation method, we find out that the present cloning machine is not the isotropic model because its output fidelity depends on the polar angle and the azimuthal angle of the initial input state on the Bloch sphere. The fidelity for the actual output clone of the present scheme is slightly smaller than one in the theoretical case. The simulation results are consistent with the theoretical ones. This further corroborates our scheme based on circuit QED can implement efficiently PCC transformation.
One-loop matching and running with covariant derivative expansion
Henning, Brian; Lu, Xiaochuan; Murayama, Hitoshi
2018-01-01
We develop tools for performing effective field theory (EFT) calculations in a manifestly gauge-covariant fashion. We clarify how functional methods account for one-loop diagrams resulting from the exchange of both heavy and light fields, as some confusion has recently arisen in the literature. To efficiently evaluate functional traces containing these "mixed" one-loop terms, we develop a new covariant derivative expansion (CDE) technique that is capable of evaluating a much wider class of traces than previous methods. The technique is detailed in an appendix, so that it can be read independently from the rest of this work. We review the well-known matching procedure to one-loop order with functional methods. What we add to this story is showing how to isolate one-loop terms coming from diagrams involving only heavy propagators from diagrams with mixed heavy and light propagators. This is done using a non-local effective action, which physically connects to the notion of "integrating out" heavy fields. Lastly, we show how to use a CDE to do running analyses in EFTs, i.e. to obtain the anomalous dimension matrix. We demonstrate the methodologies by several explicit example calculations.
Renormalizable Non-Covariant Gauges and Coulomb Gauge Limit
Baulieu, L
1999-01-01
To study ``physical'' gauges such as the Coulomb, light-cone, axial or temporal gauge, we consider ``interpolating'' gauges which interpolate linearly between a covariant gauge, such as the Feynman or Landau gauge, and a physical gauge. Lorentz breaking by the gauge-fixing term of interpolating gauges is controlled by extending the BRST method to include not only the local gauge group, but also the global Lorentz group. We enumerate the possible divergences of interpolating gauges, and show that they are renormalizable, and we show that the expectation value of physical observables is the same as in a covariant gauge. In the second part of the article we study the Coulomb-gauge as the singular limit of the Landau-Coulomb interpolating gauge. We find that unrenormalized and renormalized correlation functions are finite in this limit. We also find that there are finite two-loop diagrams of ``unphysical'' particles that are not present in formal canonical quantization in the Coulomb gauge. We verify that in the ...
Covariant description of dynamical processes in relativistic nuclear matter
International Nuclear Information System (INIS)
Celenza, L.S.; Pantziris, A.; Shakin, C.M.
1992-01-01
We report results of covariant calculations of density-dependent polarization processes in relativistic nuclear matter. We consider the polarization induced by those mesons that play an important role in the boson-exchange model of nuclear forces (σ,π,ρ,ω). After obtaining the polarization operators, we construct the propagators for these mesons. The covariant nature of the calculation greatly clarifies the structure of the polarization operators and associated Green's functions. (In addition to the meson momentum, these quantities depend upon another four-vector, η μ , that describes the uniform motion of the medium.) In the case of the pion, we show that the same results are obtained for pseudovector or pseudoscalar coupling to the nucleon, if the associated Lagrangians are related by chiral transformations. Of particular interest are the extremely large values found for the polarization operators of the omega and sigma mesons. It is also found that the coupling of the sigma and omega fields through the polarization process is also extremely large. (Because of these results one cannot usefully consider the sigma and omega fields as independent degrees of freedom in nuclear matter.) We describe methods for reorganizing the calculation of ring diagrams in which we group those diagrams that exhibit strong cancellations. We also comment on the implication of our results for nuclear structure studies
The Covariance and Bicovariance of the Stochastic Neutron Field
International Nuclear Information System (INIS)
Perez, R.B.; Mattingly, J.K.; Valentine, T.E.; Mihalczo, J.T.
2000-01-01
On the basis of the general stochastic neutron field theory developed by Munoz-Cobo et al, results on the covariance and bicovariance of the neutron field have been presented. These two statistical quantities are obtained from the counts observed in detectors operating during a period of time (gate length), Δ qc . A classical example is the so called Feynmann Y-function that is defined as the variance to mean ratio of the neutron field. Upon taking the limit of the covariance and bicovariance function for Δ qc r a rrow O , one obtains the two and three detector cross correlation functions respectively. The mathematical structure of the results so obtained have a transparent physical interpretation in terms of the space and delay time overlap between the field-of-view of the detectors. For the first time, an expression has been obtained for the bispectrum function of the stochastic neutron field and for the appropriate weight functions to be used as space-energy-angle correction factors for the one-point kinetics approximation
Structural Equation Models in a Redundancy Analysis Framework With Covariates.
Lovaglio, Pietro Giorgio; Vittadini, Giorgio
2014-01-01
A recent method to specify and fit structural equation modeling in the Redundancy Analysis framework based on so-called Extended Redundancy Analysis (ERA) has been proposed in the literature. In this approach, the relationships between the observed exogenous variables and the observed endogenous variables are moderated by the presence of unobservable composites, estimated as linear combinations of exogenous variables. However, in the presence of direct effects linking exogenous and endogenous variables, or concomitant indicators, the composite scores are estimated by ignoring the presence of the specified direct effects. To fit structural equation models, we propose a new specification and estimation method, called Generalized Redundancy Analysis (GRA), allowing us to specify and fit a variety of relationships among composites, endogenous variables, and external covariates. The proposed methodology extends the ERA method, using a more suitable specification and estimation algorithm, by allowing for covariates that affect endogenous indicators indirectly through the composites and/or directly. To illustrate the advantages of GRA over ERA we propose a simulation study of small samples. Moreover, we propose an application aimed at estimating the impact of formal human capital on the initial earnings of graduates of an Italian university, utilizing a structural model consistent with well-established economic theory.
Inverse probability weighting for covariate adjustment in randomized studies.
Shen, Changyu; Li, Xiaochun; Li, Lingling
2014-02-20
Covariate adjustment in randomized clinical trials has the potential benefit of precision gain. It also has the potential pitfall of reduced objectivity as it opens the possibility of selecting a 'favorable' model that yields strong treatment benefit estimate. Although there is a large volume of statistical literature targeting on the first aspect, realistic solutions to enforce objective inference and improve precision are rare. As a typical randomized trial needs to accommodate many implementation issues beyond statistical considerations, maintaining the objectivity is at least as important as precision gain if not more, particularly from the perspective of the regulatory agencies. In this article, we propose a two-stage estimation procedure based on inverse probability weighting to achieve better precision without compromising objectivity. The procedure is designed in a way such that the covariate adjustment is performed before seeing the outcome, effectively reducing the possibility of selecting a 'favorable' model that yields a strong intervention effect. Both theoretical and numerical properties of the estimation procedure are presented. Application of the proposed method to a real data example is presented. Copyright © 2013 John Wiley & Sons, Ltd.
