Information content of weak lensing bispectrum: including the non-Gaussian error covariance matrix
Kayo, Issha; Jain, Bhuvnesh
2013-01-01
We address a long-standing problem, how can we extract information in the non-Gaussian regime of weak lensing surveys, by accurate modeling of all relevant covariances between the power spectra and bispectra. We use 1000 ray-tracing simulation realizations for a Lambda-CDM model and an analytical halo model. We develop a formalism to describe the covariance matrices of power spectra and bispectra of all triangle configurations, which extend to 6-point correlation functions. We include a new contribution arising from coupling of the lensing Fourier modes with large-scale mass fluctuations on scales comparable with the survey region via halo bias theory, which we call the halo sample variance (HSV) effect. We show that the model predictions are in excellent agreement with the simulation results for the power spectrum and bispectrum covariances. The HSV effect gives a dominant contribution to the covariances at multipoles l > 10^3, which arise from massive halos with masses of about 10^14 solar masses and at rel...
Contamination vs. harm-relevant outcome expectancies and covariation bias in spider phobia
de Jong, Peter J.; Peters, Madelon L.
There is increasing evidence that spiders are not feared because of harmful outcome expectancies but because of disgust and contamination-relevant outcome expectancies. This study investigated the relative strength of contamination- and harm-relevant UCS expectancies and covariation bias in spider
Contamination vs. harm-relevant outcome expectancies and covariation bias in spider phobia.
de Jong, Peter J; Peters, Madelon L
2007-06-01
There is increasing evidence that spiders are not feared because of harmful outcome expectancies but because of disgust and contamination-relevant outcome expectancies. This study investigated the relative strength of contamination- and harm-relevant UCS expectancies and covariation bias in spider phobia. High (n=25) and low (n=24) spider fearful individuals saw a series of slides comprising spiders, pitbulls, maggots, and rabbits. Slides were randomly paired with either a harm-relevant outcome (electrical shock), a contamination-related outcome (drinking of a distasting fluid), or nothing. Spider fearful individuals displayed a contamination-relevant UCS expectancy bias associated with spiders, whereas controls displayed a harm-relevant expectancy bias. There was no evidence for a (differential) postexperimental covariation bias; thus the biased expectancies were not robust against refutation. The present findings add to the evidence that contamination ideation is critically involved in spider phobia.
Revised error propagation of 40Ar/39Ar data, including covariances
Vermeesch, Pieter
2015-12-01
The main advantage of the 40Ar/39Ar method over conventional K-Ar dating is that it does not depend on any absolute abundance or concentration measurements, but only uses the relative ratios between five isotopes of the same element -argon- which can be measured with great precision on a noble gas mass spectrometer. The relative abundances of the argon isotopes are subject to a constant sum constraint, which imposes a covariant structure on the data: the relative amount of any of the five isotopes can always be obtained from that of the other four. Thus, the 40Ar/39Ar method is a classic example of a 'compositional data problem'. In addition to the constant sum constraint, covariances are introduced by a host of other processes, including data acquisition, blank correction, detector calibration, mass fractionation, decay correction, interference correction, atmospheric argon correction, interpolation of the irradiation parameter, and age calculation. The myriad of correlated errors arising during the data reduction are best handled by casting the 40Ar/39Ar data reduction protocol in a matrix form. The completely revised workflow presented in this paper is implemented in a new software platform, Ar-Ar_Redux, which takes raw mass spectrometer data as input and generates accurate 40Ar/39Ar ages and their (co-)variances as output. Ar-Ar_Redux accounts for all sources of analytical uncertainty, including those associated with decay constants and the air ratio. Knowing the covariance matrix of the ages removes the need to consider 'internal' and 'external' uncertainties separately when calculating (weighted) mean ages. Ar-Ar_Redux is built on the same principles as its sibling program in the U-Pb community (U-Pb_Redux), thus improving the intercomparability of the two methods with tangible benefits to the accuracy of the geologic time scale. The program can be downloaded free of charge from
Leeb, H., E-mail: leeb@kph.tuwien.ac.at; Schnabel, G.; Srdinko, Th.; Wildpaner, V.
2015-01-15
A new evaluation of neutron-induced reactions on {sup 181}Ta using a consistent procedure based on Bayesian statistics is presented. Starting point of the evaluation is the description of nuclear reactions via nuclear models implemented in TALYS 1.4. A retrieval of experimental data was performed and covariance matrices of the experiments were generated from an extensive study of the corresponding literature. All reaction channels required for a transport file up to 200 MeV have been considered and the covariance matrices of cross section uncertainties for the most important channels are determined. The evaluation has been performed in one step including all available experimental data. A comparison of the evaluated cross sections and spectra with experimental data and available evaluations is performed. In general the evaluated cross section reflect our best knowledge and give a fair description of the observables. However, there are few deviations from expectation which clearly indicate the impact of the prior and the need to account for model defects. Using the results of the evaluation a complete ENDF-file similarly to those of the TENDL library is generated.
Ar-Ar_Redux: rigorous error propagation of 40Ar/39Ar data, including covariances
Vermeesch, P.
2015-12-01
Rigorous data reduction and error propagation algorithms are needed to realise Earthtime's objective to improve the interlaboratory accuracy of 40Ar/39Ar dating to better than 1% and thereby facilitate the comparison and combination of the K-Ar and U-Pb chronometers. Ar-Ar_Redux is a new data reduction protocol and software program for 40Ar/39Ar geochronology which takes into account two previously underappreciated aspects of the method: 1. 40Ar/39Ar measurements are compositional dataIn its simplest form, the 40Ar/39Ar age equation can be written as: t = log(1+J [40Ar/39Ar-298.5636Ar/39Ar])/λ = log(1 + JR)/λ Where λ is the 40K decay constant and J is the irradiation parameter. The age t does not depend on the absolute abundances of the three argon isotopes but only on their relative ratios. Thus, the 36Ar, 39Ar and 40Ar abundances can be normalised to unity and plotted on a ternary diagram or 'simplex'. Argon isotopic data are therefore subject to the peculiar mathematics of 'compositional data', sensu Aitchison (1986, The Statistical Analysis of Compositional Data, Chapman & Hall). 2. Correlated errors are pervasive throughout the 40Ar/39Ar methodCurrent data reduction protocols for 40Ar/39Ar geochronology propagate the age uncertainty as follows: σ2(t) = [J2 σ2(R) + R2 σ2(J)] / [λ2 (1 + R J)], which implies zero covariance between R and J. In reality, however, significant error correlations are found in every step of the 40Ar/39Ar data acquisition and processing, in both single and multi collector instruments, during blank, interference and decay corrections, age calculation etc. Ar-Ar_Redux revisits every aspect of the 40Ar/39Ar method by casting the raw mass spectrometer data into a contingency table of logratios, which automatically keeps track of all covariances in a compositional context. Application of the method to real data reveals strong correlations (r2 of up to 0.9) between age measurements within a single irradiation batch. Propertly taking
Bhatnagar, Shashank; Mengesha, Yikdem
2013-01-01
In this work we have employed Bethe-Salpeter equation (BSE) under covariant instantaneous ansatz (CIA) to study electromagnetic decays of ground state equal mass vector mesons: $\\rho$, $\\omega$, $\\phi$, $\\psi$ and $Y$ through the process $V\\rightarrow\\gamma*\\rightarrow e^+ + e^-$. We employ the generalized structure of hadron-quark vertex function $\\Gamma$ which incorporates various Dirac structures from their complete set order-by-order in powers of inverse of meson mass. The electromagnetic decay constants for the above mesons are calculated using the leading order (LO) and the next-to-leading order (NLO) Dirac structures. The relevance of various Dirac structures in this calculation is studied.
Clay, J.; Kent, E. R.; Leinfelder-Miles, M.; Lambert, J. J.; Little, C.; Paw U, K. T.; Snyder, R. L.
2016-12-01
Eddy covariance and surface renewal measurements were used to estimate evapotranspiration (ET) over a variety of crop fields in the Sacramento-San Joaquin River Delta during the 2016 growing season. However, comparing and evaluating multiple measurement systems and methods for determining ET was focused upon at a single alfalfa site. The eddy covariance systems included two systems for direct measurement of latent heat flux: one using a separate sonic anemometer and an open path infrared gas analyzer and another using a combined system (Campbell Scientific IRGASON). For these methods, eddy covariance was used with measurements from the Campbell Scientific CSAT3, the LI-COR 7500a, the Campbell Scientific IRGASON, and an additional R.M. Young sonic anemometer. In addition to those direct measures, the surface renewal approach included several energy balance residual methods in which net radiation, ground heat flux, and sensible heat flux (H) were measured. H was measured using several systems and different methods, including using multiple fast-response thermocouple measurements and using the temperatures measured by the sonic anemometers. The energy available for ET was then calculated as the residual of the surface energy balance equation. Differences in ET values were analyzed between the eddy covariance and surface renewal methods, using the IRGASON-derived values of ET as the standard for accuracy.
Elizabeth Margaret Stovold
2017-06-01
Full Text Available A Review of: Hanneke, R., & O’Brien, K. K. (2016. Comparison of three web-scale discovery services for health sciences research. Journal of the Medical Library Association, 104(2, 109-117. http://dx.doi.org/10.3163/1536-5050.104.2.004 Abstract Objective – To compare the results of health sciences search queries in three web-scale discovery (WSD services for relevance, duplicate detection, and retrieval of MEDLINE content. Design – Comparative evaluation and bibliometric study. Setting – Six university libraries in the United States of America. Subjects – Three commercial WSD services: Primo, Summon, and EBSCO Discovery Service (EDS. Methods – The authors collected data at six universities, including their own. They tested each of the three WSDs at two data collection sites. However, since one of the sites was using a legacy version of Summon that was due to be upgraded, data collected for Summon at this site were considered obsolete and excluded from the analysis. The authors generated three questions for each of six major health disciplines, then designed simple keyword searches to mimic typical student search behaviours. They captured the first 20 results from each query run at each test site, to represent the first “page” of results, giving a total of 2,086 total search results. These were independently assessed for relevance to the topic. Authors resolved disagreements by discussion, and calculated a kappa inter-observer score. They retained duplicate records within the results so that the duplicate detection by the WSDs could be compared. They assessed MEDLINE coverage by the WSDs in several ways. Using precise strategies to generate a relevant set of articles, they conducted one search from each of the six disciplines in PubMed so that they could compare retrieval of MEDLINE content. These results were cross-checked against the first 20 results from the corresponding query in the WSDs. To aid investigation of overall
Elaboration of a guide including relevant project and logistic information: a case study
Costa, Tchaikowisky M. [Faculdade de Tecnologia e Ciencias (FTC), Itabuna, BA (Brazil); Bresci, Claudio T.; Franca, Carlos M.M. [PETROBRAS, Rio de Janeiro, RJ (Brazil)
2009-07-01
For every mobilization of a new enterprise it is necessary to quickly obtain the greatest amount of relative information in regards to location and availability of infra-structure, logistics, and work site amenities. Among this information are reports elaborated for management of the enterprise, (organizational chart, work schedule, objectives, contacts, etc.) as well as geographic anomalies, social-economic and culture of the area to be developed such as territorial extension, land aspects, local population, roads and amenities (fuel stations ,restaurants and hotels), infra-structure of the cities (health, education, entertainment, housing, transport, etc.) and logistically the distance between cities the estimated travel time, ROW access maps and notable points, among other relevant information. With the idea of making this information available for everyone involved in the enterprise, it was elaborated for GASCAC Spread 2A a rapid guide containing all the information mentioned above and made it available for all the vehicles used to transport employees and visitors to the spread. With this, everyone quickly received the majority of information necessary in one place, in a practical, quick, and precise manner, since the information is always used and controlled by the same person. This study includes the model used in the gas pipeline GASCAC Spread 2A project and the methodology used to draft and update the information. Besides the above, a file in the GIS format was prepared containing all necessary planning, execution and tracking information for enterprise activities, from social communication to the execution of the works previously mentioned. Part of the GIS file information was uploaded to Google Earth so as to disclose the information to a greater group of people, bearing in mind that this program is free of charge and easy to use. (author)
O'Callaghan, Clare C.; McDermott, Fiona; Hudson, Peter; Zalcberg, John R.
2013-01-01
This study examines music's relevance, including preloss music therapy, for 8 informal caregivers of people who died from cancer. The design was informed by constructivist grounded theory and included semistructured interviews. Bereaved caregivers were supported or occasionally challenged as their musical lives enabled a connection with the…
O'Callaghan, Clare C.; McDermott, Fiona; Hudson, Peter; Zalcberg, John R.
2013-01-01
This study examines music's relevance, including preloss music therapy, for 8 informal caregivers of people who died from cancer. The design was informed by constructivist grounded theory and included semistructured interviews. Bereaved caregivers were supported or occasionally challenged as their musical lives enabled a connection with the…
Wyatt, Kirk D; Anderson, Ryan T; Creedon, Douglas; Montori, Victor M; Bachman, John; Erwin, Patricia; LeBlanc, Annie
2014-02-13
Women can choose from a range of contraceptive methods that differ in important ways. Inadequate decision support may lead them to select a method that poorly fits their circumstances, leading to dissatisfaction, misuse, or nonuse. Decision support interventions, such as decision aids, may help women choose a method of contraception that best fits their personal circumstances. To guide future decision aid development, we aim to summarize the attributes of contraceptive methods included in available decision aids as well as surveys and interviews of women actively choosing a contraceptive method. We conducted a systematic review to identify attributes of contraceptive methods that may be important to women when engaging in this decision making process. We performed a database search of MEDLINE/PubMed, Ovid EMBASE, OVID CENTRAL, Ovid PsycInfo, EBSCO CINAHL, Popline, and Scopus from 1985 until 2013 to identify decision aids, structured interviews and questionnaires reporting attributes of contraceptive options that are of importance to women. A free-text internet search was also performed to identify additional decision support tools. All articles and tools were reviewed in duplicate for inclusion, and a summary list of attributes was compiled. We included 20 surveys, 1 semistructured interview report and 19 decision aids, reporting 32 unique attributes. While some attributes were consistently included in surveys/interviews and decision aids, several were included more often in decision aids as opposed to surveys/interviews (e.g., STI prevention, noncontraceptive benefits, how the method is used, requirement of a healthcare provider), and vice versa (e.g., a woman's vicarious experience with contraceptive methods). Key attributes mentioned in both surveys/interviews and decision aids include efficacy (29 total mentioned) and side effects/health risks (28 total mentioned). While a limited number of decision support tools were formally evaluated, many were not
Diagnostic Relevance of microRNAs in Other Body Fluids Including Urine, Feces, and Saliva.
Igaz, Ivan; Igaz, Peter
2015-01-01
Beside blood-borne circulating miRNAs, miRNAs have been identified in other body fluid and excrements including stool, bile, saliva, and urine. Given the direct link of these body fluids to certain organs, their analysis for potential diagnostic miRNA markers is plausible. Several independent findings underline the potential utility of stool-derived miRNAs in the diagnosis of colorectal and pancreatic cancer. Given the difficulties in the diagnosis of cholangiocellular cancer, biliary miRNAs might be envisaged as useful markers. Several miRNAs have been identified in the saliva that could be associated with diseases, including tumors of the oral cavity. The urinary pool of miRNAs could be exploited for the diagnosis of urinary tract diseases and some appear to enable early diagnosis. In this chapter, we present findings supporting the potential diagnostic utility of fecal, biliary, salivary, and urinary miRNAs focusing mostly on tumors.
Ottowitz, William E.; Derro, David; Dougherty, Darin D.; Lindquist, Martin A.; Fischman, Alan J.; Hall, Janet E.
2014-01-01
Objectives 1.) Expand the scope of neuroendocrine applications of functional neuroimaging techniques. 2.) Compare the covariance of amygdalar activity with that of the rest of the brain during pre- and post-menopausal levels of estrogen (E2). Based on the distribution of cortical E2 receptors and the neocortical regions where E2 has been shown to preferentially accumulate, we predict that E2 infusion will increase covariance of amygdalar activity with that of the temporal and frontal cortices. Design This basic physiology study employed a within-subject design. All participants were post-menopausal women (n =7). Analysis of covariance between whole brain and amygdalar regional cerebral glucose consumption (CMRglc) was conducted in a voxel-wise manner by means of the basic regression option in SPM2 and was applied to FDG-PET scans acquired at baseline and after a 24 hour graded E2 infusion. Setting an academic medical center; Massachusetts General Hospital, Boston, Massachusetts. Results E2 levels (mean ± sem) were significantly greater at 24 hours (257.9 pg/mL ± 29.7) than at 0 hours (28.1 pg/mL ± 3.4). Right amygdalar CMRglc showed a significant covariance with activity of three different regions of the temporal cortex during E2 infusion, but none at baseline. In addition, right amygdalar CMRglc covaried with that of the right medial and superior frontal gyri only during E2 infusion. Conclusions In addition to suggesting changes in amygdalar-cortical network connectivity as a result of short-term E2 exposure, these analyses provide evidence that basic neuroendocrine research may benefit from further use of FDG-PET and other functional neuroimaging modalities for network level analyses. PMID:18766152
Frasinski, Leszek J.
2016-08-01
Recent technological advances in the generation of intense femtosecond pulses have made covariance mapping an attractive analytical technique. The laser pulses available are so intense that often thousands of ionisation and Coulomb explosion events will occur within each pulse. To understand the physics of these processes the photoelectrons and photoions need to be correlated, and covariance mapping is well suited for operating at the high counting rates of these laser sources. Partial covariance is particularly useful in experiments with x-ray free electron lasers, because it is capable of suppressing pulse fluctuation effects. A variety of covariance mapping methods is described: simple, partial (single- and multi-parameter), sliced, contingent and multi-dimensional. The relationship to coincidence techniques is discussed. Covariance mapping has been used in many areas of science and technology: inner-shell excitation and Auger decay, multiphoton and multielectron ionisation, time-of-flight and angle-resolved spectrometry, infrared spectroscopy, nuclear magnetic resonance imaging, stimulated Raman scattering, directional gamma ray sensing, welding diagnostics and brain connectivity studies (connectomics). This review gives practical advice for implementing the technique and interpreting the results, including its limitations and instrumental constraints. It also summarises recent theoretical studies, highlights unsolved problems and outlines a personal view on the most promising research directions.
Covariance Applications with Kiwi
Mattoon, C. M.; Brown, D.; Elliott, J. B.
2012-05-01
The Computational Nuclear Physics group at Lawrence Livermore National Laboratory (LLNL) is developing a new tool, named `Kiwi', that is intended as an interface between the covariance data increasingly available in major nuclear reaction libraries (including ENDF and ENDL) and large-scale Uncertainty Quantification (UQ) studies. Kiwi is designed to integrate smoothly into large UQ studies, using the covariance matrix to generate multiple variations of nuclear data. The code has been tested using critical assemblies as a test case, and is being integrated into LLNL's quality assurance and benchmarking for nuclear data.
Covariance Applications with Kiwi
Elliott J.B.
2012-05-01
Full Text Available The Computational Nuclear Physics group at Lawrence Livermore National Laboratory (LLNL is developing a new tool, named ‘Kiwi’, that is intended as an interface between the covariance data increasingly available in major nuclear reaction libraries (including ENDF and ENDL and large-scale Uncertainty Quantification (UQ studies. Kiwi is designed to integrate smoothly into large UQ studies, using the covariance matrix to generate multiple variations of nuclear data. The code has been tested using critical assemblies as a test case, and is being integrated into LLNL's quality assurance and benchmarking for nuclear data.
van der Weide, Robin H; Simonis, Marieke; Hermsen, Roel; Toonen, Pim; Cuppen, Edwin; de Ligt, Joep
2016-01-01
Unmapped next-generation sequencing reads are typically ignored while they contain biologically relevant information. We systematically analyzed unmapped reads from whole genome sequencing of 33 inbred rat strains. High quality reads were selected and enriched for biologically relevant sequences; similarity-based analysis revealed clustering similar to previously reported phylogenetic trees. Our results demonstrate that on average 20% of all unmapped reads harbor sequences that can be used to improve reference genomes and generate hypotheses on potential genotype-phenotype relationships. Analysis pipelines would benefit from incorporating the described methods and reference genomes would benefit from inclusion of the genomic segments obtained through these efforts.
Estimating Cosmological Parameter Covariance
Taylor, Andy
2014-01-01
We investigate the bias and error in estimates of the cosmological parameter covariance matrix, due to sampling or modelling the data covariance matrix, for likelihood width and peak scatter estimators. We show that these estimators do not coincide unless the data covariance is exactly known. For sampled data covariances, with Gaussian distributed data and parameters, the parameter covariance matrix estimated from the width of the likelihood has a Wishart distribution, from which we derive the mean and covariance. This mean is biased and we propose an unbiased estimator of the parameter covariance matrix. Comparing our analytic results to a numerical Wishart sampler of the data covariance matrix we find excellent agreement. An accurate ansatz for the mean parameter covariance for the peak scatter estimator is found, and we fit its covariance to our numerical analysis. The mean is again biased and we propose an unbiased estimator for the peak parameter covariance. For sampled data covariances the width estimat...
COVARIATION BIAS AND THE RETURN OF FEAR
de Jong, Peter; VANDENHOUT, MA; MERCKELBACH, H
1995-01-01
Several studies have indicated that phobic fear is accompanied by a covariation bias, i.e. that phobic Ss tend to overassociate fear relevant stimuli and aversive outcomes. Such a covariation bias seems to be a fairly direct and powerful way to confirm danger expectations and enhance fear. Therefore
Covariant representations of subproduct systems
Viselter, Ami
2010-01-01
A celebrated theorem of Pimsner states that a covariant representation $T$ of a $C^*$-correspondence $E$ extends to a $C^*$-representation of the Toeplitz algebra of $E$ if and only if $T$ is isometric. This paper is mainly concerned with finding conditions for a covariant representation of a \\emph{subproduct system} to extend to a $C^*$-representation of the Toeplitz algebra. This framework is much more general than the former. We are able to find sufficient conditions, and show that in important special cases, they are also necessary. Further results include the universality of the tensor algebra, dilations of completely contractive covariant representations, Wold decompositions and von Neumann inequalities.
Makki-Rmida, Faten; Kammoun, Arwa; Mahfoudh, Nadia; Ayadi, Adnene; Gibriel, Abdullah Ahmed; Mallek, Bakhta; Maalej, Leila; Hammami, Zouheir; Maatoug, Samir; Makni, Hafedh; Masmoudi, Saber
2015-12-01
Y chromosome STRs (Y-STRs) are being used frequently in forensic laboratories. Previous studies of Y-STR polymorphisms in different groups of the Tunisian population identified low levels of diversity and discrimination capacity (DC) using various commercial marker sets. This definitely limits the use of such systems for Y-STRs genotyping in Tunisia. In our investigation on South Tunisia, 200 unrelated males were typed for the 12 conventional Y-STRs included in the PowerPlex® Y System. Additional set of nine noncore Y-STRs including DYS446, DYS456, DYS458, DYS388, DYS444, DYS445, DYS449, DYS710, and DYS464 markers were genotyped and evaluated for their potential in improving DC. Allele frequency, gene diversity, haplotype diversity (HD), and DC calculation revealed that DYS464 was the most diverse marker followed by DYS710 and DYS449 markers. The standard panel of 12 Y-STRs (DC = 80.5%) and the nine markers were combined to obtain DC of 99%. Among the 198 different haplotypes observed, 196 haplotypes were unique (HD = 99.999). Out of the nine noncore set, six Y-STRs (DYS458, DYS456, DYS449, DYS710, DYS444, and DYS464) had the greatest impact on enhancing DC. Our data provided putative Y-STRs combination to be used for genetic and forensic applications.
Deriving covariant holographic entanglement
Dong, Xi; Lewkowycz, Aitor; Rangamani, Mukund
2016-11-01
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.
Deriving covariant holographic entanglement
Dong, Xi; Rangamani, Mukund
2016-01-01
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 Renyi 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.
Covariance Evaluation Methodology for Neutron Cross Sections
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.
Manifestly covariant electromagnetism
Hillion, P. [Institut Henri Poincare' , Le Vesinet (France)
1999-03-01
The conventional relativistic formulation of electromagnetism is covariant under the full Lorentz group. But relativity requires covariance only under the proper Lorentz group and the authors present here the formalism covariant under the complex rotation group isomorphic to the proper Lorentz group. The authors discuss successively Maxwell's equations, constitutive relations and potential functions. A comparison is made with the usual formulation.
AFCI-2.0 Neutron Cross Section Covariance Library
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
The cross section covariance library has been under development by BNL-LANL collaborative effort over the last three years. The project builds on two covariance libraries developed earlier, with considerable input from BNL and LANL. In 2006, international effort under WPEC Subgroup 26 produced BOLNA covariance library by putting together data, often preliminary, from various sources for most important materials for nuclear reactor technology. This was followed in 2007 by collaborative effort of four US national laboratories to produce covariances, often of modest quality - hence the name low-fidelity, for virtually complete set of materials included in ENDF/B-VII.0. The present project is focusing on covariances of 4-5 major reaction channels for 110 materials of importance for power reactors. The work started under Global Nuclear Energy Partnership (GNEP) in 2008, which changed to Advanced Fuel Cycle Initiative (AFCI) in 2009. With the 2011 release the name has changed to the Covariance Multigroup Matrix for Advanced Reactor Applications (COMMARA) version 2.0. The primary purpose of the library is to provide covariances for AFCI data adjustment project, which is focusing on the needs of fast advanced burner reactors. Responsibility of BNL was defined as developing covariances for structural materials and fission products, management of the library and coordination of the work; LANL responsibility was defined as covariances for light nuclei and actinides. The COMMARA-2.0 covariance library has been developed by BNL-LANL collaboration for Advanced Fuel Cycle Initiative applications over the period of three years, 2008-2010. It contains covariances for 110 materials relevant to fast reactor R&D. The library is to be used together with the ENDF/B-VII.0 central values of the latest official release of US files of evaluated neutron cross sections. COMMARA-2.0 library contains neutron cross section covariances for 12 light nuclei (coolants and moderators), 78 structural
AFCI-2.0 Neutron Cross Section Covariance Library
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
The cross section covariance library has been under development by BNL-LANL collaborative effort over the last three years. The project builds on two covariance libraries developed earlier, with considerable input from BNL and LANL. In 2006, international effort under WPEC Subgroup 26 produced BOLNA covariance library by putting together data, often preliminary, from various sources for most important materials for nuclear reactor technology. This was followed in 2007 by collaborative effort of four US national laboratories to produce covariances, often of modest quality - hence the name low-fidelity, for virtually complete set of materials included in ENDF/B-VII.0. The present project is focusing on covariances of 4-5 major reaction channels for 110 materials of importance for power reactors. The work started under Global Nuclear Energy Partnership (GNEP) in 2008, which changed to Advanced Fuel Cycle Initiative (AFCI) in 2009. With the 2011 release the name has changed to the Covariance Multigroup Matrix for Advanced Reactor Applications (COMMARA) version 2.0. The primary purpose of the library is to provide covariances for AFCI data adjustment project, which is focusing on the needs of fast advanced burner reactors. Responsibility of BNL was defined as developing covariances for structural materials and fission products, management of the library and coordination of the work; LANL responsibility was defined as covariances for light nuclei and actinides. The COMMARA-2.0 covariance library has been developed by BNL-LANL collaboration for Advanced Fuel Cycle Initiative applications over the period of three years, 2008-2010. It contains covariances for 110 materials relevant to fast reactor R&D. The library is to be used together with the ENDF/B-VII.0 central values of the latest official release of US files of evaluated neutron cross sections. COMMARA-2.0 library contains neutron cross section covariances for 12 light nuclei (coolants and moderators), 78 structural
Land, M C
2001-01-01
This paper examines the Stark effect, as a first order perturbation of manifestly covariant hydrogen-like bound states. These bound states are solutions to a relativistic Schr\\"odinger equation with invariant evolution parameter, and represent mass eigenstates whose eigenvalues correspond to the well-known energy spectrum of the non-relativistic theory. In analogy to the nonrelativistic case, the off-diagonal perturbation leads to a lifting of the degeneracy in the mass spectrum. In the covariant case, not only do the spectral lines split, but they acquire an imaginary part which is lnear in the applied electric field, thus revealing induced bound state decay in first order perturbation theory. This imaginary part results from the coupling of the external field to the non-compact boost generator. In order to recover the conventional first order Stark splitting, we must include a scalar potential term. This term may be understood as a fifth gauge potential, which compensates for dependence of gauge transformat...
Treatment Effects with Many Covariates and Heteroskedasticity
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 are obtai......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...... then propose a new heteroskedasticity consistent standard error formula that is fully automatic and robust to both (conditional) heteroskedasticity of unknown form and the inclusion of possibly many covariates. We apply our findings to three settings: (i) parametric linear models with many covariates, (ii...
Covariant Hamiltonian field theory
Giachetta, G; Sardanashvily, G
1999-01-01
We study the relationship between the equations of first order Lagrangian field theory on fiber bundles and the covariant Hamilton equations on the finite-dimensional polysymplectic phase space of covariant Hamiltonian field theory. The main peculiarity of these Hamilton equations lies in the fact that, for degenerate systems, they contain additional gauge fixing conditions. We develop the BRST extension of the covariant Hamiltonian formalism, characterized by a Lie superalgebra of BRST and anti-BRST symmetries.
Multivariate covariance generalized linear models
Bonat, W. H.; Jørgensen, Bent
2016-01-01
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...... 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...
Covariance evaluation work at LANL
Kawano, Toshihiko [Los Alamos National Laboratory; Talou, Patrick [Los Alamos National Laboratory; Young, Phillip [Los Alamos National Laboratory; Hale, Gerald [Los Alamos National Laboratory; Chadwick, M B [Los Alamos National Laboratory; Little, R C [Los Alamos National Laboratory
2008-01-01
Los Alamos evaluates covariances for nuclear data library, mainly for actinides above the resonance regions and light elements in the enUre energy range. We also develop techniques to evaluate the covariance data, like Bayesian and least-squares fitting methods, which are important to explore the uncertainty information on different types of physical quantities such as elastic scattering angular distribution, or prompt neutron fission spectra. This paper summarizes our current activities of the covariance evaluation work at LANL, including the actinide and light element data mainly for the criticality safety study and transmutation technology. The Bayesian method based on the Kalman filter technique, which combines uncertainties in the theoretical model and experimental data, is discussed.
Covariant diagrams for one-loop matching
Zhang, Zhengkang
2016-01-01
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.
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 derivative of fermions and all that
Shapiro, Ilya L
2016-01-01
We present detailed pedagogical derivation of covariant derivative of fermions and some related expressions, including commutator of covariant derivatives and energy-momentum tensor of a free Dirac field. The text represents a part of the initial chapter of a one-semester course on semiclassical gravity.
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
Holtrop, Kendal; Chaviano, Casey L; Scott, Jenna C; McNeil Smith, Shardé
2015-11-01
Homeless families in transitional housing face a number of distinct challenges, yet there is little research seeking to guide prevention and intervention work with homeless parents. Informed by the tenets of community-based participatory research, the purpose of this study was to identify relevant components to include in a parenting intervention for this population. Data were gathered from 40 homeless parents through semistructured individual interviews and were analyzed using qualitative content analysis. The resulting 15 categories suggest several topics, approach considerations, and activities that can inform parenting intervention work with homeless families in transitional housing. Study findings are discussed within the context of intervention fidelity versus adaptation, and implications for practice, research, and policy are suggested. This study provides important insights for informing parenting intervention adaptation and implementation efforts with homeless families in transitional housing. (PsycINFO Database Record
Covariant diagrams for one-loop matching
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.
Quantum corrections for the cubic Galileon in the covariant language
Saltas, Ippocratis D.; Vitagliano, Vincenzo
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.
Robustness of learning that is based on covariance-driven synaptic plasticity.
Yonatan Loewenstein
2008-03-01
Full Text Available It is widely believed that learning is due, at least in part, to long-lasting modifications of the strengths of synapses in the brain. Theoretical studies have shown that a family of synaptic plasticity rules, in which synaptic changes are driven by covariance, is particularly useful for many forms of learning, including associative memory, gradient estimation, and operant conditioning. Covariance-based plasticity is inherently sensitive. Even a slight mistuning of the parameters of a covariance-based plasticity rule is likely to result in substantial changes in synaptic efficacies. Therefore, the biological relevance of covariance-based plasticity models is questionable. Here, we study the effects of mistuning parameters of the plasticity rule in a decision making model in which synaptic plasticity is driven by the covariance of reward and neural activity. An exact covariance plasticity rule yields Herrnstein's matching law. We show that although the effect of slight mistuning of the plasticity rule on the synaptic efficacies is large, the behavioral effect is small. Thus, matching behavior is robust to mistuning of the parameters of the covariance-based plasticity rule. Furthermore, the mistuned covariance rule results in undermatching, which is consistent with experimentally observed behavior. These results substantiate the hypothesis that approximate covariance-based synaptic plasticity underlies operant conditioning. However, we show that the mistuning of the mean subtraction makes behavior sensitive to the mistuning of the properties of the decision making network. Thus, there is a tradeoff between the robustness of matching behavior to changes in the plasticity rule and its robustness to changes in the properties of the decision making network.
Covariant Bardeen perturbation formalism
Vitenti, S. D. P.; Falciano, F. T.; Pinto-Neto, N.
2014-05-01
In a previous work we obtained a set of necessary conditions for the linear approximation in cosmology. Here we discuss the relations of this approach with the so-called covariant perturbations. It is often argued in the literature that one of the main advantages of the covariant approach to describe cosmological perturbations is that the Bardeen formalism is coordinate dependent. In this paper we will reformulate the Bardeen approach in a completely covariant manner. For that, we introduce the notion of pure and mixed tensors, which yields an adequate language to treat both perturbative approaches in a common framework. We then stress that in the referred covariant approach, one necessarily introduces an additional hypersurface choice to the problem. Using our mixed and pure tensors approach, we are able to construct a one-to-one map relating the usual gauge dependence of the Bardeen formalism with the hypersurface dependence inherent to the covariant approach. Finally, through the use of this map, we define full nonlinear tensors that at first order correspond to the three known gauge invariant variables Φ, Ψ and Ξ, which are simultaneously foliation and gauge invariant. We then stress that the use of the proposed mixed tensors allows one to construct simultaneously gauge and hypersurface invariant variables at any order.
Covariant canonical quantization
Hippel, G.M. von [University of Regina, Department of Physics, Regina, Saskatchewan (Canada); Wohlfarth, M.N.R. [Universitaet Hamburg, Institut fuer Theoretische Physik, Hamburg (Germany)
2006-09-15
We present a manifestly covariant quantization procedure based on the de Donder-Weyl Hamiltonian formulation of classical field theory. This procedure agrees with conventional canonical quantization only if the parameter space is d=1 dimensional time. In d>1 quantization requires a fundamental length scale, and any bosonic field generates a spinorial wave function, leading to the purely quantum-theoretical emergence of spinors as a byproduct. We provide a probabilistic interpretation of the wave functions for the fields, and we apply the formalism to a number of simple examples. These show that covariant canonical quantization produces both the Klein-Gordon and the Dirac equation, while also predicting the existence of discrete towers of identically charged fermions with different masses. Covariant canonical quantization can thus be understood as a ''first'' or pre-quantization within the framework of conventional QFT. (orig.)
Covariant canonical quantization
Von Hippel, G M; Hippel, Georg M. von; Wohlfarth, Mattias N.R.
2006-01-01
We present a manifestly covariant quantization procedure based on the de Donder-Weyl Hamiltonian formulation of classical field theory. Covariant canonical quantization agrees with conventional canonical quantization only if the parameter space is d=1 dimensional time. In d>1 quantization requires a fundamental length scale, and any bosonic field generates a spinorial wave function, leading to the purely quantum-theoretical emergence of spinors as a byproduct. We provide a probabilistic interpretation of the wave functions for the fields, and apply the formalism to a number of simple examples. These show that covariant canonical quantization produces both the Klein-Gordon and the Dirac equation, while also predicting the existence of discrete towers of identically charged fermions with different masses.
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
Progress on Nuclear Data Covariances: AFCI-1.2 Covariance Library
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
2009-09-28
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{sup -5} eV to 19.6 MeV. BNL contributed improved covariance data for the following materials: {sup 23}Na and {sup 55}Mn where more detailed evaluation was done; improvements in major structural materials {sup 52}Cr, {sup 56}Fe and {sup 58}Ni; improved estimates for remaining structural materials and fission products; improved covariances for 14 minor actinides, and estimates of mubar covariances for {sup 23}Na and {sup 56}Fe. LANL contributed improved covariance data for {sup 235}U and {sup 239}Pu including prompt neutron fission spectra and completely new evaluation for {sup 240}Pu. New R-matrix evaluation for {sup 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.
Phenotypic covariance at species’ borders
2013-01-01
Background 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. Results 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. Conclusions 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. PMID:23714580
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.
The covariate-adjusted frequency plot.
Holling, Heinz; Böhning, Walailuck; Böhning, Dankmar; Formann, Anton K
2016-04-01
Count data arise in numerous fields of interest. Analysis of these data frequently require distributional assumptions. Although the graphical display of a fitted model is straightforward in the univariate scenario, this becomes more complex if covariate information needs to be included into the model. Stratification is one way to proceed, but has its limitations if the covariate has many levels or the number of covariates is large. The article suggests a marginal method which works even in the case that all possible covariate combinations are different (i.e. no covariate combination occurs more than once). For each covariate combination the fitted model value is computed and then summed over the entire data set. The technique is quite general and works with all count distributional models as well as with all forms of covariate modelling. The article provides illustrations of the method for various situations and also shows that the proposed estimator as well as the empirical count frequency are consistent with respect to the same parameter.
Functional CLT for sample covariance matrices
Bai, Zhidong; Zhou, Wang; 10.3150/10-BEJ250
2010-01-01
Using Bernstein polynomial approximations, we prove the central limit theorem for linear spectral statistics of sample covariance matrices, indexed by a set of functions with continuous fourth order derivatives on an open interval including $[(1-\\sqrt{y})^2,(1+\\sqrt{y})^2]$, the support of the Mar\\u{c}enko--Pastur law. We also derive the explicit expressions for asymptotic mean and covariance functions.
Minazzoli, Olivier; Chauvineau, Bertrand
2011-04-01
In a recent paper (Minazzoli and Chauvineau 2009 Phys. Rev. D 79 084027), motivated by forthcoming space experiments involving propagation of light in the solar system, we have proposed an extension of the IAU metric equations at the c-4 level in general relativity. However, scalar-tensor theories may induce corrections numerically comparable to the c-4 general relativistic terms. Accordingly, one first proposes in this paper an extension of Minazzoli and Chauvineau (2009) to the scalar-tensor case. The case of a hierarchized system (such as the solar system) is emphasized. In this case, the relevant metric solution is proposed. Then, the corresponding isotropic geodesic solution relevant for distance measurements and time transfers in the inner solar system is given in explicit form.
Saltas, Ippocratis D
2016-01-01
We derive the 1-loop effective action of the cubic Galileon coupled to quantum-gravitational fluctuations in a background and gauge-independent manner, employing the covariant framework of DeWitt and Vilkovisky. Although the bare action respects shift symmetry, the coupling to gravity induces an effective mass to the scalar, of the order of the cosmological constant, as a direct result of the non-flat field-space metric, the latter ensuring the field-reparametrization invariance of the formalism. Within a gauge-invariant regularization scheme, we discover novel, gravitationally induced non-Galileon higher-derivative interactions in the effective action. These terms, previously unnoticed within standard, non-covariant frameworks, are not Planck suppressed. Unless tuned to be sub-dominant, their presence could have important implications for the classical and quantum phenomenology of the theory.
Covariant approximation averaging
Shintani, Eigo; Blum, Thomas; Izubuchi, Taku; Jung, Chulwoo; Lehner, Christoph
2014-01-01
We present a new class of statistical error reduction techniques for Monte-Carlo simulations. Using covariant symmetries, we show that correlation functions can be constructed from inexpensive approximations without introducing any systematic bias in the final result. We introduce a new class of covariant approximation averaging techniques, known as all-mode averaging (AMA), in which the approximation takes account of contributions of all eigenmodes through the inverse of the Dirac operator computed from the conjugate gradient method with a relaxed stopping condition. In this paper we compare the performance and computational cost of our new method with traditional methods using correlation functions and masses of the pion, nucleon, and vector meson in $N_f=2+1$ lattice QCD using domain-wall fermions. This comparison indicates that AMA significantly reduces statistical errors in Monte-Carlo calculations over conventional methods for the same cost.
Using Analysis of Covariance (ANCOVA) with Fallible Covariates
Culpepper, Steven Andrew; Aguinis, Herman
2011-01-01
Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which is the norm, researchers must choose from among 3 inadequate courses of action: (a) know that the assumption that covariates are perfectly reliable is violated but…
Using Analysis of Covariance (ANCOVA) with Fallible Covariates
Culpepper, Steven Andrew; Aguinis, Herman
2011-01-01
Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which is the norm, researchers must choose from among 3 inadequate courses of action: (a) know that the assumption that covariates are perfectly reliable is violated but…
Covariate analysis of bivariate survival data
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.
Kobel, Werner; Fegert, Ivana; Billington, Richard; Lewis, Richard; Bentley, Karin; Langrand-Lerche, Carole; Botham, Phil; Sato, Masako; Debruyne, Eric; Strupp, Christian; van Ravenzwaay, Bennard
2014-11-01
Over 400 active pesticides are registered in Japan (FAMIC 2013). The results of dog toxicity studies (usually, the 1-year study) were used by the Japanese regulatory authorities to establish the acceptable daily intake (ADI) for 45 pesticide active ingredients (about 9%). A retrospective review of ADIs established in Japan with dog studies as pivotal data for their derivation was performed: the ADIs were reassessed under the assumption that the 1-year dog study would not be available and an alternate ADI was derived based on the remaining toxicology database. In 35 of the 45 cases (77.8%) the ADI resulting from the absence of the 1-year dog study was no greater than twice the Japanese ADI, a difference considered not to be of biological significance. In 6 cases (13%) the resulting ADI was 2-5 times higher, which is considered of questionable biological relevance. On further evaluation of the database, three of these six cases were assessed as to clarify that there is no clear difference and for the other three additional studies to clarify that uncertain findings would have been required. In 3 of the 45 cases (7%) there may be a real difference within the ADI ratio of 2-5. Only in 1 case (2.2%) ADI was five times higher than that has been set. Accordingly, the absence of a 1-year dog study does not appear to influence the ADI derivation in a relevant manner in more than 98% of cases. For the four compounds with a real difference in ADI, consumer exposure would still be well below the alternative ADI. Therefore, a strong case can be made that the standard mandatory requirement to conduct a 1-year dog study, in addition to the 3-month study, is not justified and of no additional value in protecting human health. In addition, a substantial reduction in test animals could be achieved.
Covariant Magnetic Connection Hypersurfaces
Pegoraro, F
2016-01-01
In the single fluid, nonrelativistic, ideal-Magnetohydrodynamic (MHD) plasma description magnetic field lines play a fundamental role by defining dynamically preserved "magnetic connections" between plasma elements. Here we show how the concept of magnetic connection needs to be generalized in the case of a relativistic MHD description where we require covariance under arbitrary Lorentz transformations. This is performed by defining 2-D {\\it magnetic connection hypersurfaces} in the 4-D Minkowski space. This generalization accounts for the loss of simultaneity between spatially separated events in different frames and is expected to provide a powerful insight into the 4-D geometry of electromagnetic fields when ${\\bf E} \\cdot {\\bf B} = 0$.
Universality of Covariance Matrices
Pillai, Natesh S
2011-01-01
We prove the universality of covariance matrices of the form $H_{N \\times N} = {1 \\over N} \\tp{X}X$ where $[X]_{M \\times N}$ is a rectangular matrix with independent real valued entries $[x_{ij}]$ satisfying $\\E \\,x_{ij} = 0$ and $\\E \\,x^2_{ij} = {1 \\over M}$, $N, M\\to \\infty$. Furthermore it is assumed that these entries have sub-exponential tails. We will study the asymptotics in the regime $N/M = d_N \\in (0,\\infty), \\lim_{N\\to \\infty}d_N \
Covariant Projective Extensions
许天周; 梁洁
2003-01-01
@@ The theory of crossed products of C*-algebras by groups of automorphisms is a well-developed area of the theory of operator algebras. Given the importance and the success ofthat theory, it is natural to attempt to extend it to a more general situation by, for example,developing a theory of crossed products of C*-algebras by semigroups of automorphisms, or evenof endomorphisms. Indeed, in recent years a number of papers have appeared that are concernedwith such non-classicaltheories of covariance algebras, see, for instance [1-3].
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.
Andresen, Elisa, E-mail: Elisa.Andresen@uni-konstanz.de [University of Konstanz, Department of Biology, D-78457 Konstanz (Germany); Opitz, Judith, E-mail: Daniela.Opitz@uni-konstanz.de [University of Konstanz, Department of Biology, D-78457 Konstanz (Germany); Thomas, George, E-mail: George.Thomas@uni-konstanz.de [University of Konstanz, Department of Biology, D-78457 Konstanz (Germany); Stärk, Hans-Joachim, E-mail: Ha-Jo.Staerk@ufz.de [UFZ – Helmholtz Centre for Environmental Research, Department of Analytical Chemistry, Permoserstr. 15, D-04318 Leipzig (Germany); Dienemann, Holger, E-mail: Holger.Dienemann@smul.sachsen.de [Saxon State Company for Environment and Agriculture, Business Domain 5 (Laboratory), Department 53, Bitterfelder Str. 25, D-04849 Bad Düben (Germany); Jenemann, Kerstin, E-mail: Kerstin.Jenemann@smul.sachsen.de [Sächsisches Landesamt für Umwelt, Landwirtschaft und Geologie, Abteilung Wasser, Boden, Wertstoffe, Zur Wetterwarte 11, D-01109 Dresden (Germany); Dickinson, Bryan C., E-mail: Bryan.Dickinson@gmail.com [Harvard University, Department of Chemistry and Chemical Biology, 12 Oxford Street, Cambridge, MA 02138 (United States); Küpper, Hendrik, E-mail: Hendrik.Kuepper@uni-konstanz.de [University of Konstanz, Department of Biology, D-78457 Konstanz (Germany); University of South Bohemia, Faculty of Biological Sciences and Institute of Physical Biology, Branišovská 31, CZ-370 05 České Budejovice (Czech Republic)
2013-10-15
Highlights: •Hardly any macrophytic growth occurred in an oligotrophic hard water lake in Germany. •All parameters were optimal, besides elevated, nanomolar concentrations of Ni and Cd. •We cultivated submerged macrophytes in real and simulated hard and soft lake water. •Nanomolar Cd and Ni inhibited the plants’ photosynthetic light reactions in soft water. •The inhibition was synergistic, i.e. stronger than the addition of Cd and Ni effects. -- Abstract: Even essential trace elements are phytotoxic over a certain threshold. In this study, we investigated whether heavy metal concentrations were responsible for the nearly complete lack of submerged macrophytes in an oligotrophic lake in Germany. We cultivated the rootless aquatic model plant Ceratophyllum demersum under environmentally relevant conditions like sinusoidal light and temperature cycles and a low plant biomass to water volume ratio. Experiments lasted for six weeks and were analysed by detailed measurements of photosynthetic biophysics, pigment content and hydrogen peroxide production. We established that individually non-toxic cadmium (3 nM) and slightly toxic nickel (300 nM) concentrations became highly toxic when applied together in soft water, severely inhibiting photosynthetic light reactions. Toxicity was further enhanced by phosphate limitation (75 nM) in soft water as present in many freshwater habitats. In the investigated lake, however, high water hardness limited the toxicity of these metal concentrations, thus the inhibition of macrophytic growth in the lake must have additional reasons. The results showed that synergistic heavy metal toxicity may change ecosystems in many more cases than estimated so far.
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.