Ultracentrifuge separative power modeling with multivariate regression using covariance matrix
International Nuclear Information System (INIS)
Migliavacca, Elder
2004-01-01
In this work, the least-squares methodology with covariance matrix is applied to determine a data curve fitting to obtain a performance function for the separative power δU of a ultracentrifuge as a function of variables that are experimentally controlled. The experimental data refer to 460 experiments on the ultracentrifugation process for uranium isotope separation. The experimental uncertainties related with these independent variables are considered in the calculation of the experimental separative power values, determining an experimental data input covariance matrix. The process variables, which significantly influence the δU values are chosen in order to give information on the ultracentrifuge behaviour when submitted to several levels of feed flow rate F, cut θ and product line pressure P p . After the model goodness-of-fit validation, a residual analysis is carried out to verify the assumed basis concerning its randomness and independence and mainly the existence of residual heteroscedasticity with any explained regression model variable. The surface curves are made relating the separative power with the control variables F, θ and P p to compare the fitted model with the experimental data and finally to calculate their optimized values. (author)
Batalin-Vilkovisky formalism in locally covariant field theory
International Nuclear Information System (INIS)
Rejzner, Katarzyna Anna
2011-12-01
The present work contains a complete formulation of the Batalin-Vilkovisky (BV) formalism in the framework of locally covariant field theory. In the first part of the thesis the classical theory is investigated with a particular focus on the infinite dimensional character of the underlying structures. It is shown that the use of infinite dimensional differential geometry allows for a conceptually clear and elegant formulation. The construction of the BV complex is performed in a fully covariant way and we also generalize the BV framework to a more abstract level, using functors and natural transformations. In this setting we construct the BV complex for classical gravity. This allows us to give a homological interpretation to the notion of diffeomorphism invariant physical quantities in general relativity. The second part of the thesis concerns the quantum theory. We provide a framework for the BV quantization that doesn't rely on the path integral formalism, but is completely formulated within perturbative algebraic quantum field theory. To make such a formulation possible we first prove that the renormalized time-ordered product can be understood as a binary operation on a suitable domain. Using this result we prove the associativity of this product and provide a consistent framework for the renormalized BV structures. In particular the renormalized quantum master equation and the renormalized quantum BV operator are defined. To give a precise meaning to theses objects we make a use of the master Ward identity, which is an important structure in causal perturbation theory. (orig.)
SCALE-6 Sensitivity/Uncertainty Methods and Covariance Data
International Nuclear Information System (INIS)
Williams, Mark L.; Rearden, Bradley T.
2008-01-01
Computational methods and data used for sensitivity and uncertainty analysis within the SCALE nuclear analysis code system are presented. The methodology used to calculate sensitivity coefficients and similarity coefficients and to perform nuclear data adjustment is discussed. A description is provided of the SCALE-6 covariance library based on ENDF/B-VII and other nuclear data evaluations, supplemented by 'low-fidelity' approximate covariances. SCALE (Standardized Computer Analyses for Licensing Evaluation) is a modular code system developed by Oak Ridge National Laboratory (ORNL) to perform calculations for criticality safety, reactor physics, and radiation shielding applications. SCALE calculations typically use sequences that execute a predefined series of executable modules to compute particle fluxes and responses like the critical multiplication factor. SCALE also includes modules for sensitivity and uncertainty (S/U) analysis of calculated responses. The S/U codes in SCALE are collectively referred to as TSUNAMI (Tools for Sensitivity and UNcertainty Analysis Methodology Implementation). SCALE-6-scheduled for release in 2008-contains significant new capabilities, including important enhancements in S/U methods and data. The main functions of TSUNAMI are to (a) compute nuclear data sensitivity coefficients and response uncertainties, (b) establish similarity between benchmark experiments and design applications, and (c) reduce uncertainty in calculated responses by consolidating integral benchmark experiments. TSUNAMI includes easy-to-use graphical user interfaces for defining problem input and viewing three-dimensional (3D) geometries, as well as an integrated plotting package.
Maximum covariance analysis to identify intraseasonal oscillations over tropical Brazil
Barreto, Naurinete J. C.; Mesquita, Michel d. S.; Mendes, David; Spyrides, Maria H. C.; Pedra, George U.; Lucio, Paulo S.
2017-09-01
A reliable prognosis of extreme precipitation events in the tropics is arguably challenging to obtain due to the interaction of meteorological systems at various time scales. A pivotal component of the global climate variability is the so-called intraseasonal oscillations, phenomena that occur between 20 and 100 days. The Madden-Julian Oscillation (MJO), which is directly related to the modulation of convective precipitation in the equatorial belt, is considered the primary oscillation in the tropical region. The aim of this study is to diagnose the connection between the MJO signal and the regional intraseasonal rainfall variability over tropical Brazil. This is achieved through the development of an index called Multivariate Intraseasonal Index for Tropical Brazil (MITB). This index is based on Maximum Covariance Analysis (MCA) applied to the filtered daily anomalies of rainfall data over tropical Brazil against a group of covariates consisting of: outgoing longwave radiation and the zonal component u of the wind at 850 and 200 hPa. The first two MCA modes, which were used to create the { MITB}_1 and { MITB}_2 indices, represent 65 and 16 % of the explained variance, respectively. The combined multivariate index was able to satisfactorily represent the pattern of intraseasonal variability over tropical Brazil, showing that there are periods of activation and inhibition of precipitation connected with the pattern of MJO propagation. The MITB index could potentially be used as a diagnostic tool for intraseasonal forecasting.
Repairable system analysis in presence of covariates and random effects
International Nuclear Information System (INIS)
Giorgio, M.; Guida, M.; Pulcini, G.
2014-01-01
This paper aims to model the failure pattern of repairable systems in presence of explained and unexplained heterogeneity. The failure pattern of each system is described by a Power Law Process. Part of the heterogeneity among the patterns is explained through the use of a covariate, and the residual unexplained heterogeneity (random effects) is modeled via a joint probability distribution on the PLP parameters. The proposed approach is applied to a real set of failure time data of powertrain systems mounted on 33 buses employed in urban and suburban routes. Moreover, the joint probability distribution on the PLP parameters estimated from the data is used as an informative prior to make Bayesian inference on the future failure process of a generic system belonging to the same population and employed in an urban or suburban route under randomly chosen working conditions. - Highlights: • We describe the failure process of buses powertrain system subject to heterogeneity. • Heterogeneity due to different service types is explained by a covariate. • Random effect is modeled through a joint pdf on failure process parameters. • The powertrain reliability under new future operating conditions is estimated
Batalin-Vilkovisky formalism in locally covariant field theory
Energy Technology Data Exchange (ETDEWEB)
Rejzner, Katarzyna Anna
2011-12-15
The present work contains a complete formulation of the Batalin-Vilkovisky (BV) formalism in the framework of locally covariant field theory. In the first part of the thesis the classical theory is investigated with a particular focus on the infinite dimensional character of the underlying structures. It is shown that the use of infinite dimensional differential geometry allows for a conceptually clear and elegant formulation. The construction of the BV complex is performed in a fully covariant way and we also generalize the BV framework to a more abstract level, using functors and natural transformations. In this setting we construct the BV complex for classical gravity. This allows us to give a homological interpretation to the notion of diffeomorphism invariant physical quantities in general relativity. The second part of the thesis concerns the quantum theory. We provide a framework for the BV quantization that doesn't rely on the path integral formalism, but is completely formulated within perturbative algebraic quantum field theory. To make such a formulation possible we first prove that the renormalized time-ordered product can be understood as a binary operation on a suitable domain. Using this result we prove the associativity of this product and provide a consistent framework for the renormalized BV structures. In particular the renormalized quantum master equation and the renormalized quantum BV operator are defined. To give a precise meaning to theses objects we make a use of the master Ward identity, which is an important structure in causal perturbation theory. (orig.)