Bistra B Nankova
Full Text Available Alterations in gut microbiome composition have an emerging role in health and disease including brain function and behavior. Short chain fatty acids (SCFA like propionic (PPA, and butyric acid (BA, which are present in diet and are fermentation products of many gastrointestinal bacteria, are showing increasing importance in host health, but also may be environmental contributors in neurodevelopmental disorders including autism spectrum disorders (ASD. Further to this we have shown SCFA administration to rodents over a variety of routes (intracerebroventricular, subcutaneous, intraperitoneal or developmental time periods can elicit behavioral, electrophysiological, neuropathological and biochemical effects consistent with findings in ASD patients. SCFA are capable of altering host gene expression, partly due to their histone deacetylase inhibitor activity. We have previously shown BA can regulate tyrosine hydroxylase (TH mRNA levels in a PC12 cell model. Since monoamine concentration is known to be elevated in the brain and blood of ASD patients and in many ASD animal models, we hypothesized that SCFA may directly influence brain monoaminergic pathways. When PC12 cells were transiently transfected with plasmids having a luciferase reporter gene under the control of the TH promoter, PPA was found to induce reporter gene activity over a wide concentration range. CREB transcription factor(s was necessary for the transcriptional activation of TH gene by PPA. At lower concentrations PPA also caused accumulation of TH mRNA and protein, indicative of increased cell capacity to produce catecholamines. PPA and BA induced broad alterations in gene expression including neurotransmitter systems, neuronal cell adhesion molecules, inflammation, oxidative stress, lipid metabolism and mitochondrial function, all of which have been implicated in ASD. In conclusion, our data are consistent with a molecular mechanism through which gut related environmental signals
Hubeny, Veronika E
2014-01-01
A recently explored interesting quantity in AdS/CFT, dubbed 'residual entropy', characterizes the amount of collective ignorance associated with either boundary observers restricted to finite time duration, or bulk observers who lack access to a certain spacetime region. However, the previously-proposed expression for this quantity involving variation of boundary entanglement entropy (subsequently renamed to 'differential entropy') works only in a severely restrictive context. We explain the key limitations, arguing that in general, differential entropy does not correspond to residual entropy. Given that the concept of residual entropy as collective ignorance transcends these limitations, we identify two correspondingly robust, covariantly-defined constructs: a 'strip wedge' associated with boundary observers and a 'rim wedge' associated with bulk observers. These causal sets are well-defined in arbitrary time-dependent asymptotically AdS spacetimes in any number of dimensions. We discuss their relation, spec...
Covariant Macroscopic Quantum Geometry
Hogan, Craig J
2012-01-01
A covariant noncommutative algebra of position operators is presented, and interpreted as the macroscopic limit of a geometry that describes a collective quantum behavior of the positions of massive bodies in a flat emergent space-time. The commutator defines a quantum-geometrical relationship between world lines that depends on their separation and relative velocity, but on no other property of the bodies, and leads to a transverse uncertainty of the geometrical wave function that increases with separation. The number of geometrical degrees of freedom in a space-time volume scales holographically, as the surface area in Planck units. Ongoing branching of the wave function causes fluctuations in transverse position, shared coherently among bodies with similar trajectories. The theory can be tested using appropriately configured Michelson interferometers.
Saltas, Ippocratis D.; Vitagliano, Vincenzo
2017-05-01
We derive the 1-loop effective action of the cubic Galileon coupled to quantum-gravitational fluctuations in a background and gauge-independent manner, employing the covariant framework of DeWitt and Vilkovisky. Although the bare action respects shift symmetry, the coupling to gravity induces an effective mass to the scalar, of the order of the cosmological constant, as a direct result of the nonflat field-space metric, the latter ensuring the field-reparametrization invariance of the formalism. Within a gauge-invariant regularization scheme, we discover novel, gravitationally induced non-Galileon higher-derivative interactions in the effective action. These terms, previously unnoticed within standard, noncovariant frameworks, are not Planck suppressed. Unless tuned to be subdominant, their presence could have important implications for the classical and quantum phenomenology of the theory.
Covariant holographic entanglement negativity
Chaturvedi, Pankaj; Sengupta, Gautam
2016-01-01
We conjecture a holographic prescription for the covariant entanglement negativity of $d$-dimensional conformal field theories dual to non static bulk $AdS_{d+1}$ gravitational configurations in the framework of the $AdS/CFT$ correspondence. Application of our conjecture to a $AdS_3/CFT_2$ scenario involving bulk rotating BTZ black holes exactly reproduces the entanglement negativity of the corresponding $(1+1)$ dimensional conformal field theories and precisely captures the distillable quantum entanglement. Interestingly our conjecture for the scenario involving dual bulk extremal rotating BTZ black holes also accurately leads to the entanglement negativity for the chiral half of the corresponding $(1+1)$ dimensional conformal field theory at zero temperature.
Bayes linear covariance matrix adjustment
Wilkinson, Darren J
1995-01-01
In this thesis, a Bayes linear methodology for the adjustment of covariance matrices is presented and discussed. A geometric framework for quantifying uncertainties about covariance matrices is set up, and an inner-product for spaces of random matrices is motivated and constructed. The inner-product on this space captures aspects of our beliefs about the relationship between covariance matrices of interest to us, providing a structure rich enough for us to adjust beliefs about unknown matrices in the light of data such as sample covariance matrices, exploiting second-order exchangeability and related specifications to obtain representations allowing analysis. Adjustment is associated with orthogonal projection, and illustrated with examples of adjustments for some common problems. The problem of adjusting the covariance matrices underlying exchangeable random vectors is tackled and discussed. Learning about the covariance matrices associated with multivariate time series dynamic linear models is shown to be a...
Kisby, Glen; Palmer, Valerie; Lasarev, Mike; Fry, Rebecca; Iordanov, Mihail; Magun, Eli; Samson, Leona; Spencer, Peter
2011-11-01
Western Pacific amyotrophic lateral sclerosis (ALS) and parkinsonism-dementia complex (PDC), a prototypical neurodegenerative disease (tauopathy) affecting distinct genetic groups with common exposure to neurotoxic chemicals in cycad seed, has many features of Parkinson's and Alzheimer's diseases (AD), including early olfactory dysfunction. Guam ALS-PDC incidence correlates with cycad flour content of cycasin and its aglycone methylazoxymethanol (MAM), which produces persistent DNA damage (O(6)-methylguanine) in the brains of mice lacking O(6)-methylguanine methyltransferase (Mgmt(-/-)). We described in Mgmt(-/-)mice up to 7 days post-MAM treatment that brain DNA damage was linked to brain gene expression changes found in human neurological disease, cancer, and skin and hair development. This addendum reports 6 months post-MAM treatment- related brain transcriptional changes as well as elevated mitogen activated protein kinases and increased caspase-3 activity, both of which are involved in tau aggregation and neurofibrillary tangle formation typical of ALS-PDC and AD, plus transcriptional changes in olfactory receptors. Does cycasin act as a "slow (geno)toxin" in ALS-PDC?
Janes, Holly; Pepe, Margaret S
2009-06-01
Recent scientific and technological innovations have produced an abundance of potential markers that are being investigated for their use in disease screening and diagnosis. In evaluating these markers, it is often necessary to account for covariates associated with the marker of interest. Covariates may include subject characteristics, expertise of the test operator, test procedures or aspects of specimen handling. In this paper, we propose the covariate-adjusted receiver operating characteristic curve, a measure of covariate-adjusted classification accuracy. Nonparametric and semiparametric estimators are proposed, asymptotic distribution theory is provided and finite sample performance is investigated. For illustration we characterize the age-adjusted discriminatory accuracy of prostate-specific antigen as a biomarker for prostate cancer.
Nuclear data evaluation methodology including estimates of covariances
Smith D.L.
2010-10-01
Full Text Available Evaluated nuclear data rather than raw experimental and theoretical information are employed in nuclear applications such as the design of nuclear energy systems. Therefore, the process by which such information is produced and ultimately used is of critical interest to the nuclear science community. This paper provides an overview of various contemporary methods employed to generate evaluated cross sections and related physical quantities such as particle emission angular distributions and energy spectra. The emphasis here is on data associated with neutron induced reaction processes, with consideration of the uncertainties in these data, and on the more recent evaluation methods, e.g., those that are based on stochastic (Monte Carlo techniques. There is no unique way to perform such evaluations, nor are nuclear data evaluators united in their opinions as to which methods are superior to the others in various circumstances. In some cases it is not critical which approaches are used as long as there is consistency and proper use is made of the available physical information. However, in other instances there are definite advantages to using particular methods as opposed to other options. Some of these distinctions are discussed in this paper and suggestions are offered regarding fruitful areas for future research in the development of evaluation methodology.
Covariant Photon Quantization in the SME
Colladay, Don
2013-01-01
The Gupta Bleuler quantization procedure is applied to the SME photon sector. A direct application of the method to the massless case fails due to an unavoidable incompleteness in the polarization states. A mass term can be included into the photon lagrangian to rescue the quantization procedure and maintain covariance.
Covariate selection in multivariate spatial analysis of ovine parasitic infection.
Musella, V; Catelan, D; Rinaldi, L; Lagazio, C; Cringoli, G; Biggeri, A
2011-05-01
Gastrointestinal (GI) strongyle and fluke infections remain one of the main constraints on health and productivity in sheep dairy production. A cross-sectional survey was conducted in 2004-2005 on ovine farms in the Campania region of southern Italy in order to evaluate the prevalence of Haemonchus contortus, Fasciola hepatica, Dicrocoelium dendriticum and Calicophoron daubneyi from among other parasitic infections. In the present work, we focused on the role of the ecological characteristics of the pasture environment while accounting for the underlying long range geographical risk pattern. Bayesian multivariate spatial statistical analysis was used. A systematic grid (10 km×10 km) sampling approach was used. Laboratory procedures were based on the FLOTAC technique to detect and count eggs of helminths. A Geographical Information System (GIS) was constructed by using environmental data layers. Data on each of these layers were then extracted for pasturing areas that were previously digitalized aerial images of the ovine farms. Bayesian multivariate statistical analyses, including improper multivariate conditional autoregressive models, were used to select covariates on a multivariate spatially structured risk surface. Out of the 121 tested farms, 109 were positive for H. contortus, 81 for D. dendriticum, 17 for C. daubneyi and 15 for F. hepatica. The statistical analysis highlighted a north-south long range spatially structured pattern. This geographical pattern is treated here as a confounder, because the main interest was in the causal role of ecological covariates at the level of each pasturing area. A high percentage of pasture and impermeable soil were strong predictors of F. hepatica risk and a high percentage of wood was a strong predictor of C. daubneyi. A high percentage of wood, rocks and arable soil with sparse trees explained the spatial distribution of D. dendriticum. Sparse vegetation, river, mixed soil and permeable soil explained the spatial
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.
Subirà, Marta; Cano, Marta; de Wit, Stella J.; Alonso, Pino; Cardoner, Narcís; Hoexter, Marcelo Q.; Kwon, Jun Soo; Nakamae, Takashi; Lochner, Christine; Sato, João R.; Jung, Wi Hoon; Narumoto, Jin; Stein, Dan J.; Pujol, Jesus; Mataix-Cols, David; Veltman, Dick J.; Menchón, José M.; van den Heuvel, Odile A.; Soriano-Mas, Carles
2016-01-01
Background Frontostriatal and frontoamygdalar connectivity alterations in patients with obsessive–compulsive disorder (OCD) have been typically described in functional neuroimaging studies. However, structural covariance, or volumetric correlations across distant brain regions, also provides network-level information. Altered structural covariance has been described in patients with different psychiatric disorders, including OCD, but to our knowledge, alterations within frontostriatal and frontoamygdalar circuits have not been explored. Methods We performed a mega-analysis pooling structural MRI scans from the Obsessive–compulsive Brain Imaging Consortium and assessed whole-brain voxel-wise structural covariance of 4 striatal regions (dorsal and ventral caudate nucleus, and dorsal-caudal and ventral-rostral putamen) and 2 amygdalar nuclei (basolateral and centromedial-superficial). Images were preprocessed with the standard pipeline of voxel-based morphometry studies using Statistical Parametric Mapping software. Results Our analyses involved 329 patients with OCD and 316 healthy controls. Patients showed increased structural covariance between the left ventral-rostral putamen and the left inferior frontal gyrus/frontal operculum region. This finding had a significant interaction with age; the association held only in the subgroup of older participants. Patients with OCD also showed increased structural covariance between the right centromedial-superficial amygdala and the ventromedial prefrontal cortex. Limitations This was a cross-sectional study. Because this is a multisite data set analysis, participant recruitment and image acquisition were performed in different centres. Most patients were taking medication, and treatment protocols differed across centres. Conclusion Our results provide evidence for structural network–level alterations in patients with OCD involving 2 frontosubcortical circuits of relevance for the disorder and indicate that structural
General covariance in computational electrodynamics
Shyroki, Dzmitry; Lægsgaard, Jesper; Bang, Ole;
2007-01-01
We advocate the generally covariant formulation of Maxwell equations as underpinning some recent advances in computational electrodynamics—in the dimensionality reduction for separable structures; in mesh truncation for finite-difference computations; and in adaptive coordinate mapping as opposed...
Covariant Quantum Gravity with Continuous Quantum Geometry I: Covariant Hamiltonian Framework
Pilc, Marián
2016-01-01
The first part of the series is devoted to the formulation of the Einstein-Cartan Theory within the covariant hamiltonian framework. In the first section the general multisymplectic approach is revised and the notion of the d-jet bundles is introduced. Since the whole Standard Model Lagrangian (including gravity) can be written as the functional of the forms, the structure of the d-jet bundles is more appropriate for the covariant hamiltonian analysis than the standard jet bundle approach. The definition of the local covariant Poisson bracket on the space of covariant observables is recalled. The main goal of the work is to show that the gauge group of the Einstein-Cartan theory is given by the semidirect product of the local Lorentz group and the group of spacetime diffeomorphisms. Vanishing of the integral generators of the gauge group is equivalent to equations of motion of the Einstein-Cartan theory and the local covariant algebra generated by Noether's currents is closed Lie algebra.
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.
Covariates of Craving in Actively Drinking Alcoholics
Chakravorty, Subhajit; Kuna, Samuel T.; Zaharakis, Nikola; O’Brien, Charles P.; Kampman, Kyle M.; Oslin, David
2010-01-01
The goal of this cross-sectional study was to assess the relationship of alcohol craving with biopsychosocial and addiction factors that are clinically pertinent to alcoholism treatment. Alcohol craving was assessed in 315 treatment-seeking, alcohol dependent subjects using the PACS questionnaire. Standard validated questionnaires were used to evaluate a variety of biological, addiction, psychological, psychiatric, and social factors. Individual covariates of craving included age, race, probl...
Calcul Stochastique Covariant à Sauts & Calcul Stochastique à Sauts Covariants
Maillard-Teyssier, Laurence
2003-01-01
We propose a stochastic covariant calculus forcàdlàg semimartingales in the tangent bundle $TM$ over a manifold $M$. A connection on $M$ allows us to define an intrinsic derivative ofa $C^1$ curve $(Y_t)$ in $TM$, the covariantderivative. More precisely, it is the derivative of$(Y_t)$ seen in a frame moving parallelly along its projection curve$(x_t)$ on $M$. With the transfer principle, Norris defined thestochastic covariant integration along a continuous semimartingale in$TM$. We describe t...
Covariate-free and Covariate-dependent Reliability.
Bentler, Peter M
2016-12-01
Classical test theory reliability coefficients are said to be population specific. Reliability generalization, a meta-analysis method, is the main procedure for evaluating the stability of reliability coefficients across populations. A new approach is developed to evaluate the degree of invariance of reliability coefficients to population characteristics. Factor or common variance of a reliability measure is partitioned into parts that are, and are not, influenced by control variables, resulting in a partition of reliability into a covariate-dependent and a covariate-free part. The approach can be implemented in a single sample and can be applied to a variety of reliability coefficients.
Levy Matrices and Financial Covariances
Burda, Zdzislaw; Jurkiewicz, Jerzy; Nowak, Maciej A.; Papp, Gabor; Zahed, Ismail
2003-10-01
In a given market, financial covariances capture the intra-stock correlations and can be used to address statistically the bulk nature of the market as a complex system. We provide a statistical analysis of three SP500 covariances with evidence for raw tail distributions. We study the stability of these tails against reshuffling for the SP500 data and show that the covariance with the strongest tails is robust, with a spectral density in remarkable agreement with random Lévy matrix theory. We study the inverse participation ratio for the three covariances. The strong localization observed at both ends of the spectral density is analogous to the localization exhibited in the random Lévy matrix ensemble. We discuss two competitive mechanisms responsible for the occurrence of an extensive and delocalized eigenvalue at the edge of the spectrum: (a) the Lévy character of the entries of the correlation matrix and (b) a sort of off-diagonal order induced by underlying inter-stock correlations. (b) can be destroyed by reshuffling, while (a) cannot. We show that the stocks with the largest scattering are the least susceptible to correlations, and likely candidates for the localized states. We introduce a simple model for price fluctuations which captures behavior of the SP500 covariances. It may be of importance for assets diversification.
The Performance Analysis Based on SAR Sample Covariance Matrix
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.
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.
Szekeres models: a covariant approach
Apostolopoulos, Pantelis S
2016-01-01
We exploit the 1+1+2 formalism to covariantly describe the inhomogeneous and anisotropic Szekeres models. It is shown that an \\emph{average scale length} can be defined \\emph{covariantly} which satisfies a 2d equation of motion driven from the \\emph{effective gravitational mass} (EGM) contained in the dust cloud. The contributions to the EGM are encoded to the energy density of the dust fluid and the free gravitational field $E_{ab}$. In addition the notions of the Apparent and Absolute Apparent Horizons are briefly discussed and we give an alternative gauge-invariant form to define them in terms of the kinematical variables of the spacelike congruences. We argue that the proposed program can be used in order to express the Sachs optical equations in a covariant form and analyze the confrontation of a spatially inhomogeneous irrotational overdense fluid model with the observational data.
Cosmic Censorship Conjecture revisited: Covariantly
Hamid, Aymen I M; 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.
Graviton Loop Corrections to Vacuum Polarization in de Sitter in a General Covariant Gauge
Glavan, D; Prokopec, Tomislav; Woodard, R P
2015-01-01
We evaluate the one-graviton loop contribution to the vacuum polarization on de Sitter background in a 1-parameter family of exact, de Sitter invariant gauges. Our result is computed using dimensional regularization and fully renormalized with BPHZ counterterms, which must include a noninvariant owing to the time-ordered interactions. Because the graviton propagator engenders a physical breaking of de Sitter invariance two structure functions are needed to express the result. In addition to its relevance for the gauge issue this is the first time a covariant gauge graviton propagator has been used to compute a noncoincident loop. A number of identities are derived which should facilitate further graviton loop computations.
Covariant description of isothermic surfaces
Tafel, Jacek
2014-01-01
We present a covariant formulation of the Gauss-Weingarten equations and the Gauss-Mainardi-Codazzi equations for surfaces in 3-dimensional curved spaces. We derive a coordinate invariant condition on the first and second fundamental form which is necessary and sufficient for the surface to be isothermic.
Covariation Neglect among Novice Investors
Hedesstrom, Ted Martin; Svedsater, Henrik; Garling, Tommy
2006-01-01
In 4 experiments, undergraduates made hypothetical investment choices. In Experiment 1, participants paid more attention to the volatility of individual assets than to the volatility of aggregated portfolios. The results of Experiment 2 show that most participants diversified even when this increased risk because of covariation between the returns…
Covariant Formulations of Superstring Theories.
Mikovic, Aleksandar Radomir
1990-01-01
Chapter 1 contains a brief introduction to the subject of string theory, and tries to motivate the study of superstrings and covariant formulations. Chapter 2 describes the Green-Schwarz formulation of the superstrings. The Hamiltonian and BRST structure of the theory is analysed in the case of the superparticle. Implications for the superstring case are discussed. Chapter 3 describes the Siegel's formulation of the superstring, which contains only the first class constraints. It is shown that the physical spectrum coincides with that of the Green-Schwarz formulation. In chapter 4 we analyse the BRST structure of the Siegel's formulation. We show that the BRST charge has the wrong cohomology, and propose a modification, called first ilk, which gives the right cohomology. We also propose another superparticle model, called second ilk, which has infinitely many coordinates and constraints. We construct the complete BRST charge for it, and show that it gives the correct cohomology. In chapter 5 we analyse the properties of the covariant vertex operators and the corresponding S-matrix elements by using the Siegel's formulation. We conclude that the knowledge of the ghosts is necessary, even at the tree level, in order to obtain the correct S-matrix. In chapter 6 we attempt to calculate the superstring loops, in a covariant gauge. We calculate the vacuum-to -vacuum amplitude, which is also the cosmological constant. We show that it vanishes to all loop orders, under the assumption that the free covariant gauge-fixed action exists. In chapter 7 we present our conclusions, and briefly discuss the random lattice approach to the string theory, as a possible way of resolving the problem of the covariant quantization and the nonperturbative definition of the superstrings.
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.
Flavour Covariant Transport Equations: an Application to Resonant Leptogenesis
Dev, P S Bhupal; Pilaftsis, Apostolos; Teresi, Daniele
2014-01-01
We present a fully flavour-covariant formalism for transport phenomena, by deriving Markovian master equations that describe the time-evolution of particle number densities in a statistical ensemble with arbitrary flavour content. As an application of this general formalism, we study flavour effects in a scenario of resonant leptogenesis (RL) and obtain the flavour-covariant evolution equations for heavy-neutrino and lepton number densities. This provides a complete and unified description of RL, capturing three relevant physical phenomena: (i) the resonant mixing between the heavy-neutrino states, (ii) coherent oscillations between different heavy-neutrino flavours, and (iii) quantum decoherence effects in the charged-lepton sector. To illustrate the importance of this formalism, we numerically solve the flavour-covariant rate equations for a minimal RL model and show that the total lepton asymmetry can be enhanced up to one order of magnitude, as compared to that obtained from flavour-diagonal or partially ...
Structural covariance of the neostriatum with regional gray matter volumes.
Soriano-Mas, C; Harrison, B J; Pujol, J; López-Solà, M; Hernández-Ribas, R; Alonso, P; Contreras-Rodríguez, O; Giménez, M; Blanco-Hinojo, L; Ortiz, H; Deus, J; Menchón, J M; Cardoner, N
2013-05-01
The caudate and putamen nuclei have been traditionally divided into dorsal and ventral territories based on their segregated patterns of functional and anatomical connectivity with distributed cortical regions. Activity-dependent structural plasticity may potentially lead to the development of regional volume correlations, or structural covariance, between the different components of each cortico-striatal circuit. Here, we studied the whole-brain structural covariance patterns of four neostriatal regions belonging to distinct cortico-striatal circuits. We also assessed the potential modulating influence of laterality, age and gender. T1-weighted three-dimensional magnetic resonance images were obtained from ninety healthy participants (50 females). Following data pre-processing, the mean signal value per hemisphere was calculated for the 'seed' regions of interest, located in the dorsal and ventral caudate and the dorsal-caudal and ventral-rostral putamen. Statistical parametric mapping was used to estimate whole-brain voxel-wise structural covariance patterns for each striatal region, controlling for the shared anatomical variance between regions in order to obtain maximally specific structural covariance patterns. As predicted, segregated covariance patterns were observed. Age was found to be a relevant modulator of the covariance patterns of the right caudate regions, while laterality effects were observed for the dorsal-caudal putamen. Gender effects were only observed via an interaction with age. The different patterns of structural covariance are discussed in detail, as well as their similarities with the functional and anatomical connectivity patterns reported for the same striatal regions in other studies. Finally, the potential mechanisms underpinning the phenomenon of volume correlations between distant cortico-striatal structures are also discussed.
Bayesian adjustment for covariate measurement errors: a flexible parametric approach.
Hossain, Shahadut; Gustafson, Paul
2009-05-15
In most epidemiological investigations, the study units are people, the outcome variable (or the response) is a health-related event, and the explanatory variables are usually environmental and/or socio-demographic factors. The fundamental task in such investigations is to quantify the association between the explanatory variables (covariates/exposures) and the outcome variable through a suitable regression model. The accuracy of such quantification depends on how precisely the relevant covariates are measured. In many instances, we cannot measure some of the covariates accurately. Rather, we can measure noisy (mismeasured) versions of them. In statistical terminology, mismeasurement in continuous covariates is known as measurement errors or errors-in-variables. Regression analyses based on mismeasured covariates lead to biased inference about the true underlying response-covariate associations. In this paper, we suggest a flexible parametric approach for avoiding this bias when estimating the response-covariate relationship through a logistic regression model. More specifically, we consider the flexible generalized skew-normal and the flexible generalized skew-t distributions for modeling the unobserved true exposure. For inference and computational purposes, we use Bayesian Markov chain Monte Carlo techniques. We investigate the performance of the proposed flexible parametric approach in comparison with a common flexible parametric approach through extensive simulation studies. We also compare the proposed method with the competing flexible parametric method on a real-life data set. Though emphasis is put on the logistic regression model, the proposed method is unified and is applicable to the other generalized linear models, and to other types of non-linear regression models as well. (c) 2009 John Wiley & Sons, Ltd.
Computational protein design quantifies structural constraints on amino acid covariation.
Noah Ollikainen
Full Text Available Amino acid covariation, where the identities of amino acids at different sequence positions are correlated, is a hallmark of naturally occurring proteins. This covariation can arise from multiple factors, including selective pressures for maintaining protein structure, requirements imposed by a specific function, or from phylogenetic sampling bias. Here we employed flexible backbone computational protein design to quantify the extent to which protein structure has constrained amino acid covariation for 40 diverse protein domains. We find significant similarities between the amino acid covariation in alignments of natural protein sequences and sequences optimized for their structures by computational protein design methods. These results indicate that the structural constraints imposed by protein architecture play a dominant role in shaping amino acid covariation and that computational protein design methods can capture these effects. We also find that the similarity between natural and designed covariation is sensitive to the magnitude and mechanism of backbone flexibility used in computational protein design. Our results thus highlight the necessity of including backbone flexibility to correctly model precise details of correlated amino acid changes and give insights into the pressures underlying these correlations.
Discrete Symmetries in Covariant LQG
Rovelli, Carlo
2012-01-01
We study time-reversal and parity ---on the physical manifold and in internal space--- in covariant loop gravity. We consider a minor modification of the Holst action which makes it transform coherently under such transformations. The classical theory is not affected but the quantum theory is slightly different. In particular, the simplicity constraints are slightly modified and this restricts orientation flips in a spinfoam to occur only across degenerate regions, thus reducing the sources of potential divergences.
Competing risks and time-dependent covariates
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...
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 ℓ1 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.
Shrinkage covariance matrix approach for microarray data
Karjanto, Suryaefiza; Aripin, Rasimah
2013-04-01
Microarray technology was developed for the purpose of monitoring the expression levels of thousands of genes. A microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints including the high cost of producing microarray chips. As a result, the widely used standard covariance estimator is not appropriate for this purpose. One such technique is the Hotelling's T2 statistic which is a multivariate test statistic for comparing means between two groups. It requires that the number of observations (n) exceeds the number of genes (p) in the set but in microarray studies it is common that n Hotelling's T2 statistic with the shrinkage approach is proposed to estimate the covariance matrix for testing differential gene expression. The performance of this approach is then compared with other commonly used multivariate tests using a widely analysed diabetes data set as illustrations. The results across the methods are consistent, implying that this approach provides an alternative to existing techniques.
ISSUES IN NEUTRON CROSS SECTION COVARIANCES
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.
Parameter inference with estimated covariance matrices
Sellentin, Elena
2015-01-01
When inferring parameters from a Gaussian-distributed data set by computing a likelihood, a covariance matrix is needed that describes the data errors and their correlations. If the covariance matrix is not known a priori, it may be estimated and thereby becomes a random object with some intrinsic uncertainty itself. We show how to infer parameters in the presence of such an estimated covariance matrix, by marginalising over the true covariance matrix, conditioned on its estimated value. This leads to a likelihood function that is no longer Gaussian, but rather an adapted version of a multivariate $t$-distribution, which has the same numerical complexity as the multivariate Gaussian. As expected, marginalisation over the true covariance matrix improves inference when compared with Hartlap et al.'s method, which uses an unbiased estimate of the inverse covariance matrix but still assumes that the likelihood is Gaussian.
ISSUES IN NEUTRON CROSS SECTION COVARIANCES
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.
Eigenvalue variance bounds for covariance matrices
Dallaporta, Sandrine
2013-01-01
This work is concerned with finite range bounds on the variance of individual eigenvalues of random covariance matrices, both in the bulk and at the edge of the spectrum. In a preceding paper, the author established analogous results for Wigner matrices and stated the results for covariance matrices. They are proved in the present paper. Relying on the LUE example, which needs to be investigated first, the main bounds are extended to complex covariance matrices by means of the Tao, Vu and Wan...
Covariate-adjusted confidence interval for the intraclass correlation coefficient.
Shoukri, Mohamed M; Donner, Allan; El-Dali, Abdelmoneim
2013-09-01
A crucial step in designing a new study is to estimate the required sample size. For a design involving cluster sampling, the appropriate sample size depends on the so-called design effect, which is a function of the average cluster size and the intracluster correlation coefficient (ICC). It is well-known that under the framework of hierarchical and generalized linear models, a reduction in residual error may be achieved by including risk factors as covariates. In this paper we show that the covariate design, indicating whether the covariates are measured at the cluster level or at the within-cluster subject level affects the estimation of the ICC, and hence the design effect. Therefore, the distinction between these two types of covariates should be made at the design stage. In this paper we use the nested-bootstrap method to assess the accuracy of the estimated ICC for continuous and binary response variables under different covariate structures. The codes of two SAS macros are made available by the authors for interested readers to facilitate the construction of confidence intervals for the ICC. Moreover, using Monte Carlo simulations we evaluate the relative efficiency of the estimators and evaluate the accuracy of the coverage probabilities of a 95% confidence interval on the population ICC. The methodology is illustrated using a published data set of blood pressure measurements taken on family members.
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.
Newton law in covariant unimodular F(R) gravity
Nojiri, S.; Odintsov, S. D.; Oikonomou, V. K.
2016-09-01
We investigate the Newton law in the unimodular F(R) gravity. In the standard F(R) gravity, due to the extra scalar mode, there often appear the large corrections to the Newton law and such models are excluded by the experiments and/or the observations. In the unimodular F(R) gravity, however, the extra scalar mode become not to be dynamical due to the unimodular constraint and there is not any correction to the Newton law. Even in the unimodular Einstein gravity, the Newton law is reproduced but the mechanism is a little bit different from that in the unimodular F(R) gravity. We also investigate the unimodular F(R) gravity in the covariant formulation. In the covariant formulation, we include the three-form field. We show that the three-form field could not have any unwanted property, like ghost nor correction to the Newton law. In the covariant formulation, however, the above extra scalar mode becomes dynamical and could give a correction to the Newton law. We also show that there are no difference in the Friedmann-Robertson-Walker (FRW) dynamics in the non-covariant and covariant formulation.
EMPIRE ULTIMATE EXPANSION: RESONANCES AND COVARIANCES.
HERMAN,M.; MUGHABGHAB, S.F.; OBLOZINSKY, P.; ROCHMAN, D.; PIGNI, M.T.; KAWANO, T.; CAPOTE, R.; ZERKIN, V.; TRKOV, A.; SIN, M.; CARSON, B.V.; WIENKE, H. CHO, Y.-S.
2007-04-22
The EMPIRE code system is being extended to cover the resolved and unresolved resonance region employing proven methodology used for the production of new evaluations in the recent Atlas of Neutron Resonances. Another directions of Empire expansion are uncertainties and correlations among them. These include covariances for cross sections as well as for model parameters. In this presentation we concentrate on the KALMAN method that has been applied in EMPIRE to the fast neutron range as well as to the resonance region. We also summarize role of the EMPIRE code in the ENDF/B-VII.0 development. Finally, large scale calculations and their impact on nuclear model parameters are discussed along with the exciting perspectives offered by the parallel supercomputing.
Baryon Spectrum Analysis using Covariant Constraint Dynamics
Whitney, Joshua; Crater, Horace
2012-03-01
The energy spectrum of the baryons is determined by treating each of them as a three-body system with the interacting forces coming from a set of two-body potentials that depend on both the distance between the quarks and the spin and orbital angular momentum coupling terms. The Two Body Dirac equations of constraint dynamics derived by Crater and Van Alstine, matched with the quasipotential formalism of Todorov as the underlying two-body formalism are used, as well as the three-body constraint formalism of Sazdjian to integrate the three two-body equations into a single relativistically covariant three body equation for the bound state energies. The results are analyzed and compared to experiment using a best fit method and several different algorithms, including a gradient approach, and Monte Carlo method. Results for all well-known baryons are presented and compared to experiment, with good accuracy.
Universal Gravitation as Lorentz-covariant Dynamics
Kauffmann, Steven Kenneth
2014-01-01
Einstein's equivalence principle implies that the acceleration of a particle in a "specified" gravitational field is independent of its mass. While this is certainly true to great accuracy for bodies we observe in the Earth's gravitational field, a hypothetical body of mass comparable to the Earth's would perceptibly cause the Earth to fall toward it, which would feed back into the strength as a function of time of the Earth's gravitational field affecting that body. In short, Einstein's equivalence principle isn't exact, but is an approximation that ignores recoil of the "specified" gravitational field, which sheds light on why general relativity has no clearly delineated native embodiment of conserved four-momentum. Einstein's 1905 relativity of course doesn't have the inexactitudes he unwittingly built into GR, so it is natural to explore a Lorentz-covariant gravitational theory patterned directly on electromagnetism, wherein a system's zero-divergence overall stress-energy, including all gravitational fee...
A scale invariant covariance structure on jet space
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 part...... of the derivation, we introduce a blurring operator At that acts on jet space contrary to doing spatial filtering and a scaling operator Ss. The stochastic Brownian image model is an example of a class of functions which are scale invariant with respect to the operators At and Ss. This paper also includes empirical...
Covariant Description of Transformation Optics in Linear and Nonlinear Media
Paul, Oliver
2011-01-01
The technique of transformation optics (TO) is an elegant method for the design of electromagnetic media with tailored optical properties. In this paper, we focus on the formal structure of TO theory. By using a complete covariant formalism, we present a general transformation law that holds for arbitrary materials including bianisotropic, magneto-optical, nonlinear and moving media. Due to the principle of general covariance, the formalism is applicable to arbitrary space-time coordinate transformations and automatically accounts for magneto-electric coupling terms. The formalism is demonstrated for the calculation of the second harmonic generation in a twisted TO concentrator.
Full covariance of CMB and lensing reconstruction power spectra
Peloton, Julien; Lewis, Antony; Carron, Julien; Zahn, Oliver
2016-01-01
CMB and lensing reconstruction power spectra are powerful probes of cosmology. However they are correlated, since the CMB power spectra are lensed and the lensing reconstruction is constructed using CMB multipoles. We perform a full analysis of the auto- and cross-covariances, including polarization power spectra and minimum variance lensing estimators, and compare with simulations of idealized future CMB-S4 observations. Covariances sourced by fluctuations in the unlensed CMB and instrumental noise can largely be removed by using a realization-dependent subtraction of lensing reconstruction noise, leaving a relatively simple covariance model that is dominated by lensing-induced terms and well described by a small number of principal components. The correlations between the CMB and lensing power spectra will be detectable at the level of $\\sim 5\\sigma$ for a CMB-S4 mission, and neglecting those could underestimate some parameter error bars by several tens of percent. However we found that the inclusion of ext...
Femtosecond Studies Of Coulomb Explosion Utilizing Covariance Mapping
Card, D A
2000-01-01
The studies presented herein elucidate details of the Coulomb explosion event initiated through the interaction of molecular clusters with an intense femtosecond laser beam (≥1 PW/cm2). Clusters studied include ammonia, titanium-hydrocarbon, pyridine, and 7-azaindole. Covariance analysis is presented as a general technique to study the dynamical processes in clusters and to discern whether the fragmentation channels are competitive. Positive covariance determinations identify concerted processes such as the concomitant explosion of protonated cluster ions of asymmetrical size. Anti- covariance mapping is exploited to distinguish competitive reaction channels such as the production of highly charged nitrogen atoms formed at the expense of the protonated members of a cluster ion ensemble. This technique is exemplified in each cluster system studied. Kinetic energy analyses, from experiment and simulation, are presented to fully understand the Coulomb explosion event. A cutoff study strongly suggests that...
Data Covariances from R-Matrix Analyses of Light Nuclei
Hale, G.M., E-mail: ghale@lanl.gov; Paris, M.W.
2015-01-15
After first reviewing the parametric description of light-element reactions in multichannel systems using R-matrix theory and features of the general LANL R-matrix analysis code EDA, we describe how its chi-square minimization procedure gives parameter covariances. This information is used, together with analytically calculated sensitivity derivatives, to obtain cross section covariances for all reactions included in the analysis by first-order error propagation. Examples are given of the covariances obtained for systems with few resonances ({sup 5}He) and with many resonances ({sup 13}C ). We discuss the prevalent problem of this method leading to cross section uncertainty estimates that are unreasonably small for large data sets. The answer to this problem appears to be using parameter confidence intervals in place of standard errors.
Spike Triggered Covariance in Strongly Correlated Gaussian Stimuli
Aljadeff, Johnatan; Segev, Ronen; Berry, Michael J.; Sharpee, Tatyana O.
2013-01-01
Many biological systems perform computations on inputs that have very large dimensionality. Determining the relevant input combinations for a particular computation is often key to understanding its function. A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs. In systems neuroscience, the corresponding method is known as spike-triggered covariance (STC). This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems. So far, most studies used the STC method with weakly correlated Gaussian inputs. However, it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment. In such cases, the stimulus covariance matrix has one (or more) outstanding eigenvalues that cannot be easily equalized because of sampling variability. Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs. In many cases, these modes obscure the significant dimensions. We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more. This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode(s). Analyzing the responses of retinal ganglion cells probed with Gaussian noise, we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons. PMID:24039563
Spike triggered covariance in strongly correlated gaussian stimuli.
Johnatan Aljadeff
Full Text Available Many biological systems perform computations on inputs that have very large dimensionality. Determining the relevant input combinations for a particular computation is often key to understanding its function. A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs. In systems neuroscience, the corresponding method is known as spike-triggered covariance (STC. This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems. So far, most studies used the STC method with weakly correlated Gaussian inputs. However, it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment. In such cases, the stimulus covariance matrix has one (or more outstanding eigenvalues that cannot be easily equalized because of sampling variability. Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs. In many cases, these modes obscure the significant dimensions. We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more. This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode(s. Analyzing the responses of retinal ganglion cells probed with [Formula: see text] Gaussian noise, we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons.
Modeling corporate defaults: Poisson autoregressions with exogenous covariates (PARX)
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...
Kinnebrock, Silja; Podolskij, Mark
This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...... and covariance, for which we obtain the optimal rate of convergence. We demonstrate some positive semidefinite estimators of the covariation and construct a positive semidefinite estimator of the conditional covariance matrix in the central limit theorem. Furthermore, we indicate how the assumptions on the noise...
Kinnebrock, Silja; Podolskij, Mark
and covariance, for which we obtain the optimal rate of convergence. We demonstrate some positive semidefinite estimators of the covariation and construct a positive semidefinite estimator of the conditional covariance matrix in the central limit theorem. Furthermore, we indicate how the assumptions on the noise......This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...
Covariance structure models of expectancy.
Henderson, M J; Goldman, M S; Coovert, M D; Carnevalla, N
1994-05-01
Antecedent variables under the broad categories of genetic, environmental and cultural influences have been linked to the risk for alcohol abuse. Such risk factors have not been shown to result in high correlations with alcohol consumption and leave unclear an understanding of the mechanism by which these variables lead to increased risk. This study employed covariance structure modeling to examine the mediational influence of stored information in memory about alcohol, alcohol expectancies in relation to two biologically and environmentally driven antecedent variables, family history of alcohol abuse and a sensation-seeking temperament in a college population. We also examined the effect of criterion contamination on the relationship between sensation-seeking and alcohol consumption. Results indicated that alcohol expectancy acts as a significant, partial mediator of the relationship between sensation-seeking and consumption, that family history of alcohol abuse is not related to drinking outcome and that overlap in items on sensation-seeking and alcohol consumption measures may falsely inflate their relationship.
On the Origin of Gravitational Lorentz Covariance
Khoury, Justin; Tolley, Andrew J
2013-01-01
We provide evidence that general relativity is the unique spatially covariant effective field theory of the transverse, traceless graviton degrees of freedom. The Lorentz covariance of general relativity, having not been assumed in our analysis, is thus plausibly interpreted as an accidental or emergent symmetry of the gravitational sector.
Neutron Cross Section Covariances for Structural Materials and Fission Products
Hoblit, S.; Cho, Y.-S.; Herman, M.; Mattoon, C. M.; Mughabghab, S. F.; Obložinský, P.; Pigni, M. T.; Sonzogni, A. A.
2011-12-01
We describe neutron cross section covariances for 78 structural materials and fission products produced for the new US evaluated nuclear reaction library ENDF/B-VII.1. Neutron incident energies cover full range from 10 eV to 20 MeV and covariances are primarily provided for capture, elastic and inelastic scattering as well as (n,2n). The list of materials follows priorities defined by the Advanced Fuel Cycle Initiative, the major application being data adjustment for advanced fast reactor systems. Thus, in addition to 28 structural materials and 49 fission products, the list includes also 23Na which is important fast reactor coolant. Due to extensive amount of materials, we adopted a variety of methodologies depending on the priority of a specific material. In the resolved resonance region we primarily used resonance parameter uncertainties given in Atlas of Neutron Resonances and either applied the kernel approximation to propagate these uncertainties into cross section uncertainties or resorted to simplified estimates based on integral quantities. For several priority materials we adopted MF32 covariances produced by SAMMY at ORNL, modified by us by adding MF33 covariances to account for systematic uncertainties. In the fast neutron region we resorted to three methods. The most sophisticated was EMPIRE-KALMAN method which combines experimental data from EXFOR library with nuclear reaction modeling and least-squares fitting. The two other methods used simplified estimates, either based on the propagation of nuclear reaction model parameter uncertainties or on a dispersion analysis of central cross section values in recent evaluated data files. All covariances were subject to quality assurance procedures adopted recently by CSEWG. In addition, tools were developed to allow inspection of processed covariances and computed integral quantities, and for comparing these values to data from the Atlas and the astrophysics database KADoNiS.
Neutron Cross Section Covariances for Structural Materials and Fission Products
Hoblit, S.; Hoblit,S.; Cho,Y.-S.; Herman,M.; Mattoon,C.M.; Mughabghab,S.F.; Oblozinsky,P.; Pigni,M.T.; Sonzogni,A.A.
2011-12-01
We describe neutron cross section covariances for 78 structural materials and fission products produced for the new US evaluated nuclear reaction library ENDF/B-VII.1. Neutron incident energies cover full range from 10{sup -5} eV to 20 MeV and covariances are primarily provided for capture, elastic and inelastic scattering as well as (n,2n). The list of materials follows priorities defined by the Advanced Fuel Cycle Initiative, the major application being data adjustment for advanced fast reactor systems. Thus, in addition to 28 structural materials and 49 fission products, the list includes also {sup 23}Na which is important fast reactor coolant. Due to extensive amount of materials, we adopted a variety of methodologies depending on the priority of a specific material. In the resolved resonance region we primarily used resonance parameter uncertainties given in Atlas of Neutron Resonances and either applied the kernel approximation to propagate these uncertainties into cross section uncertainties or resorted to simplified estimates based on integral quantities. For several priority materials we adopted MF32 covariances produced by SAMMY at ORNL, modified by us by adding MF33 covariances to account for systematic uncertainties. In the fast neutron region we resorted to three methods. The most sophisticated was EMPIRE-KALMAN method which combines experimental data from EXFOR library with nuclear reaction modeling and least-squares fitting. The two other methods used simplified estimates, either based on the propagation of nuclear reaction model parameter uncertainties or on a dispersion analysis of central cross section values in recent evaluated data files. All covariances were subject to quality assurance procedures adopted recently by CSEWG. In addition, tools were developed to allow inspection of processed covariances and computed integral quantities, and for comparing these values to data from the Atlas and the astrophysics database KADoNiS.
Safarkhani, Maryam; Moerbeek, Mirjam
2013-01-01
In a randomized controlled trial, a decision needs to be made about the total number of subjects for adequate statistical power. One way to increase the power of a trial is by including a predictive covariate in the model. In this article, the effects of various covariate adjustment strategies on increasing the power is studied for discrete-time…
Forecasting Covariance Matrices: A Mixed Frequency Approach
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 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...... matrix dynamics. Our empirical results show that the new mixing approach provides superior forecasts compared to multivariate volatility specifications using single sources of information....
Estimation of Low-Rank Covariance Function
Koltchinskii, Vladimir; Lounici, Karim; Tsybakov, Alexander B.
2015-01-01
We consider the problem of estimating a low rank covariance function $K(t,u)$ of a Gaussian process $S(t), t\\in [0,1]$ based on $n$ i.i.d. copies of $S$ observed in a white noise. We suggest a new estimation procedure adapting simultaneously to the low rank structure and the smoothness of the covariance function. The new procedure is based on nuclear norm penalization and exhibits superior performances as compared to the sample covariance function by a polynomial factor in the sample size $n$...
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
Treatment decisions based on scalar and functional baseline covariates.
Ciarleglio, Adam; Petkova, Eva; Ogden, R Todd; Tarpey, Thaddeus
2015-12-01
The amount and complexity of patient-level data being collected in randomized-controlled trials offer both opportunities and challenges for developing personalized rules for assigning treatment for a given disease or ailment. For example, trials examining treatments for major depressive disorder are not only collecting typical baseline data such as age, gender, or scores on various tests, but also data that measure the structure and function of the brain such as images from magnetic resonance imaging (MRI), functional MRI (fMRI), or electroencephalography (EEG). These latter types of data have an inherent structure and may be considered as functional data. We propose an approach that uses baseline covariates, both scalars and functions, to aid in the selection of an optimal treatment. In addition to providing information on which treatment should be selected for a new patient, the estimated regime has the potential to provide insight into the relationship between treatment response and the set of baseline covariates. Our approach can be viewed as an extension of "advantage learning" to include both scalar and functional covariates. We describe our method and how to implement it using existing software. Empirical performance of our method is evaluated with simulated data in a variety of settings and also applied to data arising from a study of patients with major depressive disorder from whom baseline scalar covariates as well as functional data from EEG are available.
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.
Flavour covariant transport equations: An application to resonant leptogenesis
P.S. Bhupal Dev
2014-09-01
Full Text Available We present a fully flavour-covariant formalism for transport phenomena, by deriving Markovian master equations that describe the time-evolution of particle number densities in a statistical ensemble with arbitrary flavour content. As an application of this general formalism, we study flavour effects in a scenario of resonant leptogenesis (RL and obtain the flavour-covariant evolution equations for heavy-neutrino and lepton number densities. This provides a complete and unified description of RL, capturing three distinct physical phenomena: (i the resonant mixing between the heavy-neutrino states, (ii coherent oscillations between different heavy-neutrino flavours, and (iii quantum decoherence effects in the charged-lepton sector. To illustrate the importance of this formalism, we numerically solve the flavour-covariant rate equations for a minimal RL model and show that the total lepton asymmetry can be enhanced by up to one order of magnitude, as compared to that obtained from flavour-diagonal or partially flavour off-diagonal rate equations. Thus, the viable RL model parameter space is enlarged, thereby enhancing further the prospects of probing a common origin of neutrino masses and the baryon asymmetry in the Universe at the LHC, as well as in low-energy experiments searching for lepton flavour and number violation. The key new ingredients in our flavour-covariant formalism are rank-4 rate tensors, which are required for the consistency of our flavour-mixing treatment, as shown by an explicit calculation of the relevant transition amplitudes by generalizing the optical theorem. We also provide a geometric and physical interpretation of the heavy-neutrino degeneracy limits in the minimal RL scenario. Finally, we comment on the consistency of various suggested forms for the heavy-neutrino self-energy regulator in the lepton-number conserving limit.
Covariance NMR spectroscopy by singular value decomposition.
Trbovic, Nikola; Smirnov, Serge; Zhang, Fengli; Brüschweiler, Rafael
2004-12-01
Covariance NMR is demonstrated for homonuclear 2D NMR data collected using the hypercomplex and TPPI methods. Absorption mode 2D spectra are obtained by application of the square-root operation to the covariance matrices. The resulting spectra closely resemble the 2D Fourier transformation spectra, except that they are fully symmetric with the spectral resolution along both dimensions determined by the favorable resolution achievable along omega2. An efficient method is introduced for the calculation of the square root of the covariance spectrum by applying a singular value decomposition (SVD) directly to the mixed time-frequency domain data matrix. Applications are shown for 2D NOESY and 2QF-COSY data sets and computational benchmarks are given for data matrix dimensions typically encountered in practice. The SVD implementation makes covariance NMR amenable to routine applications.
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.
Covariant Quantization with Extended BRST Symmetry
Geyer, B; 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.
Conformally covariant parametrizations for relativistic initial data
Delay, Erwann
2017-01-01
We revisit the Lichnerowicz-York method, and an alternative method of York, in order to obtain some conformally covariant systems. This type of parametrization is certainly more natural for non constant mean curvature initial data.
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.
Covariant action for type IIB supergravity
Sen, Ashoke
2016-07-01
Taking clues from the recent construction of the covariant action for type II and heterotic string field theories, we construct a manifestly Lorentz covariant action for type IIB supergravity, and discuss its gauge fixing maintaining manifest Lorentz invariance. The action contains a (non-gravitating) free 4-form field besides the usual fields of type IIB supergravity. This free field, being completely decoupled from the interacting sector, has no physical consequence.
On the covariance of residual lives
N. Unnikrishnan Nair
2007-10-01
Full Text Available Various properties of residual life such as mean, median, percentiles, variance etc have been discussed in literature on reliability and survival analysis. However a detailed study on covariance between residual lives in a two component system does not seem to have been undertaken. The present paper discusses various properties of product moment and covariance of residual lives. Relationships the product moment has with mean residual life and failure rate are studied and some characterizations are established.