Some observations on interpolating gauges and non-covariant gauges
International Nuclear Information System (INIS)
Joglekar, Satish D.
2003-01-01
We discuss the viability of using interpolating gauges to define the non-covariant gauges starting from the covariant ones. We draw attention to the need for a very careful treatment of boundary condition defining term. We show that the boundary condition needed to maintain gauge invariance as the interpolating parameter θ varies, depends very sensitively on the parameter variation. We do this with a gauge used by Doust. We also consider the Lagrangian path-integrals in Minkowski space for gauges with a residual gauge-invariance. We point out the necessity of inclusion of an ε-term (even) in the formal treatments, without which one may reach incorrect conclusions. We, further, point out that the ε-term can contribute to the BRST WT-identities in a non-trivial way (even as ε → 0). We point out that these contributions lead to additional constraints on Green's function that are not normally taken into account in the BRST formalism that ignores the ε-term, and that they are characteristic of the way the singularities in propagators are handled. We argue that a prescription, in general, will require renormalization; if at all it is to be viable. (author)
Structural covariance networks across healthy young adults and their consistency.
Guo, Xiaojuan; Wang, Yan; Guo, Taomei; Chen, Kewei; Zhang, Jiacai; Li, Ke; Jin, Zhen; Yao, Li
2015-08-01
To investigate structural covariance networks (SCNs) as measured by regional gray matter volumes with structural magnetic resonance imaging (MRI) from healthy young adults, and to examine their consistency and stability. Two independent cohorts were included in this study: Group 1 (82 healthy subjects aged 18-28 years) and Group 2 (109 healthy subjects aged 20-28 years). Structural MRI data were acquired at 3.0T and 1.5T using a magnetization prepared rapid-acquisition gradient echo sequence for these two groups, respectively. We applied independent component analysis (ICA) to construct SCNs and further applied the spatial overlap ratio and correlation coefficient to evaluate the spatial consistency of the SCNs between these two datasets. Seven and six independent components were identified for Group 1 and Group 2, respectively. Moreover, six SCNs including the posterior default mode network, the visual and auditory networks consistently existed across the two datasets. The overlap ratios and correlation coefficients of the visual network reached the maximums of 72% and 0.71. This study demonstrates the existence of consistent SCNs corresponding to general functional networks. These structural covariance findings may provide insight into the underlying organizational principles of brain anatomy. © 2014 Wiley Periodicals, Inc.
A Covariance Generation Methodology for Fission Product Yields
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Terranova N.
2016-01-01
Full Text Available Recent safety and economical concerns for modern nuclear reactor applications have fed an outstanding interest in basic nuclear data evaluation improvement and completion. It has been immediately clear that the accuracy of our predictive simulation models was strongly affected by our knowledge on input data. Therefore strong efforts have been made to improve nuclear data and to generate complete and reliable uncertainty information able to yield proper uncertainty propagation on integral reactor parameters. Since in modern nuclear data banks (such as JEFF-3.1.1 and ENDF/BVII.1 no correlations for fission yields are given, in the present work we propose a covariance generation methodology for fission product yields. The main goal is to reproduce the existing European library and to add covariance information to allow proper uncertainty propagation in depletion and decay heat calculations. To do so, we adopted the Generalized Least Square Method (GLSM implemented in CONRAD (COde for Nuclear Reaction Analysis and Data assimilation, developed at CEA-Cadarache. Theoretical values employed in the Bayesian parameter adjustment are delivered thanks to a convolution of different models, representing several quantities in fission yield calculations: the Brosa fission modes for pre-neutron mass distribution, a simplified Gaussian model for prompt neutron emission probability, theWahl systematics for charge distribution and the Madland-England model for the isomeric ratio. Some results will be presented for the thermal fission of U-235, Pu-239 and Pu-241.
Abnormalities in Structural Covariance of Cortical Gyrification in Parkinson's Disease.
Xu, Jinping; Zhang, Jiuquan; Zhang, Jinlei; Wang, Yue; Zhang, Yanling; Wang, Jian; Li, Guanglin; Hu, Qingmao; Zhang, Yuanchao
2017-01-01
Although abnormal cortical morphology and connectivity between brain regions (structural covariance) have been reported in Parkinson's disease (PD), the topological organizations of large-scale structural brain networks are still poorly understood. In this study, we investigated large-scale structural brain networks in a sample of 37 PD patients and 34 healthy controls (HC) by assessing the structural covariance of cortical gyrification with local gyrification index (lGI). We demonstrated prominent small-world properties of the structural brain networks for both groups. Compared with the HC group, PD patients showed significantly increased integrated characteristic path length and integrated clustering coefficient, as well as decreased integrated global efficiency in structural brain networks. Distinct distributions of hub regions were identified between the two groups, showing more hub regions in the frontal cortex in PD patients. Moreover, the modular analyses revealed significantly decreased integrated regional efficiency in lateral Fronto-Insula-Temporal module, and increased integrated regional efficiency in Parieto-Temporal module in the PD group as compared to the HC group. In summary, our study demonstrated altered topological properties of structural networks at a global, regional and modular level in PD patients. These findings suggests that the structural networks of PD patients have a suboptimal topological organization, resulting in less effective integration of information between brain regions.
International Nuclear Information System (INIS)
Bachoc, Francois
2014-01-01
Covariance parameter estimation of Gaussian processes is analyzed in an asymptotic framework. The spatial sampling is a randomly perturbed regular grid and its deviation from the perfect regular grid is controlled by a single scalar regularity parameter. Consistency and asymptotic normality are proved for the Maximum Likelihood and Cross Validation estimators of the covariance parameters. The asymptotic covariance matrices of the covariance parameter estimators are deterministic functions of the regularity parameter. By means of an exhaustive study of the asymptotic covariance matrices, it is shown that the estimation is improved when the regular grid is strongly perturbed. Hence, an asymptotic confirmation is given to the commonly admitted fact that using groups of observation points with small spacing is beneficial to covariance function estimation. Finally, the prediction error, using a consistent estimator of the covariance parameters, is analyzed in detail. (authors)
Effect of correlation on covariate selection in linear and nonlinear mixed effect models.