Covariant Hamilton equations for field theory
Giachetta, Giovanni [Department of Mathematics and Physics, University of Camerino, Camerino (Italy); Mangiarotti, Luigi [Department of Mathematics and Physics, University of Camerino, Camerino (Italy)]. E-mail: mangiaro@camserv.unicam.it; Sardanashvily, Gennadi [Department of Theoretical Physics, Physics Faculty, Moscow State University, Moscow (Russian Federation)]. E-mail: sard@grav.phys.msu.su
1999-09-24
We study the relations between the equations of first-order Lagrangian field theory on fibre bundles and the covariant Hamilton equations on the finite-dimensional polysymplectic phase space of covariant Hamiltonian field theory. If a Lagrangian is hyperregular, these equations are equivalent. A degenerate Lagrangian requires a set of associated Hamiltonian forms in order to exhaust all solutions of the Euler-Lagrange equations. The case of quadratic degenerate Lagrangians is studied in detail. (author)
Economical Phase-Covariant Cloning of Qudits
Buscemi, F; Macchiavello, C; Buscemi, Francesco; Ariano, Giacomo Mauro D'; Macchiavello, Chiara
2004-01-01
We derive the optimal $N\\to M$ phase-covariant quantum cloning for equatorial states in dimension $d$ with $M=kd+N$, $k$ integer. The cloning maps are optimal for both global and single-qudit fidelity. The map is achieved by an ``economical'' cloning machine, which works without ancilla. The connection between optimal phase-covariant cloning and optimal multi-phase estimation is finally established.
Representations of Inverse Covariances by Differential Operators
Qin XU
2005-01-01
In the cost function of three- or four-dimensional variational data assimilation, each term is weighted by the inverse of its associated error covariance matrix and the background error covariance matrix is usually much larger than the other covariance matrices. Although the background error covariances are traditionally normalized and parameterized by simple smooth homogeneous correlation functions, the covariance matrices constructed from these correlation functions are often too large to be inverted or even manipulated. It is thus desirable to find direct representations of the inverses of background errorcorrelations. This problem is studied in this paper. In particular, it is shown that the background term can be written into ∫ dx|Dv(x)|2, that is, a squared L2 norm of a vector differential operator D, called the D-operator, applied to the field of analysis increment v(x). For autoregressive correlation functions, the Doperators are of finite orders. For Gaussian correlation functions, the D-operators are of infinite order. For practical applications, the Gaussian D-operators must be truncated to finite orders. The truncation errors are found to be small even when the Gaussian D-operators are truncated to low orders. With a truncated D-operator, the background term can be easily constructed with neither inversion nor direct calculation of the covariance matrix. D-operators are also derived for non-Gaussian correlations and transformed into non-isotropic forms.
Assessing spatial covariance among time series of abundance.
Jorgensen, Jeffrey C; Ward, Eric J; Scheuerell, Mark D; Zabel, Richard W
2016-04-01
For species of conservation concern, an essential part of the recovery planning process is identifying discrete population units and their location with respect to one another. A common feature among geographically proximate populations is that the number of organisms tends to covary through time as a consequence of similar responses to exogenous influences. In turn, high covariation among populations can threaten the persistence of the larger metapopulation. Historically, explorations of the covariance in population size of species with many (>10) time series have been computationally difficult. Here, we illustrate how dynamic factor analysis (DFA) can be used to characterize diversity among time series of population abundances and the degree to which all populations can be represented by a few common signals. Our application focuses on anadromous Chinook salmon (Oncorhynchus tshawytscha), a species listed under the US Endangered Species Act, that is impacted by a variety of natural and anthropogenic factors. Specifically, we fit DFA models to 24 time series of population abundance and used model selection to identify the minimum number of latent variables that explained the most temporal variation after accounting for the effects of environmental covariates. We found support for grouping the time series according to 5 common latent variables. The top model included two covariates: the Pacific Decadal Oscillation in spring and summer. The assignment of populations to the latent variables matched the currently established population structure at a broad spatial scale. At a finer scale, there was more population grouping complexity. Some relatively distant populations were grouped together, and some relatively close populations - considered to be more aligned with each other - were more associated with populations further away. These coarse- and fine-grained examinations of spatial structure are important because they reveal different structural patterns not evident
Covariance and objectivity in mechanics and turbulence
Frewer, Michael
2016-01-01
Form-invariance (covariance) and frame-indifference (objectivity) are two notions in classical continuum mechanics which have attracted much attention and controversy over the past decades. Particularly in turbulence modelling it seems that there still is a need for clarification. The aim and purpose of this study is fourfold: (i) To achieve consensus in general on definitions and principles when trying to establish an invariant theory for modelling constitutive structures and dynamic processes in mechanics, where special focus is put on the principle of Material Frame-Indifference (MFI). (ii) To show that in constitutive modelling MFI can only be regarded as an approximation that needs to be reduced to a weaker statement when trying to advance it to an axiom of nature. (iii) To convince that in dynamical modelling, as in turbulence, MFI may not be utilized as a modelling guideline, not even in an approximative sense. Instead, its reduced form has to be supplemented by a second, independent axiom that include...
Cortisol covariation within parents of young children: Moderation by relationship aggression.
Saxbe, Darby E; Adam, Emma K; Schetter, Christine Dunkel; Guardino, Christine M; Simon, Clarissa; McKinney, Chelsea O; Shalowitz, Madeleine U
2015-12-01
Covariation in diurnal cortisol has been observed in several studies of cohabiting couples. In two such studies (Liu et al., 2013; Saxbe and Repetti, 2010), relationship distress was associated with stronger within-couple correlations, suggesting that couples' physiological linkage with each other may indicate problematic dyadic functioning. Although intimate partner aggression has been associated with dysregulation in women's diurnal cortisol, it has not yet been tested as a moderator of within-couple covariation. This study reports on a diverse sample of 122 parents who sampled salivary cortisol on matched days for two years following the birth of an infant. Partners showed strong positive cortisol covariation. In couples with higher levels of partner-perpetrated aggression reported by women at one year postpartum, both women and men had a flatter diurnal decrease in cortisol and stronger correlations with partners' cortisol sampled at the same timepoints. In other words, relationship aggression was linked both with indices of suboptimal cortisol rhythms in both members of the couples and with stronger within-couple covariation coefficients. These results persisted when relationship satisfaction and demographic covariates were included in the model. During some of the sampling days, some women were pregnant with a subsequent child, but pregnancy did not significantly moderate cortisol levels or within-couple covariation. The findings suggest that couples experiencing relationship aggression have both suboptimal neuroendocrine profiles and stronger covariation. Cortisol covariation is an understudied phenomenon with potential implications for couples' relationship functioning and physical health.
Hydrodynamic Covariant Symplectic Structure from Bilinear Hamiltonian Functions
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.
Wishart distributions for decomposable covariance graph models
Khare, Kshitij; 10.1214/10-AOS841
2011-01-01
Gaussian covariance graph models encode marginal independence among the components of a multivariate random vector by means of a graph $G$. These models are distinctly different from the traditional concentration graph models (often also referred to as Gaussian graphical models or covariance selection models) since the zeros in the parameter are now reflected in the covariance matrix $\\Sigma$, as compared to the concentration matrix $\\Omega =\\Sigma^{-1}$. The parameter space of interest for covariance graph models is the cone $P_G$ of positive definite matrices with fixed zeros corresponding to the missing edges of $G$. As in Letac and Massam [Ann. Statist. 35 (2007) 1278--1323], we consider the case where $G$ is decomposable. In this paper, we construct on the cone $P_G$ a family of Wishart distributions which serve a similar purpose in the covariance graph setting as those constructed by Letac and Massam [Ann. Statist. 35 (2007) 1278--1323] and Dawid and Lauritzen [Ann. Statist. 21 (1993) 1272--1317] do in ...
Lorentz covariance of loop quantum gravity
Rovelli, Carlo
2010-01-01
The kinematics of loop gravity can be given a manifestly Lorentz-covariant formulation: the conventional SU(2)-spin-network Hilbert space can be mapped to a space K of SL(2,C) functions, where Lorentz covariance is manifest. K can be described in terms of a certain subset of the "projected" spin networks studied by Livine, Alexandrov and Dupuis. It is formed by SL(2,C) functions completely determined by their restriction on SU(2). These are square-integrable in the SU(2) scalar product, but not in the SL(2,C) one. Thus, SU(2)-spin-network states can be represented by Lorentz-covariant SL(2,C) functions, as two-component photons can be described in the Lorentz-covariant Gupta-Bleuler formalism. As shown by Wolfgang Wieland in a related paper, this manifestly Lorentz-covariant formulation can also be directly obtained from canonical quantization. We show that the spinfoam dynamics of loop quantum gravity is locally SL(2,C)-invariant in the bulk, and yields states that are preciseley in K on the boundary. This c...
Accurate covariance estimation of galaxy-galaxy weak lensing: limitations of jackknife covariance
Shirasaki, Masato; Miyatake, Hironao; Takahashi, Ryuichi; Hamana, Takashi; Nishimichi, Takahiro; Murata, Ryoma
2016-01-01
We develop a method to simulate galaxy-galaxy weak lensing by utilizing all-sky, light-cone simulations. We populate a real catalog of source galaxies into a light-cone simulation realization, simulate the lensing effect on each galaxy, and then identify lensing halos that are considered to host galaxies or clusters of interest. We use the mock catalog to study the error covariance matrix of galaxy-galaxy weak lensing and find that the super-sample covariance (SSC), which arises from density fluctuations with length scales comparable with or greater than a size of survey area, gives a dominant source of the sample variance. We then compare the full covariance with the jackknife (JK) covariance, the method that estimates the covariance from the resamples of the data itself. We show that, although the JK method gives an unbiased estimator of the covariance in the shot noise or Gaussian regime, it always over-estimates the true covariance in the sample variance regime, because the JK covariance turns out to be a...
Hackel, Meredith A; Tsuji, Masakatsu; Yamano, Yoshinori; Echols, Roger; Karlowsky, James A; Sahm, Daniel F
2017-09-01
-negative bacilli, including carbapenem-nonsusceptible isolates. Copyright © 2017 American Society for Microbiology.
Multigroup covariance matrices for fast-reactor studies
Smith, J.D. III; Broadhead, B.L.
1981-04-01
This report presents the multigroup covariance matrices based on the ENDF/B-V nuclear data evaluations. The materials and reactions have been chosen according to the specifications of ORNL-5517. Several cross section covariances, other than those specified by that report, are included due to the derived nature of the uncertainty files in ENDF/B-V. The materials represented are Ni, Cr, /sup 16/O, /sup 12/C, Fe, Na, /sup 235/U, /sup 238/U, /sup 239/Pu, /sup 240/Pu, /sup 241/Pu, and /sup 10/B (present due to its correlation to /sup 238/U). The data have been originally processed into a 52-group energy structure by PUFF-II and subsequently collapsed to smaller subgroup strutures. The results are illustrated in 52-group correlation matrix plots and tabulated into thirteen groups for convenience.
Transformation rule for covariance matrices under Bell-like detections
Spedalieri, Gaetana; Pirandola, Stefano
2013-01-01
Starting from the transformation rule of a covariance matrix under homodyne detections, we can easily derive a formula for the transformation of a covariance matrix of (n+2) bosonic modes under Bell-like detections, where the last two modes are combined in an arbitrary beam splitter (i.e., with arbitrary transmissivity) and then homodyned. This formula can be specialized to describe the standard Bell detection and the heterodyne measurement, which are exploited in many contexts, including protocols of quantum teleportation, entanglement swapping and quantum cryptography. Our general formula can be adopted to study these protocols in the presence of experimental imperfections or asymmetric setups, e.g., deriving from the use of unbalanced beam splitters.
The Shape of Covariantly Smeared Sources in Lattice QCD
von Hippel, Georg M; Rae, Thomas D; Wittig, Hartmut
2013-01-01
Covariantly smeared sources are commonly used in lattice QCD to enhance the projection onto the ground state. Here we investigate the dependence of their shape on the gauge field background and find that the presence of localized concentrations of magnetic field can lead to strong distortions which reduce the smearing radii achievable by iterative smearing prescriptions. In particular, as $a\\to 0$, iterative procedures like Jacobi smearing require increasingly large iteration counts in order to reach physically-sized smearing radii $r_{sm}\\sim$ 0.5 fm, and the resulting sources are strongly distorted. To bypass this issue, we propose a covariant smearing procedure (``free-form smearing'') that allows us to create arbitrarily shaped sources, including in particular Gaussians of arbitrary radius.
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.
Covariant Lyapunov vectors for rigid disk systems.
Bosetti, Hadrien; Posch, Harald A
2010-10-05
We carry out extensive computer simulations to study the Lyapunov instability of a two-dimensional hard-disk system in a rectangular box with periodic boundary conditions. The system is large enough to allow the formation of Lyapunov modes parallel to the x-axis of the box. The Oseledec splitting into covariant subspaces of the tangent space is considered by computing the full set of covariant perturbation vectors co-moving with the flow in tangent space. These vectors are shown to be transversal, but generally not orthogonal to each other. Only the angle between covariant vectors associated with immediate adjacent Lyapunov exponents in the Lyapunov spectrum may become small, but the probability of this angle to vanish approaches zero. The stable and unstable manifolds are transverse to each other and the system is hyperbolic.
Manifest Covariant Hamiltonian Theory of General Relativity
Cremaschini, Claudio
2016-01-01
The problem of formulating a manifest covariant Hamiltonian theory of General Relativity in the presence of source fields is addressed, by extending the so-called "DeDonder-Weyl" formalism to the treatment of classical fields in curved space-time. The theory is based on a synchronous variational principle for the Einstein equation, formulated in terms of superabundant variables. The technique permits one to determine the continuum covariant Hamiltonian structure associated with the Einstein equation. The corresponding continuum Poisson bracket representation is also determined. The theory relies on first-principles, in the sense that the conclusions are reached in the framework of a non-perturbative covariant approach, which allows one to preserve both the 4-scalar nature of Lagrangian and Hamiltonian densities as well as the gauge invariance property of the theory.
Hui, Yi; Law, Siu Seong; Ku, Chiu Jen
2017-02-01
Covariance of the auto/cross-covariance matrix based method is studied for the damage identification of a structure with illustrations on its advantages and limitations. The original method is extended for structures under direct white noise excitations. The auto/cross-covariance function of the measured acceleration and its corresponding derivatives are formulated analytically, and the method is modified in two new strategies to enable successful identification with much fewer sensors. Numerical examples are adopted to illustrate the improved method, and the effects of sampling frequency and sampling duration are discussed. Results show that the covariance of covariance calculated from responses of higher order modes of a structure play an important role to the accurate identification of local damage in a structure.
Activities on covariance estimation in Japanese Nuclear Data Committee
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)
Notes on Cosmic Censorship Conjecture revisited: Covariantly
Hamid, Aymen I M; Maharaj, Sunil D
2016-01-01
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.
A covariant formulation of classical spinning particle
Cho, J H; Kim, J K; Jin-Ho Cho; Seungjoon Hyun; Jae-Kwan Kim
1994-01-01
Covariantly we reformulate the description of a spinning particle in terms of the which entails all possible constraints explicitly; all constraints can be obtained just from the Lagrangian. Furthermore, in this covariant reformulation, the Lorentz element is to be considered to evolve the momentum or spin component from an arbitrary fixed frame and not just from the particle rest frame. In distinction with the usual formulation, our system is directly comparable with the pseudo-classical formulation. We get a peculiar symmetry which resembles the supersymmetry of the pseudo-classical formulation.
A violation of the covariant entropy bound?
Masoumi, Ali
2014-01-01
Several arguments suggest that the entropy density at high energy density $\\rho$ should be given by the expression $s=K\\sqrt{\\rho/G}$, where $K$ is a constant of order unity. On the other hand the covariant entropy bound requires that the entropy on a light sheet be bounded by $A/4G$, where $A$ is the area of the boundary of the sheet. We find that in a suitably chosen cosmological geometry, the above expression for $s$ violates the covariant entropy bound. We consider different possible explanations for this fact; in particular the possibility that entropy bounds should be defined in terms of volumes of regions rather than areas of surfaces.
Zhao, Wenle; Hill, Michael D; Palesch, Yuko
2015-12-01
In many clinical trials, baseline covariates could affect the primary outcome. Commonly used strategies to balance baseline covariates include stratified constrained randomization and minimization. Stratification is limited to few categorical covariates. Minimization lacks the randomness of treatment allocation. Both apply only to categorical covariates. As a result, serious imbalances could occur in important baseline covariates not included in the randomization algorithm. Furthermore, randomness of treatment allocation could be significantly compromised because of the high proportion of deterministic assignments associated with stratified block randomization and minimization, potentially resulting in selection bias. Serious baseline covariate imbalances and selection biases often contribute to controversial interpretation of the trial results. The National Institute of Neurological Disorders and Stroke recombinant tissue plasminogen activator Stroke Trial and the Captopril Prevention Project are two examples. In this article, we propose a new randomization strategy, termed the minimal sufficient balance randomization, which will dually prevent serious imbalances in all important baseline covariates, including both categorical and continuous types, and preserve the randomness of treatment allocation. Computer simulations are conducted using the data from the National Institute of Neurological Disorders and Stroke recombinant tissue plasminogen activator Stroke Trial. Serious imbalances in four continuous and one categorical covariate are prevented with a small cost in treatment allocation randomness. A scenario of simultaneously balancing 11 baseline covariates is explored with similar promising results. The proposed minimal sufficient balance randomization algorithm can be easily implemented in computerized central randomization systems for large multicenter trials.
The relevance and consequences of mediterranean desertification including security aspects
2006-01-01
33 páginas, 5 figuras, 4 tablas. Proceedings of the NATO Mediterranean Dialogue Workshop on Desertification in the Mediterranean Region. A Security Issue -- Part I. Introducction: Desertification in the Mediterranen Region: Linking environmental condition to security. Valencia, Spain 2-5 December 2003
Xu, Xu Steven; Yuan, Min; Yang, Haitao; Feng, Yan; Xu, Jinfeng; Pinheiro, Jose
2017-01-01
Covariate analysis based on population pharmacokinetics (PPK) is used to identify clinically relevant factors. The likelihood ratio test (LRT) based on nonlinear mixed effect model fits is currently recommended for covariate identification, whereas individual empirical Bayesian estimates (EBEs) are considered unreliable due to the presence of shrinkage. The objectives of this research were to investigate the type I error for LRT and EBE approaches, to confirm the similarity of power between the LRT and EBE approaches from a previous report and to explore the influence of shrinkage on LRT and EBE inferences. Using an oral one-compartment PK model with a single covariate impacting on clearance, we conducted a wide range of simulations according to a two-way factorial design. The results revealed that the EBE-based regression not only provided almost identical power for detecting a covariate effect, but also controlled the false positive rate better than the LRT approach. Shrinkage of EBEs is likely not the root cause for decrease in power or inflated false positive rate although the size of the covariate effect tends to be underestimated at high shrinkage. In summary, contrary to the current recommendations, EBEs may be a better choice for statistical tests in PPK covariate analysis compared to LRT. We proposed a three-step covariate modeling approach for population PK analysis to utilize the advantages of EBEs while overcoming their shortcomings, which allows not only markedly reducing the run time for population PK analysis, but also providing more accurate covariate tests.
Full covariance of CMB and lensing reconstruction power spectra
Peloton, Julien; Schmittfull, Marcel; Lewis, Antony; Carron, Julien; Zahn, Oliver
2017-02-01
CMB and lensing reconstruction power spectra are powerful probes of cosmology. However, they are correlated, since the CMB power spectra are lensed, and the lensing reconstruction is constructed using CMB multipoles. We perform a full analysis of the auto- and cross-covariances, including polarization power spectra and minimum-variance lensing estimators, and compare with simulations of idealized future CMB-S4 observations. Covariances sourced by fluctuations in the unlensed CMB and instrumental noise can largely be removed by using a realization-dependent subtraction of lensing reconstruction noise, leaving a relatively simple covariance model that is dominated by lensing-induced terms and well described by a small number of principal components. The correlations between the CMB and lensing power spectra will be detectable at the level of ˜5 σ for a CMB-S4 mission, and neglecting them could underestimate some parameter error bars by several tens of percent. However, we found that the inclusion of external priors or data sets to estimate parameter error bars can make the impact of the correlations almost negligible.
A Covariant model for the nucleon and the $\\Delta$
Ramalho, G; Gross, Franz
2008-01-01
The covariant spectator formalism is used to model the nucleon and the $\\Delta$(1232) as a system of three constituent quarks with their own electromagnetic structure. The definition of the ``fixed-axis'' polarization states for the diquark emitted from the initial state vertex and absorbed into the final state vertex is discussed. The helicity sum over those states is evaluated and seen to be covariant. Using this approach, all four electromagnetic form factors of the nucleon, together with the {\\it magnetic} form factor, $G_M^*$, for the $\\gamma N \\to \\Delta$ transition, can be described using manifestly covariant nucleon and $\\Delta$ wave functions with {\\it zero} orbital angular momentum $L$, but a successful description of $G_M^*$ near $Q^2=0$ requires the addition of a pion cloud term not included in the class of valence quark models considered here. We also show that the pure $S$-wave model gives electric, $G_E^*$, and coulomb, $G^*_C$, transition form factors that are identically zero, showing that th...
The Massless Spectrum of Covariant Superstrings
Grassi, P A; van Nieuwenhuizen, P
2002-01-01
We obtain the correct cohomology at any ghost number for the open and closed covariant superstring, quantized by an approach which we recently developed. We define physical states by the usual condition of BRST invariance and a new condition involving a new current which is related to a grading of the underlying affine Lie algebra.
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 def
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...
Covariant formulation of pion-nucleon scattering
Lahiff, A. D.; Afnan, I. R.
A covariant model of elastic pion-nucleon scattering based on the Bethe-Salpeter equation is presented. The kernel consists of s- and u-channel nucleon and delta poles, along with rho and sigma exchange in the t-channel. A good fit is obtained to the s- and p-wave phase shifts up to the two-pion production threshold.
Approximate methods for derivation of covariance data
Tagesen, S. [Vienna Univ. (Austria). Inst. fuer Radiumforschung und Kernphysik; Larson, D.C. [Oak Ridge National Lab., TN (United States)
1992-12-31
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.
Covariance of noncommutative Grassmann star product
Daoud, M.
2004-01-01
Using the Coherent states of many fermionic degrees of freedom labeled by Gra\\ss mann variables, we introduce the noncommutative (precisely non anticommutative) Gra\\ss mann star product. The covariance of star product under unitary transformations, particularly canonical ones, is studied. The super star product, based on supercoherent states of supersymmetric harmonic oscillator, is also considered.
Covariance of the selfdual vector model
2004-01-01
The Poisson algebra between the fields involved in the vectorial selfdual action is obtained by means of the reduced action. The conserved charges associated with the invariance under the inhomogeneous Lorentz group are obtained and its action on the fields. The covariance of the theory is proved using the Schwinger-Dirac algebra. The spin of the excitations is discussed.
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.
Linear transformations of variance/covariance matrices
Parois, P.J.A.; Lutz, M.
2011-01-01
Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance
Covariant derivative expansion of the heat kernel
Salcedo, L.L. [Universidad de Granada, Departamento de Fisica Moderna, Granada (Spain)
2004-11-01
Using the technique of labeled operators, compact explicit expressions are given for all traced heat kernel coefficients containing zero, two, four and six covariant derivatives, and for diagonal coefficients with zero, two and four derivatives. The results apply to boundaryless flat space-times and arbitrary non-Abelian scalar and gauge background fields. (orig.)
Enveloping Spectral Surfaces: Covariate Dependent Spectral Analysis of Categorical Time Series.
Krafty, Robert T; Xiong, Shuangyan; Stoffer, David S; Buysse, Daniel J; Hall, Martica
2012-09-01
Motivated by problems in Sleep Medicine and Circadian Biology, we present a method for the analysis of cross-sectional categorical time series collected from multiple subjects where the effect of static continuous-valued covariates is of interest. Toward this goal, we extend the spectral envelope methodology for the frequency domain analysis of a single categorical process to cross-sectional categorical processes that are possibly covariate dependent. The analysis introduces an enveloping spectral surface for describing the association between the frequency domain properties of qualitative time series and covariates. The resulting surface offers an intuitively interpretable measure of association between covariates and a qualitative time series by finding the maximum possible conditional power at a given frequency from scalings of the qualitative time series conditional on the covariates. The optimal scalings that maximize the power provide scientific insight by identifying the aspects of the qualitative series which have the most pronounced periodic features at a given frequency conditional on the value of the covariates. To facilitate the assessment of the dependence of the enveloping spectral surface on the covariates, we include a theory for analyzing the partial derivatives of the surface. Our approach is entirely nonparametric, and we present estimation and asymptotics in the setting of local polynomial smoothing.
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....
McEwan, C.; Ball, M.; Novog, D., E-mail: mcewac2@mcmaster.ca [McMaster Univ., Hamilton, Ontario (Canada)
2013-07-01
Simulation results are of little use if nothing is known about the uncertainty in the results. In order to assess the uncertainty in a set of output parameters due to uncertainty in a set of input parameters, knowledge of the covariance between input parameters is required. Current practice is to apply the covariance between multigroup cross sections at infinite dilution to all cross sections including those at non-infinite dilutions. In this work, the effect of dilution on multigroup cross section covariance is investigated as well as the effect on the covariance between the few group homogenized cross sections produced by lattice code DRAGON. (author)
Covariant effective action for a Galilean invariant quantum Hall system
Geracie, Michael; Prabhu, Kartik; Roberts, Matthew M.
2016-09-01
We construct effective field theories for gapped quantum Hall systems coupled to background geometries with local Galilean invariance i.e. Bargmann spacetimes. Along with an electromagnetic field, these backgrounds include the effects of curved Galilean spacetimes, including torsion and a gravitational field, allowing us to study charge, energy, stress and mass currents within a unified framework. A shift symmetry specific to single constituent theories constraints the effective action to couple to an effective background gauge field and spin connection that is solved for by a self-consistent equation, providing a manifestly covariant extension of Hoyos and Son's improvement terms to arbitrary order in m.
Unravelling Lorentz Covariance and the Spacetime Formalism
Cahill R. T.
2008-10-01
Full Text Available We report the discovery of an exact mapping from Galilean time and space coordinates to Minkowski spacetime coordinates, showing that Lorentz covariance and the space-time construct are consistent with the existence of a dynamical 3-space, and absolute motion. We illustrate this mapping first with the standard theory of sound, as vibrations of a medium, which itself may be undergoing fluid motion, and which is covariant under Galilean coordinate transformations. By introducing a different non-physical class of space and time coordinates it may be cast into a form that is covariant under Lorentz transformations wherein the speed of sound is now the invariant speed. If this latter formalism were taken as fundamental and complete we would be lead to the introduction of a pseudo-Riemannian spacetime description of sound, with a metric characterised by an invariant speed of sound. This analysis is an allegory for the development of 20th century physics, but where the Lorentz covariant Maxwell equations were constructed first, and the Galilean form was later constructed by Hertz, but ignored. It is shown that the Lorentz covariance of the Maxwell equations only occurs because of the use of non-physical space and time coordinates. The use of this class of coordinates has confounded 20th century physics, and resulted in the existence of a allowing dynamical 3-space being overlooked. The discovery of the dynamics of this 3-space has lead to the derivation of an extended gravity theory as a quantum effect, and confirmed by numerous experiments and observations
Unravelling Lorentz Covariance and the Spacetime Formalism
Cahill R. T.
2008-10-01
Full Text Available We report the discovery of an exact mapping from Galilean time and space coordinates to Minkowski spacetime coordinates, showing that Lorentz covariance and the space- time construct are consistent with the existence of a dynamical 3-space, and “absolute motion”. We illustrate this mapping first with the standard theory of sound, as vibra- tions of a medium, which itself may be undergoing fluid motion, and which is covari- ant under Galilean coordinate transformations. By introducing a different non-physical class of space and time coordinates it may be cast into a form that is covariant under “Lorentz transformations” wherein the speed of sound is now the “invariant speed”. If this latter formalism were taken as fundamental and complete we would be lead to the introduction of a pseudo-Riemannian “spacetime” description of sound, with a metric characterised by an “invariant speed of sound”. This analysis is an allegory for the development of 20th century physics, but where the Lorentz covariant Maxwell equa- tions were constructed first, and the Galilean form was later constructed by Hertz, but ignored. It is shown that the Lorentz covariance of the Maxwell equations only occurs because of the use of non-physical space and time coordinates. The use of this class of coordinates has confounded 20th century physics, and resulted in the existence of a “flowing” dynamical 3-space being overlooked. The discovery of the dynamics of this 3-space has lead to the derivation of an extended gravity theory as a quantum effect, and confirmed by numerous experiments and observations
On covariances for fusing laser rangers and vision with sensors onboard a moving robot
Wernersson, Åke; Nygårds, Jonas
1998-01-01
Consider a robot to measure or operate on man made objects randomly located in the workspace. The optronic sensing onboard the robot are a scanning range measuring time-of-flight laser and a CCD camera. The goal of the paper is to give explicit covariance matrices for the extracted geometric primitives in the surrounding workspace. Emphasis is on correlation properties of the stochastic error models during motion. Topics studied include: (i) covariance of Radon/Hough peaks for plane surfaces;...
Coincidence and covariance data acquisition in photoelectron and -ion spectroscopy. I. Formal theory
Mikosch, Jochen; Patchkovskii, Serguei
2013-10-01
We derive a formal theory of noisy Poisson processes with multiple outcomes. We obtain simple, compact expressions for the probability distribution function of arbitrarily complex composite events and its moments. We illustrate the utility of the theory by analyzing properties of coincidence and covariance photoelectron-photoion detection involving single-ionization events. The results and techniques introduced in this work are directly applicable to more general coincidence and covariance experiments, including multiple ionization and multiple-ion fragmentation pathways.
In-medium covariant propagator of nucleons under a strong magnetic field
Aguirre, R M
2016-01-01
We obtain the covariant propagator at finite temperature for interacting nucleons immersed in a strong magnetic field, including the effects of the intrinsic anomalous magnetic moments. We make an expansion in terms of the eigenfunctions in the mean field approximation. We define spinors satisfying covariant orthogonal conditions, which allows a straightforward compact form of the Green function. We present some simple applications of these propagators, where the statistical averages of nuclear currents and energy density are evaluated.
Identifiability of the Sign of Covariate Effects in the Competing Risks Model
Lo, Simon M.S.; Wilke, Ralf
2017-01-01
We present a new framework for the identification of competing risks models, which also include Roy models. We show that by establishing a Hicksian-type decomposition, the direction of covariate effects on the marginal distributions of the competing risks model can be identified under weak...... of the range of durations for which the direction of the covariate effect is identified, particularly for long duration....
Informed conditioning on clinical covariates increases power in case-control association studies.
Zaitlen, Noah; Lindström, Sara; Pasaniuc, Bogdan; Cornelis, Marilyn; Genovese, Giulio; Pollack, Samuela; Barton, Anne; Bickeböller, Heike; Bowden, Donald W; Eyre, Steve; Freedman, Barry I; Friedman, David J; Field, John K; Groop, Leif; Haugen, Aage; Heinrich, Joachim; Henderson, Brian E; Hicks, Pamela J; Hocking, Lynne J; Kolonel, Laurence N; Landi, Maria Teresa; Langefeld, Carl D; Le Marchand, Loic; Meister, Michael; Morgan, Ann W; Raji, Olaide Y; Risch, Angela; Rosenberger, Albert; Scherf, David; Steer, Sophia; Walshaw, Martin; Waters, Kevin M; Wilson, Anthony G; Wordsworth, Paul; Zienolddiny, Shanbeh; Tchetgen, Eric Tchetgen; Haiman, Christopher; Hunter, David J; Plenge, Robert M; Worthington, Jane; Christiani, David C; Schaumberg, Debra A; Chasman, Daniel I; Altshuler, David; Voight, Benjamin; Kraft, Peter; Patterson, Nick; Price, Alkes L
2012-01-01
Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low-BMI cases are larger than those estimated from high-BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment) or phenotype and clinical covariates (case-control-covariate ascertainment). While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled false-positive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1 × 10(-9)). The improvement varied across diseases with a 16% median increase in χ(2) test statistics and a
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.
Chiral Dynamics of Baryons in a Lorentz Covariant Quark Model
Faessler, A; Lyubovitskij, V E; Pumsa-ard, K; Faessler, Amand; Gutsche, Th.
2006-01-01
We develop a manifestly Lorentz covariant chiral quark model for the study of baryons as bound states of constituent quarks dressed by a cloud of pseudoscalar mesons. The approach is based on a non-linear chirally symmetric Lagrangian, which involves effective degrees of freedom - constituent quarks and the chiral (pseudoscalar meson) fields. In a first step, this Lagrangian can be used to perform a dressing of the constituent quarks by a cloud of light pseudoscalar mesons and other heavy states using the calculational technique of infrared dimensional regularization of loop diagrams. We calculate the dressed transition operators with a proper chiral expansion which are relevant for the interaction of quarks with external fields in the presence of a virtual meson cloud. In a second step, these dressed operators are used to calculate baryon matrix elements. Applications are worked out for the masses of the baryon octet, the meson-nucleon sigma terms, the magnetic moments of the baryon octet, the nucleon charge...
Dowling, D K; Maklakov, A A; Friberg, U; Hailer, F
2009-04-01
Two genetic models exist to explain the evolution of ageing - mutation accumulation (MA) and antagonistic pleiotropy (AP). Under MA, a reduced intensity of selection with age results in accumulation of late-acting deleterious mutations. Under AP, late-acting deleterious mutations accumulate because they confer beneficial effects early in life. Recent studies suggest that the mitochondrial genome is a major player in ageing. It therefore seems plausible that the MA and AP models will be relevant to genomes within the cytoplasm. This possibility has not been considered previously. We explore whether patterns of covariation between fitness and ageing across 25 cytoplasmic lines, sampled from a population of Drosophila melanogaster, are consistent with the genetic associations predicted under MA or AP. We find negative covariation for fitness and the rate of ageing, and positive covariation for fitness and lifespan. Notably, the direction of these associations is opposite to that typically predicted under AP.
Pion generalized parton distributions within a fully covariant constituent quark model
Fanelli, Cristiano [Massachusetts Institute of Technology, Cambridge, MA (United States). Lab. for Nuclear Science; Pace, Emanuele [' ' Tor Vergata' ' Univ., Rome (Italy). Physics Dept.; INFN Sezione di TorVergata, Rome (Italy); Romanelli, Giovanni [Rutherford-Appleton Laboratory, Didcot (United Kingdom). STFC; Salme, Giovanni [Istituto Nazionale di Fisica Nucleare, Rome (Italy); Salmistraro, Marco [Rome La Sapienza Univ. (Italy). Physics Dept.; I.I.S. G. De Sanctis, Rome (Italy)
2016-05-15
We extend the investigation of the generalized parton distribution for a charged pion within a fully covariant constituent quark model, in two respects: (1) calculating the tensor distribution and (2) adding the treatment of the evolution, needed for achieving a meaningful comparison with both the experimental parton distribution and the lattice evaluation of the so-called generalized form factors. Distinct features of our phenomenological covariant quark model are: (1) a 4D Ansatz for the pion Bethe-Salpeter amplitude, to be used in the Mandelstam formula for matrix elements of the relevant current operators, and (2) only two parameters, namely a quark mass assumed to be m{sub q} = 220 MeV and a free parameter fixed through the value of the pion decay constant. The possibility of increasing the dynamical content of our covariant constituent quark model is briefly discussed in the context of the Nakanishi integral representation of the Bethe-Salpeter amplitude. (orig.)
Chi, Zhiyi
2010-01-01
Two extensions of generalized linear models are considered. In the first one, response variables depend on multiple linear combinations of covariates. In the second one, only response variables are observed while the linear covariates are missing. We derive stochastic Lipschitz continuity results for the loss functions involved in the regression problems and apply them to get bounds on estimation error for Lasso. Multivariate comparison results on Rademacher complexity are obtained as tools to establish the stochastic Lipschitz continuity results.
Brief Review on the Relevance Theory
龚腾龙; 阿勒腾
2015-01-01
Relevance theory has had an impact on the study in various disciplines including linguistics,literature and so on. This paper gives a brief review of the relevance theory and two principles of relevance.
Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.
Engemann, Denis A; Gramfort, Alexandre
2015-03-01
Magnetoencephalography and electroencephalography (M/EEG) measure non-invasively the weak electromagnetic fields induced by post-synaptic neural currents. The estimation of the spatial covariance of the signals recorded on M/EEG sensors is a building block of modern data analysis pipelines. Such covariance estimates are used in brain-computer interfaces (BCI) systems, in nearly all source localization methods for spatial whitening as well as for data covariance estimation in beamformers. The rationale for such models is that the signals can be modeled by a zero mean Gaussian distribution. While maximizing the Gaussian likelihood seems natural, it leads to a covariance estimate known as empirical covariance (EC). It turns out that the EC is a poor estimate of the true covariance when the number of samples is small. To address this issue the estimation needs to be regularized. The most common approach downweights off-diagonal coefficients, while more advanced regularization methods are based on shrinkage techniques or generative models with low rank assumptions: probabilistic PCA (PPCA) and factor analysis (FA). Using cross-validation all of these models can be tuned and compared based on Gaussian likelihood computed on unseen data. We investigated these models on simulations, one electroencephalography (EEG) dataset as well as magnetoencephalography (MEG) datasets from the most common MEG systems. First, our results demonstrate that different models can be the best, depending on the number of samples, heterogeneity of sensor types and noise properties. Second, we show that the models tuned by cross-validation are superior to models with hand-selected regularization. Hence, we propose an automated solution to the often overlooked problem of covariance estimation of M/EEG signals. The relevance of the procedure is demonstrated here for spatial whitening and source localization of MEG signals.
SUN; Xiaomin; ZHU; Zhilin; XU; Jinping; YUAN; Guofu
2005-01-01
It is more and more popular to estimate the exchange of water vapor, heat and CO2fluxes between the land surface and the atmosphere using the eddy covariance technique. To get believable fluxes, it is necessary to correct the observations based on the different surface conditions and to determine relevant techinical parameters. The raw 10 Hz eddy covariance data observed in the Yucheng and Changbai Mountains stations were recalculated by various averaging periods (from 1 to 720 min) respectively, and the recalculated results were compared with the results calculated by the averaging period of 30 mins. Meanwhile, the distinctions of fluxes calculated by different averaging periods were analyzed. The continuous 15 days observations over wheat fields in the Yucheng station were mainly analyzed. The results are shown that: (i) In the Yucheng station, compared with the observations by 30 min, when the averaging period changes from 10 to 60 min, the variations of the eddy-covariance estimates of fluxes were less than 2%; when the averaging period changes less than 10 min, the estimate of fluxes reduced obviously with the reduction of the averaging period (the max relative error was -12%); and when the averaging period exceeds 120 min, the eddy covariance estimates of fluxes will be increased and become unsteady (the max relative error is over 10%); (ii) the eddy covariance estimates of fluxes over wheat field in the Yucheng station suggusted that it is much better to take 10 min as an averaging period in studying diurnal change of fluxes, and take 30min for a long-term flux observation; and (iii) normalized ratio was put forward to determine the range of averaging period of eddy covariance measurements. By comparing the observations over farmlands and those over forests, it is indicated that the increase of eddy covariance estimates over tall forest was more than that over short vegetation when the averaging period increased.
A hierarchical nest survival model integrating incomplete temporally varying covariates
Converse, Sarah J.; Royle, J. Andrew; Adler, Peter H.; Urbanek, Richard P.; Barzan, Jeb A.
2013-01-01
biting-insect hypothesis and other hypotheses for nesting failure in this reintroduced population; resulting inferences will support ongoing efforts to manage this population via an adaptive management approach. Wider application of our approach offers promise for modeling the effects of other temporally varying, but imperfectly observed covariates on nest survival, including the possibility of modeling temporally varying covariates collected from incubating adults.
Ocean Data Assimilation with Background Error Covariance Derived from OGCM Outputs
符伟伟; 周广庆; 王会军
2004-01-01
The background error covariance plays an important role in modern data assimilation and analysis systems by determining the spatial spreading of information in the data. A novel method based on model output is proposed to estimate background error covariance for use in Optimum Interpolation. At every model level, anisotropic correlation scales are obtained that give a more detailed description of the spatial correlation structure. Furthermore, the impact of the background field itself is included in the background error covariance. The methodology of the estimation is presented and the structure of the covariance is examined. The results of 20-year assimilation experiments are compared with observations from TOGATAO (The Tropical Ocean-Global Atmosphere-Tropical Atmosphere Ocean) array and other analysis data.
Covariant Quantization of CPT-violating Photons
Colladay, D; Noordmans, J P; Potting, R
2016-01-01
We perform the covariant canonical quantization of the CPT- and Lorentz-symmetry-violating photon sector of the minimal Standard-Model Extension, which contains a general (timelike, lightlike, or spacelike) fixed background tensor $k_{AF}^\\mu$. Well-known stability issues, arising from complex-valued energy states, are solved by introducing a small photon mass, orders of magnitude below current experimental bounds. We explicitly construct a covariant basis of polarization vectors, in which the photon field can be expanded. We proceed to derive the Feynman propagator and show that the theory is microcausal. Despite the occurrence of negative energies and vacuum-Cherenkov radiation, we do not find any runaway stability issues, because the energy remains bounded from below. An important observation is that the ordering of the roots of the dispersion relations is the same in any observer frame, which allows for a frame-independent condition that selects the correct branch of the dispersion relation. This turns ou...
Covariant holography of a tachyonic accelerating universe
Rozas-Fernández, Alberto
2014-01-01
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 $w=p/\\rho$, 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 analysed whether the existence of these preferred screens allows a mathematically consistent formulation of fundamental theories based on the existence of a S matrix at infinite distances.
Model selection for Poisson processes with covariates
Sart, Mathieu
2011-01-01
We observe $n$ inhomogeneous Poisson processes with covariates and aim at estimating their intensities. To handle this problem, we assume that the intensity of each Poisson process is of the form $s (\\cdot, x)$ where $x$ is the covariate and where $s$ is an unknown function. We propose a model selection approach where the models are used to approximate the multivariate function $s$. We show that our estimator satisfies an oracle-type inequality under very weak assumptions both on the intensities and the models. By using an Hellinger-type loss, we establish non-asymptotic risk bounds and specify them under various kind of assumptions on the target function $s$ such as being smooth or composite. Besides, we show that our estimation procedure is robust with respect to these assumptions.
Errors on errors - Estimating cosmological parameter covariance
Joachimi, Benjamin
2014-01-01
Current and forthcoming cosmological data analyses share the challenge of huge datasets alongside increasingly tight requirements on the precision and accuracy of extracted cosmological parameters. The community is becoming increasingly aware that these requirements not only apply to the central values of parameters but, equally important, also to the error bars. Due to non-linear effects in the astrophysics, the instrument, and the analysis pipeline, data covariance matrices are usually not well known a priori and need to be estimated from the data itself, or from suites of large simulations. In either case, the finite number of realisations available to determine data covariances introduces significant biases and additional variance in the errors on cosmological parameters in a standard likelihood analysis. Here, we review recent work on quantifying these biases and additional variances and discuss approaches to remedy these effects.
Linear transformations of variance/covariance matrices.
Parois, Pascal; Lutz, Martin
2011-07-01
Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance matrix. For the transformation of second-rank tensors it is suggested that the 3 × 3 matrix is re-written into a 9 × 1 vector. The transformation of the corresponding variance/covariance matrix is then straightforward and easily implemented into computer software. This method is applied in the transformation of anisotropic displacement parameters, the calculation of equivalent isotropic displacement parameters, the comparison of refinements in different space-group settings and the calculation of standard uncertainties of eigenvalues.
Covariant holography of a tachyonic accelerating universe
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.)
Chiral Four-Dimensional Heterotic Covariant Lattices
Beye, Florian
2014-01-01
In the covariant lattice formalism, chiral four-dimensional heterotic string vacua are obtained from certain even self-dual lattices which completely decompose into a left-mover and a right-mover lattice. The main purpose of this work is to classify all right-mover lattices that can appear in such a chiral model, and to study the corresponding left-mover lattices using the theory of lattice genera. In particular, the Smith-Minkowski-Siegel mass formula is employed to calculate a lower bound on the number of left-mover lattices. Also, the known relationship between asymmetric orbifolds and covariant lattices is considered in the context of our classification.
Twisted Covariant Noncommutative Self-dual Gravity
Estrada-Jimenez, S; Obregón, O; Ramírez, C
2008-01-01
A twisted covariant formulation of noncommutative self-dual gravity is presented. The recent formulation introduced by J. Wess and coworkers for constructing twisted Yang-Mills fields is used. It is shown that the noncommutative torsion is solved at any order of the $\\theta$-expansion in terms of the tetrad and the extra fields of the theory. In the process the first order expansion in $\\theta$ for the Pleba\\'nski action is explicitly obtained.
Covariant quantization of the CBS superparticle
Grassi, P.A. E-mail: pag5@nyu.edu; Policastro, G.; Porrati, M
2001-07-09
The quantization of the Casalbuoni-Brink-Schwarz superparticle is performed in an explicitly covariant way using the antibracket formalism. Since an infinite number of ghost fields are required, within a suitable off-shell twistor-like formalism, we are able to fix the gauge of each ghost sector without modifying the physical content of the theory. The computation reveals that the antibracket cohomology contains only the physical degrees of freedom.
Adaptive Covariance Estimation with model selection
Biscay, Rolando; Loubes, Jean-Michel
2012-01-01
We provide in this paper a fully adaptive penalized procedure to select a covariance among a collection of models observing i.i.d replications of the process at fixed observation points. For this we generalize previous results of Bigot and al. and propose to use a data driven penalty to obtain an oracle inequality for the estimator. We prove that this method is an extension to the matricial regression model of the work by Baraud.
Economical phase-covariant cloning with multiclones
Zhang Wen-Hai; Ye Liu
2009-01-01
This paper presents a very simple method to derive the explicit transformations of the optimal economical to M phase-covariant cloning. The fidelity of clones reaches the theoretic bound [D'Ariano G M and Macchiavello C 2003 Phys. Rcv. A 67 042306]. The derived transformations cover the previous contributions [Delgado Y,Lamata L et al,2007 Phys. Rev. Lett. 98 150502] in which M must be odd.
Unbiased risk estimation method for covariance estimation
Lescornel, Hélène; Chabriac, Claudie
2011-01-01
We consider a model selection estimator of the covariance of a random process. Using the Unbiased Risk Estimation (URE) method, we build an estimator of the risk which allows to select an estimator in a collection of model. Then, we present an oracle inequality which ensures that the risk of the selected estimator is close to the risk of the oracle. Simulations show the efficiency of this methodology.
Risk evaluation with enhaced covariance matrix
Urbanowicz, K; Richmond, P; Holyst, Janusz A.; Richmond, Peter; Urbanowicz, Krzysztof
2006-01-01
We propose a route for the evaluation of risk based on a transformation of the covariance matrix. The approach uses a `potential' or `objective' function. This allows us to rescale data from diferent assets (or sources) such that each set then has similar statistical properties in terms of their probability distributions. The method is tested using historical data from both the New York and Warsaw Stock Exchanges.
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
Covariant quantization of the CBS superparticle
Grassi, P. A.; Policastro, G.; Porrati, M.
2001-07-01
The quantization of the Casalbuoni-Brink-Schwarz superparticle is performed in an explicitly covariant way using the antibracket formalism. Since an infinite number of ghost fields are required, within a suitable off-shell twistor-like formalism, we are able to fix the gauge of each ghost sector without modifying the physical content of the theory. The computation reveals that the antibracket cohomology contains only the physical degrees of freedom.
Torsion and geometrostasis in covariant superstrings
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.
ANL Critical Assembly Covariance Matrix Generation
McKnight, Richard D. [Argonne National Lab. (ANL), Argonne, IL (United States); Grimm, Karl N. [Argonne National Lab. (ANL), Argonne, IL (United States)
2014-01-15
This report discusses the generation of a covariance matrix for selected critical assemblies that were carried out by Argonne National Laboratory (ANL) using four critical facilities-all of which are now decommissioned. The four different ANL critical facilities are: ZPR-3 located at ANL-West (now Idaho National Laboratory- INL), ZPR-6 and ZPR-9 located at ANL-East (Illinois) and ZPPr located at ANL-West.
Covariant Calculus for Effective String Theories
Dass, N. D. Hari; Matlock, Peter
2007-01-01
A covariant calculus for the construction of effective string theories is developed. Effective string theory, describing quantum string-like excitations in arbitrary dimension, has in the past been constructed using the principles of conformal field theory, but not in a systematic way. Using the freedom of choice of field definition, a particular field definition is made in a systematic way to allow an explicit construction of effective string theories with manifest exact conformal symmetry. ...
How covariant is the galaxy luminosity function?