Bonate, Peter L
2017-01-01
The effect of correlation among covariates on covariate selection was examined with linear and nonlinear mixed effect models. Demographic covariates were extracted from the National Health and Nutrition Examination Survey III database. Concentration-time profiles were Monte Carlo simulated where only one covariate affected apparent oral clearance (CL/F). A series of univariate covariate population pharmacokinetic models was fit to the data and compared with the reduced model without covariate. The "best" covariate was identified using either the likelihood ratio test statistic or AIC. Weight and body surface area (calculated using Gehan and George equation, 1970) were highly correlated (r = 0.98). Body surface area was often selected as a better covariate than weight, sometimes as high as 1 in 5 times, when weight was the covariate used in the data generating mechanism. In a second simulation, parent drug concentration and three metabolites were simulated from a thorough QT study and used as covariates in a series of univariate linear mixed effects models of ddQTc interval prolongation. The covariate with the largest significant LRT statistic was deemed the "best" predictor. When the metabolite was formation-rate limited and only parent concentrations affected ddQTc intervals the metabolite was chosen as a better predictor as often as 1 in 5 times depending on the slope of the relationship between parent concentrations and ddQTc intervals. A correlated covariate can be chosen as being a better predictor than another covariate in a linear or nonlinear population analysis by sheer correlation These results explain why for the same drug different covariates may be identified in different analyses. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Covariant Density Functionals: time-odd channel investigated
International Nuclear Information System (INIS)
Afanasjev, A. V.; Abusara, H.
2009-01-01
The description of exotic nuclear systems and phenomena requires a detailed understanding of all channels of density functional theories. The role of time-odd mean fields, their evidence in experiment, and an accurate description of these fields are subject of current interest. Recent studies advanced the understanding of these fields in energy density functional theories based on the Skyrme force [1,2]. Time-odd mean fields are related to nuclear magnetism in covariant density functional (CDF) theories [3]. They arise from space-like components of vector mesons and Lorentz invariance requires that their coupling strengths are identical to that of time-like components. There were only few limited efforts to understand the role of time-odd mean fields in covariant density functional theory [4,5]. For example, the microscopic role of nuclear magnetism and its impact on rotational properties of nuclei has been studied in Ref. [5]. It is known that time-odd mean fields modify the angular momentum content of the single-particle orbitals and thus the moments of inertia, effective alignments, alignment gains at the band crossings and other physical observables. We aim on more detailed and systematic understanding of the role of time-odd mean fields in covariant density functional theory. This investigation covers both rotating and non-rotating systems. It is shown that contrary to the Skyrme energy density functionals time-odd mean fields of CDF theory always provide additional binding in the systems with broken time-reversal symmetry (rotating nuclei, odd mass nuclei). This additional binding increases with spin and has its maximum exactly at the terminating state [6], where it can reach several MeV. The impact of time-odd mean fields on the properties of rotating systems has been studied in a systematic way (as a function of particle number and deformation) across the nuclear chart [7]. In addition, this contribution extends these studies to non-rotating systems such as
Managing distance and covariate information with point-based clustering
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Peter A. Whigham
2016-09-01
Full Text Available Abstract Background Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures. An approach, based on Ripley’s K and applied to the problem of clustering with deliberate self-harm (DSH, is presented. Methods Point-based Monte-Carlo simulation of Ripley’s K, accounting for socio-economic deprivation and sources of distance measurement bias, was developed to estimate clustering of DSH at a range of spatial scales. A rotated Minkowski L1 distance metric allowed variation in physical distance and clustering to be assessed. Self-harm data was derived from an audit of 2 years’ emergency hospital presentations (n = 136 in a New Zealand town (population ~50,000. Study area was defined by residential (housing land parcels representing a finite set of possible point addresses. Results Area-based deprivation was spatially correlated. Accounting for deprivation and distance bias showed evidence for clustering of DSH for spatial scales up to 500 m with a one-sided 95 % CI, suggesting that social contagion may be present for this urban cohort. Conclusions Many problems involve finite locations in geographic space that require estimates of distance-based clustering at many scales. A Monte-Carlo approach to Ripley’s K, incorporating covariates and models for distance bias, are crucial when assessing health-related clustering. The case study showed that social network structure defined at the neighbourhood level may account for aspects of neighbourhood clustering of DSH. Accounting for
Sparse Covariance Matrix Estimation by DCA-Based Algorithms.
Phan, Duy Nhat; Le Thi, Hoai An; Dinh, Tao Pham
2017-11-01
This letter proposes a novel approach using the [Formula: see text]-norm regularization for the sparse covariance matrix estimation (SCME) problem. The objective function of SCME problem is composed of a nonconvex part and the [Formula: see text] term, which is discontinuous and difficult to tackle. Appropriate DC (difference of convex functions) approximations of [Formula: see text]-norm are used that result in approximation SCME problems that are still nonconvex. DC programming and DCA (DC algorithm), powerful tools in nonconvex programming framework, are investigated. Two DC formulations are proposed and corresponding DCA schemes developed. Two applications of the SCME problem that are considered are classification via sparse quadratic discriminant analysis and portfolio optimization. A careful empirical experiment is performed through simulated and real data sets to study the performance of the proposed algorithms. Numerical results showed their efficiency and their superiority compared with seven state-of-the-art methods.
An introduction to covariant quantum gravity and asymptotic safety
Percacci, Roberto
2017-01-01
This book covers recent developments in the covariant formulation of quantum gravity. Developed in the 1960s by Feynman and DeWitt, by the 1980s this approach seemed to lead nowhere due to perturbative non-renormalizability. The possibility of non-perturbative renormalizability or "asymptotic safety," originally suggested by Weinberg but largely ignored for two decades, was revived towards the end of the century by technical progress in the field of the renormalization group. It is now a very active field of research, providing an alternative to other approaches to quantum gravity. Written by one of the early contributors to this subject, this book provides a gentle introduction to the relevant ideas and calculational techniques. Several explicit calculations gradually bring the reader close to the current frontier of research. The main difficulties and present lines of development are also outlined.
Covariant generalized holographic dark energy and accelerating universe
Energy Technology Data Exchange (ETDEWEB)
Nojiri, Shin' ichi [Nagoya University, Department of Physics, Nagoya (Japan); Nagoya University, Kobayashi-Maskawa Institute for the Origin of Particles and the Universe, Nagoya (Japan); Odintsov, S.D. [ICREA, Barcelona (Spain); Institute of Space Sciences (IEEC-CSIC), Barcelona (Spain); National Research Tomsk State University, Tomsk (Russian Federation); Tomsk State Pedagogical University, Tomsk (Russian Federation)
2017-08-15
We propose the generalized holographic dark energy model where the infrared cutoff is identified with the combination of the FRW universe parameters: the Hubble rate, particle and future horizons, cosmological constant, the universe lifetime (if finite) and their derivatives. It is demonstrated that with the corresponding choice of the cutoff one can map such holographic dark energy to modified gravity or gravity with a general fluid. Explicitly, F(R) gravity and the general perfect fluid are worked out in detail and the corresponding infrared cutoff is found. Using this correspondence, we get realistic inflation or viable dark energy or a unified inflationary-dark energy universe in terms of covariant holographic dark energy. (orig.)
A FORMALISM FOR COVARIANT POLARIZED RADIATIVE TRANSPORT BY RAY TRACING
International Nuclear Information System (INIS)
Gammie, Charles F.; Leung, Po Kin
2012-01-01
We write down a covariant formalism for polarized radiative transfer appropriate for ray tracing through a turbulent plasma. The polarized radiation field is represented by the polarization tensor (coherency matrix) N αβ ≡ (a α k a* β k ), where a k is a Fourier coefficient for the vector potential. Using Maxwell's equations, the Liouville-Vlasov equation, and the WKB approximation, we show that the transport equation in vacuo is k μ ∇ μ N αβ = 0. We show that this is equivalent to Broderick and Blandford's formalism based on invariant Stokes parameters and a rotation coefficient, and suggest a modification that may reduce truncation error in some situations. Finally, we write down several alternative approaches to integrating the transfer equation.
Covariant differential calculus on the quantum exterior vector space
International Nuclear Information System (INIS)
Parashar, P.; Soni, S.K.
1992-01-01
We formulate a differential calculus on the quantum exterior vector space spanned by the generators of a non-anticommutative algebra satisfying r ij = θ i θ j +B kl ij θ k θ l =0 i, j=1, 2, ..., n. and (θ i ) 2 =(θ j ) 2 =...=(θ n ) 2 =0, where B kl ij is the most general matrix defined in terms of complex deformation parameters. Following considerations analogous to those of Wess and Zumino, we are able to exhibit covariance of our calculus under ( 2 n )+1 parameter deformation of GL(n) and explicitly check that the non-anticommutative differential calculus satisfies the general constraints given by them, such as the 'linear' conditions dr ij ≅0 and the 'quadratic' condition r ij x n ≅0 where x n =dθ n are the differentials of the variables. (orig.)
A chiral covariant approach to ρρ scattering
Energy Technology Data Exchange (ETDEWEB)
Guelmez, D. [Universitaet Bonn, Helmholtz-Institut fuer Strahlen- und Kernphysik and Bethe Center for Theoretical Physics, Bonn (Germany); Meissner, U.G. [Universitaet Bonn, Helmholtz-Institut fuer Strahlen- und Kernphysik and Bethe Center for Theoretical Physics, Bonn (Germany); Institut fuer Kernphysik and Juelich Center for Hadron Physics, Institute for Advanced Simulation, Juelich (Germany); Oller, J.A. [Universidad de Murcia, Departamento de Fisica, Murcia (Spain)
2017-07-15
We analyze vector meson-vector meson scattering in a unitarized chiral theory based on a chiral covariant framework restricted to ρρ intermediate states. We show that a pole assigned to the scalar meson f{sub 0}(1370) can be dynamically generated from the ρρ interaction, while this is not the case for the tensor meson f{sub 2}(1270) as found in earlier work. We show that the generation of the tensor state is untenable due to the extreme non-relativistic kinematics used before. We further consider the effects arising from the coupling of channels with different orbital angular momenta which are also important. We suggest to use the formalism outlined here to obtain more reliable results for the dynamical generation of resonances in the vector-vector interaction. (orig.)
Structure of Pioncare covariant tensor operators in quantum mechanical models
International Nuclear Information System (INIS)
Polyzou, W.N.; Klink, W.H.
1988-01-01
The structure of operators that transform covariantly in Poincare invariant quantum mechanical models is analyzed. These operators are shown to have an interaction dependence that comes from the geometry of the Poincare group. The operators can be expressed in terms of matrix elements in a complete set of eigenstates of the mass and spin operators associated with the dynamical representation of the Poincare group. The matrix elements are factored into geometrical coefficients (Clebsch--Gordan coefficients for the Poincare group) and invariant matrix elements. The geometrical coefficients are fixed by the transformation properties of the operator and the eigenvalue spectrum of the mass and spin. The invariant matrix elements, which distinguish between different operators with the same transformation properties, are given in terms of a set of invariant form factors. copyright 1988 Academic Press, Inc
Two- and three-loop amplitudes in covariant loop calculus
International Nuclear Information System (INIS)
Roland, K.
1988-04-01
We study 2- and 3-loop vacuum-amplitudes for the closed bosonic string. We compare two sets of expressions for the corresponding density on moduli space: One, based on the covariant Reggeon loop calculus (where modular invariance is not manifest). The other, based on analytic geometry. We want to prove identity between the two sets of expressions. Quite apart from demonstrating modular invariance of the Reggeon results, this would in itself be a remarkable mathematical feature. Identity is established to 'high' order in some moduli and exactly in others. The expansions reveal an essentially number-theoretical structure. Agreement is found only by exploiting the connection between the 4 Jacobi θ-functions and number theory. (orig.)
Covariant currents in N=2 super-Liouville theory
International Nuclear Information System (INIS)
Gomis, J.; Suzuki, Hiroshi
1993-01-01
Based on a path-integral prescription for anomaly calculation, we analyze an effective theory of the two-dimensional N=2 supergravity, i.e. N=2 super-Liouville theory. We calculate the anomalies associated with the BRST supercurrent and the ghost-number supercurrent. From those expressions of anomalies, we construct covariant BRST and ghost-number supercurrents in the effective theory. We then show that the (super-)coordinate BRST current algebra forms a superfield extension of the topological conformal algebra for an arbitrary type of conformal matter or, in terms of the string theory, for an arbitrary number of space-time dimensions. This fact is in great contrast with N=0 and N=1 (super-)Liouville theory, where the topological algebra singles out a particular value of dimensions. Our observation suggests a topological nature of the two-dimensional N=2 supergravity as a quantum theory. (orig.)
A New Heteroskedastic Consistent Covariance Matrix Estimator using Deviance Measure
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Nuzhat Aftab
2016-06-01
Full Text Available In this article we propose a new heteroskedastic consistent covariance matrix estimator, HC6, based on deviance measure. We have studied and compared the finite sample behavior of the new test and compared it with other this kind of estimators, HC1, HC3 and HC4m, which are used in case of leverage observations. Simulation study is conducted to study the effect of various levels of heteroskedasticity on the size and power of quasi-t test with HC estimators. Results show that the test statistic based on our new suggested estimator has better asymptotic approximation and less size distortion as compared to other estimators for small sample sizes when high level ofheteroskedasticity is present in data.
Two- and three-loop amplitudes in covariant loop calculus
International Nuclear Information System (INIS)
Roland, K.
1989-01-01
We study two- and three-loop vacuum amplitudes for the closed bosonic string. We compare two sets of expressions for the corresponding density on moduli space. One is based on the covariant reggeon loop calculus (where modular invariance is not manifest). The other is based on analytic geometry. We want to prove identity between the two sets of expressions. Quite apart from demonstrating modular invariance of the reggeon results, this would in itself be a remarkable mathematical feature. Identity is established to ''high'' order in some moduli and exactly in others. The expansions reveal an essentially number-theoretic structure. Agreement is found only by exploiting the connection between the four Jacobi θ-functions and number theory. (orig.)
Covariant generalized holographic dark energy and accelerating universe
International Nuclear Information System (INIS)
Nojiri, Shin'ichi; Odintsov, S.D.