Smith, Robert E
2012-01-01
We investigate the error properties of certain galaxy luminosity function (GLF) estimators. Using a cluster expansion of the density field, we show how, for both volume and flux limited samples, the GLF estimates are covariant. The covariance matrix can be decomposed into three pieces: a diagonal term arising from Poisson noise; a sample variance term arising from large-scale structure in the survey volume; an occupancy covariance term arising due to galaxies of different luminosities inhabiting the same cluster. To evaluate the theory one needs: the mass function and bias of clusters, and the conditional luminosity function (CLF). We use a semi-analytic model (SAM) galaxy catalogue from the Millennium run N-body simulation and the CLF of Yang et al. (2003) to explore these effects. The GLF estimates from the SAM and the CLF qualitatively reproduce results from the 2dFGRS. We also measure the luminosity dependence of clustering in the SAM and find reasonable agreement with 2dFGRS results for bright galaxies. ...
Development of covariance capabilities in EMPIRE code
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.
Neutron Multiplicity: LANL W Covariance Matrix for Curve Fitting
Wendelberger, James G. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2016-12-08
In neutron multiplicity counting one may fit a curve by minimizing an objective function, χ$2\\atop{n}$. The objective function includes the inverse of an n by n matrix of covariances, W. The inverse of the W matrix has a closed form solution. In addition W^{-1} is a tri-diagonal matrix. The closed form and tridiagonal nature allows for a simpler expression of the objective function χ$2\\atop{n}$. Minimization of this simpler expression will provide the optimal parameters for the fitted curve.
Covariance of Light-Front Models Pair Current
Pacheco-Bicudo-Cabral de Melo, J; Naus, H W L; Sauer, P U
1999-01-01
We compute the "+" component of the electromagnetic current of a composite spin-one two-fermion system for vanishing momentum transfer component $q^+=q^0+q^3$. In particular, we extract the nonvanishing pair production amplitude on the light-front. It is a consequence of the longitudinal zero momentum mode, contributing to the light-front current in the Breit-frame. The covariance of the current is violated, if such pair terms are not included in its matrix elements. We illustrate our discussion with some numerical examples.
Small area estimation with covariates perturbed for disclosure limitation
Silvia Polettini
2015-03-01
Full Text Available We exploit the connections between measurement error and data perturbation for disclosure limitation in the context of small area estimation. Our starting point is the model in Ybarra and Lohr (2008, where some of the covariates (all continuous are measured with error. Using a fully Bayesian approach, we extend the aforementioned model including continuous and categorical auxiliary variables, both possibily perturbed by disclosure limitation methods, with masking distributions fixed according to the assumed protection mechanism. In order to investigate the feasibility of the proposed method, we conduct a simulation study exploring the effect of different post-randomization scenarios on the small area model.
Performance evaluation of sensor allocation algorithm based on covariance control
无
2005-01-01
The covariance control capability of sensor allocation algorithms based on covariance control strategy is an important index to evaluate the performance of these algorithms. Owing to lack of standard performance metric indices to evaluate covariance control capability, sensor allocation ratio, etc, there are no guides to follow in the design procedure of sensor allocation algorithm in practical applications. To meet these demands, three quantified performance metric indices are presented, which are average covariance misadjustment quantity (ACMQ), average sensor allocation ratio (ASAR) and matrix metric influence factor (MMIF), where ACMQ, ASAR and MMIF quantify the covariance control capability, the usage of sensor resources and the robustness of sensor allocation algorithm, respectively. Meanwhile, a covariance adaptive sensor allocation algorithm based on a new objective function is proposed to improve the covariance control capability of the algorithm based on information gain. The experiment results show that the proposed algorithm have the advantage over the preceding sensor allocation algorithm in covariance control capability and robustness.
Covariant equations for the NN-πNN system
Phillips, D. R.; Afnan, I. R.
1995-05-01
We explain the deficiencies of the current NN-πNN equations, sketch the derivation of a set of covariant NN-πNN equations and describe the ways in which these equations differ from previous sets of covariant equations.
Symmetry and Covariance of Non-relativistic Quantum Mechanics
Omote, Minoru; kamefuchi, Susumu
2000-01-01
On the basis of a 5-dimensional form of space-time transformations non-relativistic quantum mechanics is reformulated in a manifestly covariant manner. The resulting covariance resembles that of the conventional relativistic quantum mechanics.
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.
Multilevel covariance regression with correlated random effects in the mean and variance structure.
Quintero, Adrian; Lesaffre, Emmanuel
2017-09-01
Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. The implied conditional covariance function can be different across clusters as a result of the random effect in the variance structure. In addition, allowing for correlation between the random intercepts in the mean and covariance makes the model convenient for skewedly distributed responses. Furthermore, it permits us to analyse directly the relation between the mean response level and the variability in each cluster. Parameter estimation is carried out via Gibbs sampling. We compare the performance of our model to other covariance modelling approaches in a simulation study. Finally, the proposed model is applied to the RN4CAST dataset to identify the variables that impact burnout of nurses in Belgium. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Donegan, Sarah; Williams, Lisa; Tudur-Smith, Catrin
2015-01-01
Background Treatment by covariate interactions can be explored in reviews using interaction analyses (e.g., subgroup analysis). Such analyses can provide information on how the covariate modifies the treatment effect and is an important methodological approach for personalising medicine. Guidance exists regarding how to apply such analyses but little is known about whether authors follow the guidance. Methods Using published recommendations, we developed criteria to assess how well interaction analyses were designed, applied, interpreted, and reported. The Cochrane Database of Systematic Reviews was searched (8th August 2013). We applied the criteria to the most recently published review, with an accessible protocol, for each Cochrane Review Group. We excluded review updates, diagnostic test accuracy reviews, withdrawn reviews, and overviews of reviews. Data were summarised regarding reviews, covariates, and analyses. Results Each of the 52 included reviews planned or did interaction analyses; 51 reviews (98%) planned analyses and 33 reviews (63%) applied analyses. The type of analysis planned and the type subsequently applied (e.g., sensitivity or subgroup analysis) was discrepant in 24 reviews (46%). No review reported how or why each covariate had been chosen; 22 reviews (42%) did state each covariate a priori in the protocol but no review identified each post-hoc covariate as such. Eleven reviews (21%) mentioned five covariates or less. One review reported planning to use a method to detect interactions (i.e., interaction test) for each covariate; another review reported applying the method for each covariate. Regarding interpretation, only one review reported whether an interaction was detected for each covariate and no review discussed the importance, or plausibility, of the results, or the possibility of confounding for each covariate. Conclusions Interaction analyses in Cochrane Reviews can be substantially improved. The proposed criteria can be used to
Sarah Donegan
Full Text Available Treatment by covariate interactions can be explored in reviews using interaction analyses (e.g., subgroup analysis. Such analyses can provide information on how the covariate modifies the treatment effect and is an important methodological approach for personalising medicine. Guidance exists regarding how to apply such analyses but little is known about whether authors follow the guidance.Using published recommendations, we developed criteria to assess how well interaction analyses were designed, applied, interpreted, and reported. The Cochrane Database of Systematic Reviews was searched (8th August 2013. We applied the criteria to the most recently published review, with an accessible protocol, for each Cochrane Review Group. We excluded review updates, diagnostic test accuracy reviews, withdrawn reviews, and overviews of reviews. Data were summarised regarding reviews, covariates, and analyses.Each of the 52 included reviews planned or did interaction analyses; 51 reviews (98% planned analyses and 33 reviews (63% applied analyses. The type of analysis planned and the type subsequently applied (e.g., sensitivity or subgroup analysis was discrepant in 24 reviews (46%. No review reported how or why each covariate had been chosen; 22 reviews (42% did state each covariate a priori in the protocol but no review identified each post-hoc covariate as such. Eleven reviews (21% mentioned five covariates or less. One review reported planning to use a method to detect interactions (i.e., interaction test for each covariate; another review reported applying the method for each covariate. Regarding interpretation, only one review reported whether an interaction was detected for each covariate and no review discussed the importance, or plausibility, of the results, or the possibility of confounding for each covariate.Interaction analyses in Cochrane Reviews can be substantially improved. The proposed criteria can be used to help guide the reporting and
Adaptive automatic sleep stage classification under covariate shift.
Khalighi, Sirvan; Sousa, Teresa; Nunes, Urbano
2012-01-01
Current automatic sleep stage classification (ASSC) methods that rely on polysomnographic (PSG) signals suffer from inter-subject differences that make them unreliable in facing with new and different subjects. A novel adaptive sleep scoring method based on unsupervised domain adaptation, aiming to be robust to inter-subject variability, is proposed. We assume that the sleep quality variants follow a covariate shift model, where only the sleep features distribution change in the training and test phases. The maximum overlap discrete wavelet transform (MODWT) is applied to extract relevant features from EEG, EOG and EMG signals. A set of significant features are selected by minimum-redundancy maximum-relevance (mRMR) which is a powerful feature selection method. Finally, an instance-weighting method, namely the importance weighted kernel logistic regression (IWKLR) is applied for the purpose of obtaining adaptation in classification. The classification results using leave one out cross-validation (LOOCV), show that the proposed method performs at the state-of-the art in the field of ASSC.
Accurate Interatomic Force Fields via Machine Learning with Covariant Kernels
Glielmo, Aldo; De Vita, Alessandro
2016-01-01
We present a novel scheme to accurately predict atomic forces as vector quantities, rather than sets of scalar components, by Gaussian Process (GP) Regression. This is based on matrix-valued kernel functions, to which we impose that the predicted force rotates with the target configuration and is independent of any rotations applied to the configuration database entries. We show that such "covariant" GP kernels can be obtained by integration over the elements of the rotation group SO(d) for the relevant dimensionality d. Remarkably, in specific cases the integration can be carried out analytically and yields a conservative force field that can be recast into a pair interaction form. Finally, we show that restricting the integration to a summation over the elements of a finite point group relevant to the target system is sufficient to recover an accurate GP. The accuracy of our kernels in predicting quantum-mechanical forces in real materials is investigated by tests on pure and defective Ni and Fe crystalline...
Accurate interatomic force fields via machine learning with covariant kernels
Glielmo, Aldo; Sollich, Peter; De Vita, Alessandro
2017-06-01
We present a novel scheme to accurately predict atomic forces as vector quantities, rather than sets of scalar components, by Gaussian process (GP) regression. This is based on matrix-valued kernel functions, on which we impose the requirements that the predicted force rotates with the target configuration and is independent of any rotations applied to the configuration database entries. We show that such covariant GP kernels can be obtained by integration over the elements of the rotation group SO (d ) for the relevant dimensionality d . Remarkably, in specific cases the integration can be carried out analytically and yields a conservative force field that can be recast into a pair interaction form. Finally, we show that restricting the integration to a summation over the elements of a finite point group relevant to the target system is sufficient to recover an accurate GP. The accuracy of our kernels in predicting quantum-mechanical forces in real materials is investigated by tests on pure and defective Ni, Fe, and Si crystalline systems.
Global symplectic potentials on the Witten covariant phase space for bosonic extendons
Cartas-Fuentevilla, R
2002-01-01
It is proved that the projections of the deformation vector field, normal and tangential to the worldsheet manifold swept out by Dirac-Nambu-Goto bosonic extendons propagating in a curved background, play the role of {\\it global} symplectic potentials on the corresponding Witten covariant phase space. It is also proved that the {\\it presymplectic} structure obtained from such potentials by direct exterior derivation, has not components tangent to the action of the relevant diffeomorphisms group of the theory.
Models with orthogonal block structure, with diagonal blockwise variance-covariance matrices
Carvalho, Francisco; Mexia, João T.; Covas, Ricardo
2017-07-01
We intend to show that in the family of models with orthogonal block structure, OBS, we may single out those with blockwise diagonal variance-covariance matrices, DOBS. Namely we show that for every model with observation vector y with OBS, there is a model y °=P y , with P orthogonal which is DOBS and that the estimation of relevant parameters may be carried out for y ° .
On the Problem of Permissible Covariance and Variogram Models
Christakos, George
1984-02-01
The covariance and variogram models (ordinary or generalized) are important statistical tools used in various estimation and simulation techniques which have been recently applied to diverse hydrologic problems. For example, the efficacy of kriging, a method for interpolating, filtering, or averaging spatial phenomena, depends, to a large extent, on the covariance or variogram model chosen. The aim of this article is to provide the users of these techniques with convenient criteria that may help them to judge whether a function which arises in a particular problem, and is not included among the known covariance or variogram models, is permissible as such a model. This is done by investigating the properties of the candidate model in both the space and frequency domains. In the present article this investigation covers stationary random functions as well as intrinsic random functions (i.e., nonstationary functions for which increments of some order are stationary). Then, based on the theoretical results obtained, a procedure is outlined and successfully applied to a number of candidate models. In order to give to this procedure a more practical context, we employ "stereological" equations that essentially transfer the investigations to one-dimensional space, together with approximations in terms of polygonal functions and Fourier-Bessel series expansions. There are many benefits and applications of such a procedure. Polygonal models can be fit arbitrarily closely to the data. Also, the approximation of a particular model in the frequency domain by a Fourier-Bessel series expansion can be very effective. This is shown by theory and by example.
Quantum energy inequalities and local covariance II: categorical formulation
Fewster, Christopher J.
2007-11-01
We formulate quantum energy inequalities (QEIs) in the framework of locally covariant quantum field theory developed by Brunetti, Fredenhagen and Verch, which is based on notions taken from category theory. This leads to a new viewpoint on the QEIs, and also to the identification of a new structural property of locally covariant quantum field theory, which we call local physical equivalence. Covariant formulations of the numerical range and spectrum of locally covariant fields are given and investigated, and a new algebra of fields is identified, in which fields are treated independently of their realisation on particular spacetimes and manifestly covariant versions of the functional calculus may be formulated.
Gallilei covariant quantum mechanics in electromagnetic fields
H. E. Wilhelm
1985-01-01
Full Text Available A formulation of the quantum mechanics of charged particles in time-dependent electromagnetic fields is presented, in which both the Schroedinger equation and wave equations for the electromagnetic potentials are Galilei covariant, it is shown that the Galilean relativity principle leads to the introduction of the electromagnetic substratum in which the matter and electromagnetic waves propagate. The electromagnetic substratum effects are quantitatively significant for quantum mechanics in reference frames, in which the substratum velocity w is in magnitude comparable with the velocity of light c. The electromagnetic substratum velocity w occurs explicitly in the wave equations for the electromagnetic potentials but not in the Schroedinger equation.
Inferring Meta-covariates in Classification
Harris, Keith; McMillan, Lisa; Girolami, Mark
This paper develops an alternative method for gene selection that combines model based clustering and binary classification. By averaging the covariates within the clusters obtained from model based clustering, we define “meta-covariates” and use them to build a probit regression model, thereby selecting clusters of similarly behaving genes, aiding interpretation. This simultaneous learning task is accomplished by an EM algorithm that optimises a single likelihood function which rewards good performance at both classification and clustering. We explore the performance of our methodology on a well known leukaemia dataset and use the Gene Ontology to interpret our results.
Minimal covariant observables identifying all pure states
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.
Radiative Transfer in Special Relativity: Covariance
Duque, Mauricio; Duque, Carlos
2007-01-01
The purpose is to introduce in a clear and direct way the students of undergraduate courses in physics and/or astronomy to the subject of radiative transfer. A pedagogical revision is made in order to obtain the radiative transfer equation, its restrictions and the different types of interactions present between the radiation and the matter. Because in the classical literature about radiative transfer the covariance is not fully developed, we show in an explicit manner detail calculations and then we discuss the relativistic effects.
Covariant harmonic oscillators and coupled harmonic oscillators
Han, Daesoo; Kim, Young S.; Noz, Marilyn E.
1995-01-01
It is shown that the system of two coupled harmonic oscillators shares the basic symmetry properties with the covariant harmonic oscillator formalism which provides a concise description of the basic features of relativistic hadronic features observed in high-energy laboratories. It is shown also that the coupled oscillator system has the SL(4,r) symmetry in classical mechanics, while the present formulation of quantum mechanics can accommodate only the Sp(4,r) portion of the SL(4,r) symmetry. The possible role of the SL(4,r) symmetry in quantum mechanics is discussed.
Development and Testing of Neutron Cross Section Covariance Data for SCALE 6.2
Marshall, William BJ J [ORNL; Williams, Mark L [ORNL; Wiarda, Dorothea [ORNL; Rearden, Bradley T [ORNL; Dunn, Michael E [ORNL; Mueller, Don [ORNL; Clarity, Justin B [ORNL; Jones, Elizabeth L [ORNL
2015-01-01
Neutron cross-section covariance data are essential for many sensitivity/uncertainty and uncertainty quantification assessments performed both within the TSUNAMI suite and more broadly throughout the SCALE code system. The release of ENDF/B-VII.1 included a more complete set of neutron cross-section covariance data: these data form the basis for a new cross-section covariance library to be released in SCALE 6.2. A range of testing is conducted to investigate the properties of these covariance data and ensure that the data are reasonable. These tests include examination of the uncertainty in critical experiment benchmark model k_{eff} values due to nuclear data uncertainties, as well as similarity assessments of irradiated pressurized water reactor (PWR) and boiling water reactor (BWR) fuel with suites of critical experiments. The contents of the new covariance library, the testing performed, and the behavior of the new covariance data are described in this paper. The neutron cross-section covariances can be combined with a sensitivity data file generated using the TSUNAMI suite of codes within SCALE to determine the uncertainty in system k_{eff} caused by nuclear data uncertainties. The Verified, Archived Library of Inputs and Data (VALID) maintained at Oak Ridge National Laboratory (ORNL) contains over 400 critical experiment benchmark models, and sensitivity data are generated for each of these models. The nuclear data uncertainty in k_{eff} is generated for each experiment, and the resulting uncertainties are tabulated and compared to the differences in measured and calculated results. The magnitude of the uncertainty for categories of nuclides (such as actinides, fission products, and structural materials) is calculated for irradiated PWR and BWR fuel to quantify the effect of covariance library changes between the SCALE 6.1 and 6.2 libraries. One of the primary applications of sensitivity/uncertainty methods within SCALE is the
Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data
Jun, Sung C [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Plis, Sergey M [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Ranken, Doug M [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Schmidt, David M [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)
2006-11-07
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
Evaluation of covariance and information performance measures for dynamic object tracking
Yang, Chun; Blasch, Erik; Douville, Phil; Kaplan, Lance; Qiu, Di
2010-04-01
In surveillance and reconnaissance applications, dynamic objects are dynamically followed by track filters with sequential measurements. There are two popular implementations of tracking filters: one is the covariance or Kalman filter and the other is the information filter. Evaluation of tracking filters is important in performance optimization not only for tracking filter design but also for resource management. Typically, the information matrix is the inverse of the covariance matrix. The covariance filter-based approaches attempt to minimize the covariance matrix-based scalar indexes whereas the information filter-based methods aim at maximizing the information matrix-based scalar indexes. Such scalar performance measures include the trace, determinant, norms (1-norm, 2-norm, infinite-norm, and Forbenius norm), and eigenstructure of the covariance matrix or the information matrix and their variants. One natural question to ask is if the scalar track filter performance measures applied to the covariance matrix are equivalent to those applied to the information matrix? In this paper we show most of the scalar performance indexes are equivalent yet some are not. As a result, the indexes if used improperly would provide an "optimized" solution but in the wrong sense relative to track accuracy. The simulation indicated that all the seven indexes were successful when applied to the covariance matrix. However, the failed indexes for the information filter include the trace and the four norms (as defined in MATLAB) of the information matrix. Nevertheless, the determinant and the properly selected eigenvalue of the information matrix were successful to select the optimal sensor update configuration. The evaluation analysis of track measures can serve as a guideline to determine the suitability of performance measures for tracking filter design and resource management.
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).
Covariant Entropy Bound and Padmanabhan's Emergent Paradigm
Hadi, H; Darabi, F
2016-01-01
The covariant entropy conjecture is invariant under time reversal and consequently its origin must be statistical rather than thermodynamical. This may impose a fundamental constraint on the number of degrees of freedom in nature. Indeed, the covariant entropy bound imposes an upper entropy bound for any physical system. Considering a cosmological system, we show that Padmanabhan's emergent paradigm, which indicates that the emergence of cosmic space is due to the discrepancy between the surface and bulk degrees of freedom, leads to a lower entropy bound. The lower and upper entropy bounds may coincide on the apparent horizon for the radiation field and dark energy with the equations of state $\\omega=\\frac{1}{3}$ and $\\omega=-1$, respectively. Moreover, the maximal entropy inside the apparent horizon occurs when it is filled completely by the radiation field or dark energy. It turns out that for dark energy case (pure de Sitter space)\\ the holographic principle is satisfied in the sense that the number of deg...
Stochastic precipitation generator with hidden state covariates
Kim, Yongku; Lee, GyuWon
2017-08-01
Time series of daily weather such as precipitation, minimum temperature and maximum temperature are commonly required for various fields. Stochastic weather generators constitute one of the techniques to produce synthetic daily weather. The recently introduced approach for stochastic weather generators is based on generalized linear modeling (GLM) with covariates to account for seasonality and teleconnections (e.g., with the El Niño). In general, stochastic weather generators tend to underestimate the observed interannual variance of seasonally aggregated variables. To reduce this overdispersion, we incorporated time series of seasonal dry/wet indicators in the GLM weather generator as covariates. These seasonal time series were local (or global) decodings obtained by a hidden Markov model of seasonal total precipitation and implemented in the weather generator. The proposed method is applied to time series of daily weather from Seoul, Korea and Pergamino, Argentina. This method provides a straightforward translation of the uncertainty of the seasonal forecast to the corresponding conditional daily weather statistics.
Diallo, Thierno M O; Morin, Alexandre J S; Lu, HuiZhong
2017-03-01
This article evaluates the impact of partial or total covariate inclusion or exclusion on the class enumeration performance of growth mixture models (GMMs). Study 1 examines the effect of including an inactive covariate when the population model is specified without covariates. Study 2 examines the case in which the population model is specified with 2 covariates influencing only the class membership. Study 3 examines a population model including 2 covariates influencing the class membership and the growth factors. In all studies, we contrast the accuracy of various indicators to correctly identify the number of latent classes as a function of different design conditions (sample size, mixing ratio, invariance or noninvariance of the variance-covariance matrix, class separation, and correlations between the covariates in Studies 2 and 3) and covariate specification (exclusion, partial or total inclusion as influencing class membership, partial or total inclusion as influencing class membership, and the growth factors in a class-invariant or class-varying manner). The accuracy of the indicators shows important variation across studies, indicators, design conditions, and specification of the covariates effects. However, the results suggest that the GMM class enumeration process should be conducted without covariates, and should rely mostly on the Bayesian information criterion (BIC) and consistent Akaike information criterion (CAIC) as the most reliable indicators under conditions of high class separation (as indicated by higher entropy), versus the sample size adjusted BIC or CAIC (SBIC, SCAIC) and bootstrapped likelihood ratio test (BLRT) under conditions of low class separation (indicated by lower entropy). (PsycINFO Database Record
Why relevance theory is relevant for lexicography
Bothma, Theo; Tarp, Sven
2014-01-01
, socio-cognitive and affective relevance. It then shows, at the hand of examples, why relevance is important from a user perspective in the extra-lexicographical pre- and post-consultation phases and in the intra-lexicographical consultation phase. It defines an additional type of subjective relevance...... that is very important for lexicography as well as for information science, viz. functional relevance. Since all lexicographic work is ultimately aimed at satisfying users’ information needs, the article then discusses why the lexicographer should take note of all these types of relevance when planning a new...... dictionary project, identifying new tasks and responsibilities of the modern lexicographer. The article furthermore discusses how relevance theory impacts on teaching dictionary culture and reference skills. By integrating insights from lexicography and information science, the article contributes to new...
Urban eddy covariance measurements reveal significant missing NOx emissions in Central Europe.
Karl, T; Graus, M; Striednig, M; Lamprecht, C; Hammerle, A; Wohlfahrt, G; Held, A; von der Heyden, L; Deventer, M J; Krismer, A; Haun, C; Feichter, R; Lee, J
2017-05-30
Nitrogen oxide (NOx) pollution is emerging as a primary environmental concern across Europe. While some large European metropolitan areas are already in breach of EU safety limits for NO2, this phenomenon does not seem to be only restricted to large industrialized areas anymore. Many smaller scale populated agglomerations including their surrounding rural areas are seeing frequent NO2 concentration violations. The question of a quantitative understanding of different NOx emission sources is therefore of immanent relevance for climate and air chemistry models as well as air pollution management and health. Here we report simultaneous eddy covariance flux measurements of NOx, CO2, CO and non methane volatile organic compound tracers in a city that might be considered representative for Central Europe and the greater Alpine region. Our data show that NOx fluxes are largely at variance with modelled emission projections, suggesting an appreciable underestimation of the traffic related atmospheric NOx input in Europe, comparable to the weekend-weekday effect, which locally changes ozone production rates by 40%.