2017-01-01
We propose the generalized holographic dark energy model where the infrared cutoff is identified with the combination of the FRW universe parameters: the Hubble rate, particle and future horizons, cosmological constant, the universe lifetime (if finite) and their derivatives. It is demonstrated that with the corresponding choice of the cutoff one can map such holographic dark energy to modified gravity or gravity with a general fluid. Explicitly, F(R) gravity and the general perfect fluid are worked out in detail and the corresponding infrared cutoff is found. Using this correspondence, we get realistic inflation or viable dark energy or a unified inflationary-dark energy universe in terms of covariant holographic dark energy. (orig.)
The breaking of Bjorken scaling in the covariant parton model
International Nuclear Information System (INIS)
Polkinghorne, J.C.
1976-01-01
Scale breaking is investigated in terms of a covariant parton model formulation of deep inelastic processes. It is shown that a consistent theory requires that the convergence properties of parton-hadron amplitudes should be modified as well as the parton being given form factors. Purely logarithmic violation is possible and the resulting model has many features in common with asymtotically free gauge theories. Behaviour at large and small ω and fixed q 2 is investigated. γW 2 should increase with q 2 at large ω and decrease with q 2 at small ω. Heuristic arguments are also given which suggest that the model would only lead to logarithmic modifications of dimensional counting results in purely hadronic deep scattering. (Auth.)
Covariant density functional theory: The role of the pion
International Nuclear Information System (INIS)
Lalazissis, G. A.; Karatzikos, S.; Serra, M.; Otsuka, T.; Ring, P.
2009-01-01
We investigate the role of the pion in covariant density functional theory. Starting from conventional relativistic mean field (RMF) theory with a nonlinear coupling of the σ meson and without exchange terms we add pions with a pseudovector coupling to the nucleons in relativistic Hartree-Fock approximation. In order to take into account the change of the pion field in the nuclear medium the effective coupling constant of the pion is treated as a free parameter. It is found that the inclusion of the pion to this sort of density functionals does not destroy the overall description of the bulk properties by RMF. On the other hand, the noncentral contribution of the pion (tensor coupling) does have effects on single particle energies and on binding energies of certain nuclei.
Developing the covariant Batalin-Vilkovisky approach to string theory
International Nuclear Information System (INIS)
Hata, H.; Zwiebach, B.
1994-01-01
In this work the authors investigate the variation of the string field action under changes of the string field vertices giving rise to different decompositions of the moduli spaces of Riemann surfaces. The authors establish that any such change in the string action arises from a field transformation canonical with respect to the Batalin-Vilkovisky (BV) antibracket and find the explicit form of the generator of the infinitesimal transformations. Two theories using different decompositions of moduli space are shown to yield the same gauge-fixed action upon use of different gauge-fixing conditions. The authors also elaborate on recent work on the covariant BV formalism, and emphasize the necessity of a measure in the space of two-dimensional field theories in order to extend a recent analysis of background independence to quantum string field theory. 22 refs., 2 figs
Variational formulation of covariant eikonal theory for vector waves
International Nuclear Information System (INIS)
Kaufman, A.N.; Ye, H.; Hui, Y.
1986-10-01
The eikonal theory of wave propagation is developed by means of a Lorentz-covariant variational principle, involving functions defined on the natural eight-dimensional phase space of rays. The wave field is a four-vector representing the electromagnetic potential, while the medium is represented by an anisotropic, dispersive nonuniform dielectric tensor D/sup μν/(k,x). The eikonal expansion yields, to lowest order, the Hamiltonian ray equations, which define the Lagrangian manifold k(x), and the wave-action conservation law, which determines the wave-amplitude transport along the rays. The first-order contribution to the variational principle yields a concise expression for the transport of the polarization phase. The symmetry between k-space and x-space allows for a simple implementation of the Maslov transform, which avoids the difficulties of caustic singularities
Robust adaptive multichannel SAR processing based on covariance matrix reconstruction
Tan, Zhen-ya; He, Feng
2018-04-01
With the combination of digital beamforming (DBF) processing, multichannel synthetic aperture radar(SAR) systems in azimuth promise well in high-resolution and wide-swath imaging, whereas conventional processing methods don't take the nonuniformity of scattering coefficient into consideration. This paper brings up a robust adaptive Multichannel SAR processing method which utilizes the Capon spatial spectrum estimator to obtain the spatial spectrum distribution over all ambiguous directions first, and then the interference-plus-noise covariance Matrix is reconstructed based on definition to acquire the Multichannel SAR processing filter. The performance of processing under nonuniform scattering coefficient is promoted by this novel method and it is robust again array errors. The experiments with real measured data demonstrate the effectiveness and robustness of the proposed method.
Asymptotics of empirical eigenstructure for high dimensional spiked covariance.
Wang, Weichen; Fan, Jianqing
2017-06-01
We derive the asymptotic distributions of the spiked eigenvalues and eigenvectors under a generalized and unified asymptotic regime, which takes into account the magnitude of spiked eigenvalues, sample size, and dimensionality. This regime allows high dimensionality and diverging eigenvalues and provides new insights into the roles that the leading eigenvalues, sample size, and dimensionality play in principal component analysis. Our results are a natural extension of those in Paul (2007) to a more general setting and solve the rates of convergence problems in Shen et al. (2013). They also reveal the biases of estimating leading eigenvalues and eigenvectors by using principal component analysis, and lead to a new covariance estimator for the approximate factor model, called shrinkage principal orthogonal complement thresholding (S-POET), that corrects the biases. Our results are successfully applied to outstanding problems in estimation of risks of large portfolios and false discovery proportions for dependent test statistics and are illustrated by simulation studies.
A New Bias Corrected Version of Heteroscedasticity Consistent Covariance Estimator
Directory of Open Access Journals (Sweden)
Munir Ahmed
2016-06-01
Full Text Available In the presence of heteroscedasticity, different available flavours of the heteroscedasticity consistent covariance estimator (HCCME are used. However, the available literature shows that these estimators can be considerably biased in small samples. Cribari–Neto et al. (2000 introduce a bias adjustment mechanism and give the modified White estimator that becomes almost bias-free even in small samples. Extending these results, Cribari-Neto and Galvão (2003 present a similar bias adjustment mechanism that can be applied to a wide class of HCCMEs’. In the present article, we follow the same mechanism as proposed by Cribari-Neto and Galvão to give bias-correction version of HCCME but we use adaptive HCCME rather than the conventional HCCME. The Monte Carlo study is used to evaluate the performance of our proposed estimators.
Covariant approach of perturbations in Lovelock type brane gravity
Bagatella-Flores, Norma; Campuzano, Cuauhtemoc; Cruz, Miguel; Rojas, Efraín
2016-12-01
We develop a covariant scheme to describe the dynamics of small perturbations on Lovelock type extended objects propagating in a flat Minkowski spacetime. The higher-dimensional analogue of the Jacobi equation in this theory becomes a wave type equation for a scalar field Φ . Whithin this framework, we analyse the stability of membranes with a de Sitter geometry where we find that the Jacobi equation specializes to a Klein-Gordon (KG) equation for Φ possessing a tachyonic mass. This shows that, to some extent, these types of extended objects share the symmetries of the Dirac-Nambu-Goto (DNG) action which is by no means coincidental because the DNG model is the simplest included in this type of gravity.
Maxwell-Chern-Simons theory in covariant and Coulomb gauges
International Nuclear Information System (INIS)
Haller, K.; Lim-Lombridas, E.
1996-01-01
We quantize quantum electrodynamics in 2 + 1 dimensions coupled to a Chern-Simons (CS) term and a charged spinor field, in covariant gauges and in the Coulomb gauge. The resulting Maxwell-Chern-Simons (MCS) theory describes charged fermions interacting with each other and with topologically massive propagating photons. We impose Gauss's law and the gauge conditions and investigate their effect on the dynamics and on the statistics of n-particle states. We construct charged spinor states that obey Gauss's law and the gauge conditions and transform the theory to representations in which these states constitute a Fock space. We demonstrate that, in these representations, the nonlocal interactions between charges and between charges and transverse currents-along with the interactions between currents and massive propagating photons-are identical in the different gauges we analyze in this and in earlier work. We construct the generators of the Poincare group, show that they implement the Poincare algebra, and explicitly demonstrate the effect of rotations and Lorentz boosts on the particle states. We show that the imposition of Gauss's law does not produce any open-quotes exoticclose quotes fractional statistics. In the case of the covariant gauges, this demonstration makes use of unitary transformations that provide charged particles with the gauge fields required by Gauss's law, but that leave the anticommutator algebra of the spinor fields untransformed. In the Coulomb gauge, we show that the anticommutators of the spinor fields apply to the Dirac-Bergmann constraint surfaces, on which Gauss's law and the gauge conditions obtain. We examine MCS theory in the large CS coupling constant limit, and compare that limiting form with CS theory, in which the Maxwell kinetic energy term is not included in the Larangian. 34 refs
Cosmological tests of a scale covariant theory of gravitation
International Nuclear Information System (INIS)
Owen, J.R.
1979-01-01
The Friedmann models with #betta# = 0 are subjected to several optical and radio tests within the standard and scale covariant theories of gravitation. Within standard cosmology, both interferometric and scintillation data are interpreted in terms of selection effects and evolution. Within the context of scale covariant cosmology are derived: (1) the full solution to Einstein's gravitational equations in atomic units for a matter dominated universe, (2) the study of the magnitude vs. redshift relation for elliptical galaxies, (3) the derivation of the evolutionary parameter used in (2), (4) the isophotal angular diameter vs. redshift relation, (5) the metric angular diameter vs. redshift relation, (6) the N(m) vs. magnitude relation for QSO's and their m vs z relation, and finally (7) the integrated and differential expressions for the number count vs. radio flux test. The results, both in graphical and tabular form, are presented for four gauges (i.e. parametrized relations between atomic and gravitational units). No contradiction between the new theory and the data is found with any of the tests studied. For some gauges, which are suggested by a recent analysis of the time variation of the Moon's period which is discussed in the text in terms of the new theory, the effect of the deceleration parameter on cosmological predictions is enhanced over standard cosmology and it is possible to say that the data are more easily reconciled with an open universe. Within the same gauge, the main features of both the N(m) vs. m and m-z test are accounted for by the same simple evolutionary parametrization whereas different evolutionary rates were indicated by interpretation within standard cosmology. The same consistency, lacking in standard cosmology on this level of analysis, is achieved for the integrated and differential number count - radio flux tests within the same gauge
Toward a Mexican eddy covariance network for carbon cycle science
Vargas, Rodrigo; Yépez, Enrico A.
2011-09-01
First Annual MexFlux Principal Investigators Meeting; Hermosillo, Sonora, Mexico, 4-8 May 2011; The carbon cycle science community has organized a global network, called FLUXNET, to measure the exchange of energy, water, and carbon dioxide (CO2) between the ecosystems and the atmosphere using the eddy covariance technique. This network has provided unprecedented information for carbon cycle science and global climate change but is mostly represented by study sites in the United States and Europe. Thus, there is an important gap in measurements and understanding of ecosystem dynamics in other regions of the world that are seeing a rapid change in land use. Researchers met under the sponsorship of Red Temática de Ecosistemas and Consejo Nacional de Ciencia y Tecnologia (CONACYT) to discuss strategies to establish a Mexican eddy covariance network (MexFlux) by identifying researchers, study sites, and scientific goals. During the meeting, attendees noted that 10 study sites have been established in Mexico with more than 30 combined years of information. Study sites span from new sites installed during 2011 to others with 9 to 6 years of measurements. Sites with the longest span measurements are located in Baja California Sur (established by Walter Oechel in 2002) and Sonora (established by Christopher Watts in 2005); both are semiarid ecosystems. MexFlux sites represent a variety of ecosystem types, including Mediterranean and sarcocaulescent shrublands in Baja California; oak woodland, subtropical shrubland, tropical dry forest, and a grassland in Sonora; tropical dry forests in Jalisco and Yucatan; a managed grassland in San Luis Potosi; and a managed pine forest in Hidalgo. Sites are maintained with an individual researcher's funds from Mexican government agencies (e.g., CONACYT) and international collaborations, but no coordinated funding exists for a long-term program.
Covariant theory of gravitation in the framework of special relativity
Vieira, R. S.; Brentan, H. B.
2018-04-01
In this work, we study the magnetic effects of gravity in the framework of special relativity. Imposing covariance of the gravitational force with respect to the Lorentz transformations, we show from a thought experiment that a magnetic-like force must be present whenever two or more bodies are in motion. The exact expression for this gravitomagnetic force is then derived purely from special relativity and the consequences of such a covariant theory are developed. For instance, we show that the gravitomagnetic fields satisfy a system of differential equations similar to the Maxwell equations of electrodynamics. This implies that the gravitational waves spread out with the speed of light in a flat spacetime, which is in agreement with the recent results concerning the gravitational waves detection. We also propose that the vector potential can be associated with the interaction momentum in the same way as the scalar potential is usually associated with the interaction energy. Other topics are also discussed, for example, the transformation laws for the fields, the energy and momentum stored in the gravitomagnetic fields, the invariance of the gravitational mass and so on. We remark that is not our intention here to propose an alternative theory of gravitation but, rather, only a first approximation for the gravitational phenomena, so that it can be applied whenever the gravitational force can be regarded as an ordinary effective force field and special relativity can be used with safety. To make this point clear we present briefly a comparison between our approach and that based on the (linearized) Einstein's theory. Finally, we remark that although we have assumed nothing from the electromagnetic theory, we found that gravity and electricity share many properties in common -these similarities, in fact, are just a requirement of special relativity that must apply to any physically acceptable force field.
Multisample adjusted U-statistics that account for confounding covariates.
Satten, Glen A; Kong, Maiying; Datta, Somnath
2018-06-19
Multisample U-statistics encompass a wide class of test statistics that allow the comparison of 2 or more distributions. U-statistics are especially powerful because they can be applied to both numeric and nonnumeric data, eg, ordinal and categorical data where a pairwise similarity or distance-like measure between categories is available. However, when comparing the distribution of a variable across 2 or more groups, observed differences may be due to confounding covariates. For example, in a case-control study, the distribution of exposure in cases may differ from that in controls entirely because of variables that are related to both exposure and case status and are distributed differently among case and control participants. We propose to use individually reweighted data (ie, using the stratification score for retrospective data or the propensity score for prospective data) to construct adjusted U-statistics that can test the equality of distributions across 2 (or more) groups in the presence of confounding covariates. Asymptotic normality of our adjusted U-statistics is established and a closed form expression of their asymptotic variance is presented. The utility of our approach is demonstrated through simulation studies, as well as in an analysis of data from a case-control study conducted among African-Americans, comparing whether the similarity in haplotypes (ie, sets of adjacent genetic loci inherited from the same parent) occurring in a case and a control participant differs from the similarity in haplotypes occurring in 2 control participants. Copyright © 2018 John Wiley & Sons, Ltd.
The Influence of Normalization Weight in Population Pharmacokinetic Covariate Models.
Goulooze, Sebastiaan C; Völler, Swantje; Välitalo, Pyry A J; Calvier, Elisa A M; Aarons, Leon; Krekels, Elke H J; Knibbe, Catherijne A J
2018-03-23
In covariate (sub)models of population pharmacokinetic models, most covariates are normalized to the median value; however, for body weight, normalization to 70 kg or 1 kg is often applied. In this article, we illustrate the impact of normalization weight on the precision of population clearance (CL pop ) parameter estimates. The influence of normalization weight (70, 1 kg or median weight) on the precision of the CL pop estimate, expressed as relative standard error (RSE), was illustrated using data from a pharmacokinetic study in neonates with a median weight of 2.7 kg. In addition, a simulation study was performed to show the impact of normalization to 70 kg in pharmacokinetic studies with paediatric or obese patients. The RSE of the CL pop parameter estimate in the neonatal dataset was lowest with normalization to median weight (8.1%), compared with normalization to 1 kg (10.5%) or 70 kg (48.8%). Typical clearance (CL) predictions were independent of the normalization weight used. Simulations showed that the increase in RSE of the CL pop estimate with 70 kg normalization was highest in studies with a narrow weight range and a geometric mean weight away from 70 kg. When, instead of normalizing with median weight, a weight outside the observed range is used, the RSE of the CL pop estimate will be inflated, and should therefore not be used for model selection. Instead, established mathematical principles can be used to calculate the RSE of the typical CL (CL TV ) at a relevant weight to evaluate the precision of CL predictions.
Moerbeek, Mirjam; van Schie, Sander
2016-07-11
The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.
Cross-covariance functions for multivariate random fields based on latent dimensions
Apanasovich, T. V.
2010-02-16
The problem of constructing valid parametric cross-covariance functions is challenging. We propose a simple methodology, based on latent dimensions and existing covariance models for univariate random fields, to develop flexible, interpretable and computationally feasible classes of cross-covariance functions in closed form. We focus on spatio-temporal cross-covariance functions that can be nonseparable, asymmetric and can have different covariance structures, for instance different smoothness parameters, in each component. We discuss estimation of these models and perform a small simulation study to demonstrate our approach. We illustrate our methodology on a trivariate spatio-temporal pollution dataset from California and demonstrate that our cross-covariance performs better than other competing models. © 2010 Biometrika Trust.
A cautionary note on generalized linear models for covariance of unbalanced longitudinal data
Huang, Jianhua Z.
2012-03-01
Missing data in longitudinal studies can create enormous challenges in data analysis when coupled with the positive-definiteness constraint on a covariance matrix. For complete balanced data, the Cholesky decomposition of a covariance matrix makes it possible to remove the positive-definiteness constraint and use a generalized linear model setup to jointly model the mean and covariance using covariates (Pourahmadi, 2000). However, this approach may not be directly applicable when the longitudinal data are unbalanced, as coherent regression models for the dependence across all times and subjects may not exist. Within the existing generalized linear model framework, we show how to overcome this and other challenges by embedding the covariance matrix of the observed data for each subject in a larger covariance matrix and employing the familiar EM algorithm to compute the maximum likelihood estimates of the parameters and their standard errors. We illustrate and assess the methodology using real data sets and simulations. © 2011 Elsevier B.V.
Extended covariance data formats for the ENDF/B-VI differential data evaluation
International Nuclear Information System (INIS)
Peelle, R.W.; Muir, D.W.
1988-01-01
The ENDF/B-V included cross section covariance data, but covariances could not be encoded for all the important data types. New ENDF-6 covariance formats are outlined including those for cross-file (MF) covariances, resonance parameters over the whole range, and secondary energy and angle distributions. One ''late entry'' format encodes covariance data for cross sections that are output from model or fitting codes in terms of the model parameter covariance matrix and the tabulated derivatives of cross sections with respect to the model parameters. Another new format yields multigroup cross section variances that increase as the group width decreases. When evaluators use the new formats, the files can be processed and used for improved uncertainty propagation and data combination. 22 refs
On the Covariance of Moore-Penrose Inverses in Rings with Involution
Mahzoon, Hesam
2014-01-01
We consider the so-called covariance set of Moore-Penrose inverses in rings with an involution. We deduce some new results concerning covariance set. We will show that if $a$ is a regular element in a ${C}^{\\ast }$ -algebra, then the covariance set of $a$ is closed in the set of invertible elements (with relative topology) of ${C}^{\\ast }$ -algebra and is a cone in the ${C}^{\\ast }$ -algebra.
Yu, Xu; Yu, Miao; Xu, Li-xun; Yang, Jing; Xie, Zhi-qiang
2015-01-01
The assumption that the training and testing samples are drawn from the same distribution is violated under covariate shift setting, and most algorithms for the covariate shift setting try to first estimate distributions and then reweight samples based on the distributions estimated. Due to the difficulty of estimating a correct distribution, previous methods can not get good classification performance. In this paper, we firstly present two types of covariate shift problems. Rather than estim...
The covariance matrix of neutron spectra used in the REAL 84 exercise
International Nuclear Information System (INIS)
Matzke, M.
1986-08-01
Covariance matrices of continuous functions are discussed. It is pointed out that the number of non-vanishing eigenvalues corresponds to the number of random variables (parameters) involved in the construction of the continuous functions. The covariance matrices used in the REAL 84 international intercomparison of unfolding methods of neutron spectra are investigated. It is shown that a small rank of these covariance matrices leads to a restriction of the possible solution spectra. (orig.) [de
Alam, Md. Ashad; Fukumizu, Kenji; Wang, Yu-Ping
2016-01-01
To the best of our knowledge, there are no general well-founded robust methods for statistical unsupervised learning. Most of the unsupervised methods explicitly or implicitly depend on the kernel covariance operator (kernel CO) or kernel cross-covariance operator (kernel CCO). They are sensitive to contaminated data, even when using bounded positive definite kernels. First, we propose robust kernel covariance operator (robust kernel CO) and robust kernel crosscovariance operator (robust kern...