Modeling the angular correlation function and its full covariance in Photometric Galaxy Surveys
Crocce, Martin; Gaztañaga, Enrique
2010-01-01
Near future cosmology will see the advent of wide area photometric galaxy surveys, like the Dark Energy Survey (DES), that extent to high redshifts (z ~ 1 - 2) but with poor radial distance resolution. In such cases splitting the data into redshift bins and using the angular correlation function $w(\\theta)$, or the $C_{\\ell}$ power spectrum, will become the standard approach to extract cosmological information or to study the nature of dark energy through the Baryon Acoustic Oscillations (BAO) probe. In this work we present a detailed model for $w(\\theta)$ at large scales as a function of redshift and bin width, including all relevant effects, namely nonlinear gravitational clustering, bias, redshift space distortions and photo-z uncertainties. We also present a model for the full covariance matrix characterizing the angular correlation measurements, that takes into account the same effects as for $w(\\theta)$ and also the possibility of a shot-noise component and partial sky coverage. Provided with a large vo...
Identifying sources of uncertainty from the inter-species covariance of measurement errors.
Hyslop, Nicole P; White, Warren H
2011-05-01
A standard metric of measurement precision in environmental monitoring is the variance of differences between duplicate (collocated) samples. With duplicate measurements of multiple species, we can extend this variance analysis to include the interspecies covariance of differences between duplicate samples; these covariances can provide clues about the sources of error. We illustrate the potential of such an analysis with atmospheric aerosol measurements from two national air quality monitoring networks: Interagency Monitoring of Protected Visual Environments (IMPROVE) and Speciation Trends Network (STN). These aerosol "speciation" networks provide the multivariate data sets needed to characterize error covariance by operating duplicate samplers at several of their monitoring locations and analyzing both the collected aerosol samples for multiple species. We observe covariance among the measurement differences for multiple species in both networks. The covariance among measurement differences for soil-derived elements suggests an error associated with the particle size discrimination step in sampling, which is not currently included in either network's uncertainty estimates. The multivariate statistical analyses of aerosol speciation data performed by standard source apportionment models assume that measurement errors in different species are independent of each other; the present analysis invalidates this assumption for several species measured by IMPROVE and STN.
Estimating the power spectrum covariance matrix with fewer mock samples
Pearson, David W
2015-01-01
The covariance matrices of power-spectrum (P(k)) measurements from galaxy surveys are difficult to compute theoretically. The current best practice is to estimate covariance matrices by computing a sample covariance of a large number of mock catalogues. The next generation of galaxy surveys will require thousands of large volume mocks to determine the covariance matrices to desired accuracy. The errors in the inverse covariance matrix are larger and scale with the number of P(k) bins, making the problem even more acute. We develop a method of estimating covariance matrices using a theoretically justified, few-parameter model, calibrated with mock catalogues. Using a set of 600 BOSS DR11 mock catalogues, we show that a seven parameter model is sufficient to fit the covariance matrix of BOSS DR11 P(k) measurements. The covariance computed with this method is better than the sample covariance at any number of mocks and only ~100 mocks are required for it to fully converge and the inverse covariance matrix conver...
Holographic bound in covariant loop quantum gravity
Tamaki, Takashi
2016-01-01
We investigate puncture statistics based on the covariant area spectrum in loop quantum gravity. First, we consider Maxwell-Boltzmann statistics with a Gibbs factor for punctures. We establish formulae which relate physical quantities such as horizon area to the parameter characterizing holographic degrees of freedom. We also perform numerical calculations and obtain consistency with these formulae. These results tell us that the holographic bound is satisfied in the large area limit and correction term of the entropy-area law can be proportional to the logarithm of the horizon area. Second, we also consider Bose-Einstein statistics and show that the above formulae are also useful in this case. By applying the formulae, we can understand intrinsic features of Bose-Einstein condensate which corresponds to the case when the horizon area almost consists of punctures in the ground state. When this phenomena occurs, the area is approximately constant against the parameter characterizing the temperature. When this ...
The covariance of GPS coordinates and frames
Lachièze-Rey, M
2006-01-01
We explore, in the general relativistic context, the properties of the recently introduced GPS coordinates, as well as those of the associated frames and coframes. 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 [four-]velocity and (iii) the components of the metric in the GPS frame. This provides to this system an unique value both for conceptual discussion (no frame dependence) and for practical use (involved quantities are directly measurable): localisation, motion monitoring, astrometry, cosmography, tests of gravitation theories. We show explicitly, in the general relativistic context, how an observer may estimate its 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; a...
Covariant Hyperbolization of Force-free Electrodynamics
Carrasco, Federico
2016-01-01
Force-Free Flectrodynamics (FFE) is a non-linear system of equations modeling the evolution of the electromagnetic field, in the presence of a magnetically dominated relativistic plasma. This configuration arises on several astrophysical scenarios, which represent exciting laboratories to understand physics in extreme regimes. We show that this system, when restricted to the correct constraint submanifold, is symmetric hyperbolic. In numerical applications is not feasible to keep the system in that submanifold, and so, it is necessary to analyze its structure first in the tangent space of that submanifold and then in a whole neighborhood of it. As already shown by Pfeiffer, a direct (or naive) formulation of this system (in the whole tangent space) results in a weakly hyperbolic system of evolution equations for which well-possednes for the initial value formulation does not follows. Using the generalized symmetric hyperbolic formalism due to Geroch, we introduce here a covariant hyperbolization for the FFE s...
Supergeometry in locally covariant quantum field theory
Hack, Thomas-Paul; Schenkel, Alexander
2015-01-01
In this paper we analyze supergeometric locally covariant quantum field theories. We develop suitable categories SLoc of super-Cartan supermanifolds, which generalize Lorentz manifolds in ordinary quantum field theory, and show that, starting from a few representation theoretic and geometric data, one can construct a functor A : SLoc --> S*Alg to the category of super-*-algebras which can be interpreted as a non-interacting super-quantum field theory. This construction turns out to disregard supersymmetry transformations as the morphism sets in the above categories are too small. We then solve this problem by using techniques from enriched category theory, which allows us to replace the morphism sets by suitable morphism supersets that contain supersymmetry transformations as their higher superpoints. We construct super-quantum field theories in terms of enriched functors eA : eSLoc --> eS*Alg between the enriched categories and show that supersymmetry transformations are appropriately described within the en...
Covariant non-commutative space–time
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.
Variance and covariance of accumulated displacement estimates.
Bayer, Matthew; Hall, Timothy J
2013-04-01
Tracking large deformations in tissue using ultrasound can enable the reconstruction of nonlinear elastic parameters, but poses a challenge to displacement estimation algorithms. Such large deformations have to be broken up into steps, each of which contributes an estimation error to the final accumulated displacement map. The work reported here measured the error variance for single-step and accumulated displacement estimates using one-dimensional numerical simulations of ultrasound echo signals, subjected to tissue strain and electronic noise. The covariance between accumulation steps was also computed. These simulations show that errors due to electronic noise are negatively correlated between steps, and therefore accumulate slowly, whereas errors due to tissue deformation are positively correlated and accumulate quickly. For reasonably low electronic noise levels, the error variance in the accumulated displacement estimates is remarkably constant as a function of step size, but increases with the length of the tracking kernel.
Noncommutative Spacetime Symmetries from Covariant Quantum Mechanics
Alessandro Moia
2017-01-01
Full Text Available In the last decades, noncommutative spacetimes and their deformed relativistic symmetries have usually been studied in the context of field theory, replacing the ordinary Minkowski background with an algebra of noncommutative coordinates. However, spacetime noncommutativity can also be introduced into single-particle covariant quantum mechanics, replacing the commuting operators representing the particle’s spacetime coordinates with noncommuting ones. In this paper, we provide a full characterization of a wide class of physically sensible single-particle noncommutative spacetime models and the associated deformed relativistic symmetries. In particular, we prove that they can all be obtained from the standard Minkowski model and the usual Poincaré transformations via a suitable change of variables. Contrary to previous studies, we find that spacetime noncommutativity does not affect the dispersion relation of a relativistic quantum particle, but only the transformation properties of its spacetime coordinates under translations and Lorentz transformations.
Multisymplectic formalism and the covariant phase
Hélein, Frédéric
2011-01-01
The formulation of a relativistic dynamical problem as a system of Hamilton equations by respecting the principles of Relativity is a delicate task, because in their classical form the Hamilton equations require the use of a time coordinate, which of course contradicts the Relativity. Two interesting solutions have been proposed during the last century: the covariant phase space and the multisymplectic formalism. These two approaches were inspired at the beginning by different points of view. However, as shown by works by Kijowski-Szczyrba, Forger-Romero and Vitagliano, a synthetic vision of the two theories leads probably to the most satisfactory answer to the basic question of understanding the Hamiltonian structure of relativistic fields theory.
Flavour Covariant Formalism for Resonant Leptogenesis
Dev, P S Bhupal; Pilaftsis, Apostolos; Teresi, Daniele
2014-01-01
We present a fully flavour-covariant formalism for transport phenomena and apply it to study the flavour-dynamics of Resonant Leptogenesis (RL). We show that this formalism provides a complete and unified description of RL, consistently accounting for three distinct physical phenomena: (i) resonant mixing and (ii) coherent oscillations between different heavy-neutrino flavours, as well as (iii) quantum decoherence effects in the charged-lepton sector. We describe the necessary emergence of higher-rank tensors in flavour space, arising from the unitarity cuts of partial self-energies. Finally, we illustrate the importance of this formalism within a minimal Resonant $\\tau$-Genesis model by showing that, with the inclusion of all flavour effects in a consistent way, the final lepton asymmetry can be enhanced by up to an order of magnitude, when compared to previous partially flavour-dependent treatments.
McGloin, Ryan; McGowan, Hamish; McJannet, David; Cook, Freeman; Sogachev, Andrey; Burn, Stewart
2014-01-01
Accurate quantification of evaporation from small water storages is essential for water management and planning, particularly in water-scarce regions. In order to ascertain suitable methods for direct measurement of evaporation from small water bodies, this study presents a comparison of eddy covariance and scintillometry measurements from a reservoir in southeast Queensland, Australia. The work presented expands on a short study presented by McJannet et al. (2011) to include comparisons of eddy covariance measurements and scintillometer-derived predictions of surface energy fluxes under a wide range of seasonal weather conditions. In this study, analysis was undertaken to ascertain whether important theoretical assumptions required for both techniques are valid in the complex environment of a small reservoir. Statistical comparison, energy balance closure, and the relationship between evaporation measurements and key environmental controls were used to compare the results of the two techniques. Reasonable agreement was shown between the sensible heat flux measurements from eddy covariance and scintillometry, while scintillometer-derived estimates of latent heat flux were approximately 21% greater than eddy covariance measurements. We suggest possible reasons for this difference and provide recommendations for further research for improving measurements of surface energy fluxes over small water bodies using eddy covariance and scintillometry.
Evolutionary evidence for alternative structure in RNA sequence co-variation.
Justin Ritz
Full Text Available Sequence conservation and co-variation of base pairs are hallmarks of structured RNAs. For certain RNAs (e.g. riboswitches, a single sequence must adopt at least two alternative secondary structures to effectively regulate the message. If alternative secondary structures are important to the function of an RNA, we expect to observe evolutionary co-variation supporting multiple conformations. We set out to characterize the evolutionary co-variation supporting alternative conformations in riboswitches to determine the extent to which alternative secondary structures are conserved. We found strong co-variation support for the terminator, P1, and anti-terminator stems in the purine riboswitch by extending alignments to include terminator sequences. When we performed Boltzmann suboptimal sampling on purine riboswitch sequences with terminators we found that these sequences appear to have evolved to favor specific alternative conformations. We extended our analysis of co-variation to classic alignments of group I/II introns, tRNA, and other classes of riboswitches. In a majority of these RNAs, we found evolutionary evidence for alternative conformations that are compatible with the Boltzmann suboptimal ensemble. Our analyses suggest that alternative conformations are selected for and thus likely play functional roles in even the most structured of RNAs.
Baryon Wave Functions in Covariant Relativistic Quark Models
Dillig, M
2002-01-01
We derive covariant baryon wave functions for arbitrary Lorentz boosts. Modeling baryons as quark-diquark systems, we reduce their manifestly covariant Bethe-Salpeter equation to a covariant 3-dimensional form by projecting on the relative quark-diquark energy. Guided by a phenomenological multigluon exchange representation of a covariant confining kernel, we derive for practical applications explicit solutions for harmonic confinement and for the MIT Bag Model. We briefly comment on the interplay of boosts and center-of-mass corrections in relativistic quark models.
Kriging approach for the experimental cross-section covariances estimation
Garlaud A.
2013-03-01
Full Text Available In the classical use of a generalized χ2 to determine the evaluated cross section uncertainty, we need the covariance matrix of the experimental cross sections. The usual propagation error method to estimate the covariances is hardly usable and the lack of data prevents from using the direct empirical estimator. We propose in this paper to apply the kriging method which allows to estimate the covariances via the distances between the points and with some assumptions on the covariance matrix structure. All the results are illustrated with the 2555Mn nucleus measurements.
On the Validity of Covariate Adjustment for Estimating Causal Effects
Shpitser, Ilya; Robins, James M
2012-01-01
Identifying effects of actions (treatments) on outcome variables from observational data and causal assumptions is a fundamental problem in causal inference. This identification is made difficult by the presence of confounders which can be related to both treatment and outcome variables. Confounders are often handled, both in theory and in practice, by adjusting for covariates, in other words considering outcomes conditioned on treatment and covariate values, weighed by probability of observing those covariate values. In this paper, we give a complete graphical criterion for covariate adjustment, which we term the adjustment criterion, and derive some interesting corollaries of the completeness of this criterion.
Relativistic Covariance and Quark-Diquark Wave Functions
Dillig, M
2006-01-01
We derive covariant wave functions for hadrons composed of two constituents for arbitrary Lorentz boosts. Focussing explicitly on baryons as quark-diquark systems, we reduce their manifestly covariant Bethe-Salpeter equation to covariant 3-dimensional forms by projecting on the relative quark-diquark energy. Guided by a phenomenological multi gluon exchange representation of covariant confining kernels, we derive explicit solutions for harmonic confinement and for the MIT Bag Model. We briefly sketch implications of breaking the spherical symmetry of the ground state and the transition from the instant form to the light cone via the infinite momentum frame.
Rotation-Covariant Texture Learning Using Steerable Riesz Wavelets.
Depeursinge, Adrien; Foncubierta-Rodriguez, Antonio; Van de Ville, Dimitri; Muller, Henning
2014-02-01
We propose a texture learning approach that exploits local organizations of scales and directions. First, linear combinations of Riesz wavelets are learned using kernel support vector machines. The resulting texture signatures are modeling optimal class-wise discriminatory properties. The visualization of the obtained signatures allows verifying the visual relevance of the learned concepts. Second, the local orientations of the signatures are optimized to maximize their responses, which is carried out analytically and can still be expressed as a linear combination of the initial steerable Riesz templates. The global process is iteratively repeated to obtain final rotation-covariant texture signatures. Rapid convergence of class-wise signatures is observed, which demonstrates that the instances are projected into a feature space that leverages the local organizations of scales and directions. Experimental evaluation reveals average classification accuracies in the range of 97% to 98% for the Outex_TC_00010, the Outex_TC_00012, and the Contrib_TC_00000 suites for even orders of the Riesz transform, and suggests high robustness to changes in images orientation and illumination. The proposed framework requires no arbitrary choices of scales and directions and is expected to perform well in a large range of computer vision applications.
Lyapunov Exponents and Covariant Vectors for Turbulent Flow Simulations
Blonigan, Patrick; Murman, Scott; Fernandez, Pablo; Wang, Qiqi
2016-11-01
As computational power increases, engineers are beginning to use scale-resolving turbulent flow simulations for applications in which jets, wakes, and separation dominate. However, the chaotic dynamics exhibited by scale-resolving simulations poses problems for the conventional sensitivity analysis and stability analysis approaches that are vital for design and control. Lyapunov analysis is used to study the chaotic behavior of dynamical systems, including flow simulations. Lyapunov exponents are the growth or a decay rate of specific flow field perturbations called the Lyapunov covariant vectors. Recently, the authors have used Lyapunov analysis to study the breakdown in conventional sensitivity analysis and the cost of new shadowing-based sensitivity analysis. The current work reviews Lyapunov analysis and presents new results for a DNS of turbulent channel flow, wall-modeled channel flow, and a DNS of a low pressure turbine blade. Additionally, the implications of these Lyapunov analyses for computing sensitivities of these flow simulations will be discussed.
Orbit Determination Covariance Analysis for the Europa Clipper Mission
Ionasescu, Rodica; Martin-Mur, Tomas; Valerino, Powtawche; Criddle, Kevin; Buffington, Brent; McElrath, Timothy
2014-01-01
A new Jovian satellite tour is proposed by NASA, which would include numerous flybys of the moon Europa, and would explore its potential habitability by characterizing the existence of any water within and beneath Europa's ice shell. This paper describes the results of a covariance study that was undertaken on a sample tour to assess the navigational challenges and capabilities of such a mission from an orbit determination (OD) point of view, and to help establish a delta V budget for the maneuvers needed to keep the spacecraft on the reference trajectory. Additional parametric variations from the baseline case were also investigated. The success of the Europa Clipper mission will depend on the science measurements that it will enable. Meeting the requirements of the instruments onboard the spacecraft is an integral part of this analysis.
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.
Covariant approach of perturbations in Lovelock type brane gravity
Norma, Bagatella-Flores; Miguel, Cruz; Efrain, Rojas
2016-01-01
We develop a covariant scheme to describe the dynamics of small perturbations on Lovelock type branes probing a Minkowski spacetime. The higher-dimensional analogue of the Jacobi equation in this theory becomes a wave type equation for a scalar field $\\Phi$. Whithin this framework, we analyse the stability of spherically symmetric branes with a de Sitter geometry floating in a flat Minkowski spacetime where we find that the Jacobi equation specializes to a Klein-Gordon equation for a scalar field possessing a tachyonic mass. This fact shows that, to some extent, these type of branes share the symmetries of the usual Dirac-Nambu-Goto (DNG) action which is by no means coincidental because the DNG model is the simplest included in the Lovelock type brane gravity.
User's manual for covariance and hypothesis testing program
Parr, J.T.; Bogar, G.P.; Johnson, D.H.
1978-06-01
Statistical computer programs are described which are intended for general usage in evaluating multidimensional feature indices for resource potential. In particular, the computer programs comprise a covariance computation program and a likelihood function evaluation program. These programs have been exercised in this study for geothermal exploration, using as many as 34 selected feature indices from a data base that may include up to 100 distinct indices. It is anticipated that many more indices might be considered simultaneously. Practical limitations occur with large covariances due to numerical errors in computing eigenvalues and eigenvectors. The basic concept of hypothesis testing as formulated in this study is described.
Schur complement inequalities for covariance matrices and monogamy of quantum correlations
Lami, Ludovico; Adesso, Gerardo; Winter, Andreas
2016-01-01
We derive fundamental constraints for the Schur complement of positive matrices, which provide an operator strengthening to recently established information inequalities for quantum covariance matrices, including strong subadditivity. This allows us to prove general results on the monogamy of entanglement and steering quantifiers in continuous variable systems with an arbitrary number of modes per party. A powerful hierarchical relation for correlation measures based on the log-determinant of covariance matrices is further established for all Gaussian states, which has no counterpart among quantities based on the conventional von Neumann entropy.
Parameterization of Copulas and Covariance Decay of Stochastic Processes with Applications
Pumi, Guilherme
2012-01-01
In this work we study the problem of constructing stochastic processes with a predetermined covariance decay by parameterizing its marginals and a given family of copulas. We present several examples to illustrate the theory, including the important Gaussian and Euclidean families of copulas. We associate the theory to common applied time series models and present a general methodology to estimate a given parameter of interest identifiable through the process' covariance decay. To exemplify the proposed methodology, we present simple Monte Carlo applications to parameter estimation in time series. The methodology is also applied to the S&P500 US stock market index.
Covariance Data File Formats for Whisper-1.0 & Whisper-1.1
Brown, Forrest B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Rising, Michael Evan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-01-09
Whisper is a statistical analysis package developed in 2014 to support nuclear criticality safety (NCS) validation. It uses the sensitivity profile data for an application as computed by MCNP6 along with covariance files for the nuclear data to determine a baseline upper-subcritical-limit (USL) for the application. Whisper version 1.0 was first developed and used at LANL in 2014. During 2015-2016, Whisper was updated to version 1.1 and is to be included with the upcoming release of MCNP6.2. This report describes the file formats used for the covariance data in both Whisper-1.0 and Whisper-1.1.
Lompay, Robert R
2013-01-01
Arbitrary diffeomorphically invariant metric-torsion theories of gravity are considered. It is assumed that Lagrangians of such theories contain derivatives of field variables (tensor densities of arbitrary ranks and weights) up to a second order only. The generalized Klein-Noether methods for constructing manifestly covariant identities and conserved quantities are developed. Manifestly covariant expressions are constructed without including auxiliary structures like a background metric. In the Riemann-Cartan space, the following \\emph{manifestly generally covariant results} are presented: (a) The complete generalized system of differential identities (the Klein-Noether identities) is obtained. (b) The generalized currents of three types depending on an arbitrary vector field displacements are constructed: they are the canonical Noether current, symmetrized Belinfante current and identically conserved Hilbert-Bergmann current. In particular, it is stated that the symmetrized Belinfante current does not depen...
Revisiting Gruss's inequality: covariance bounds,QDE but not QD copulas, and central moments
Egozcue, Martin; Wong, Wing-Keung; Zitikis, Ricardas
2010-01-01
Since the pioneering work of Gerhard Gruss dating back to 1935, Gruss's inequality and, more generally, Gruss-type bounds for covariances have fascinated researchers and found numerous applications in areas such as economics, insurance, reliability, and, more generally, decision making under uncertainly. Gruss-type bounds for covariances have been established mainly under most general dependence structures, meaning no restrictions on the dependence structure between the two underlying random variables. Recent work in the area has revealed a potential for improving Gruss-type bounds, including the original Gruss's bound, assuming dependence structures such as quadrant dependence (QD). In this paper we demonstrate that the relatively little explored notion of `quadrant dependence in expectation' (QDE) is ideally suited in the context of bounding covariances, especially those that appear in the aforementioned areas of application. We explore this research avenue in detail, establish general Gruss-type bounds, an...
Compilation of multigroup cross-section covariance matrices for several important reactor materials
Drischler, J.D.; Weisbin, C.R.
1977-10-01
Multigroup cross-section covariance matrices are presented for fission in /sup 235/U, /sup 238/U, /sup 239/Pu, and /sup 241/Pu; capture in /sup 235/U, /sup 238/U, /sup 239/Pu, /sup 240/Pu, and /sup 241/Pu; fission neutron yield (anti nu) for /sup 235/U, /sup 238/U, /sup 239/Pu, and /sup 240/Pu; elastic scattering for Na and Fe; non-elastic reactions for Na and Fe; first-level inelastic scattering for /sup 238/U; and all reactions provided in the ENDF/B-IV covariance description of N, O, and C. Other data files generated are included for reference but have not yet been tested. The report presents the nultigroup data in six, ten, and fifteen energy group forms corresponding to weighting of the covariance data with fission (GODIVA), LMFBR (ZPR-6/7) and 1/E spectra, respectively.
Alfred Stadler, Franz Gross
2010-10-01
We provide a short overview of the Covariant Spectator Theory and its applications. The basic ideas are introduced through the example of a {phi}{sup 4}-type theory. High-precision models of the two-nucleon interaction are presented and the results of their use in calculations of properties of the two- and three-nucleon systems are discussed. A short summary of applications of this framework to other few-body systems is also presented.
Bryan, M.F.; Piepel, G.F.; Simpson, D.B.
1996-03-01
The high-level waste (HLW) vitrification plant at the Hanford Site was being designed to transuranic and high-level radioactive waste in borosilicate class. Each batch of plant feed material must meet certain requirements related to plant performance, and the resulting class must meet requirements imposed by the Waste Acceptance Product Specifications. Properties of a process batch and the resultlng glass are largely determined by the composition of the feed material. Empirical models are being developed to estimate some property values from data on feed composition. Methods for checking and documenting compliance with feed and glass requirements must account for various types of uncertainties. This document focuses on the estimation. manipulation, and consequences of composition uncertainty, i.e., the uncertainty inherent in estimates of feed or glass composition. Three components of composition uncertainty will play a role in estimating and checking feed and glass properties: batch-to-batch variability, within-batch uncertainty, and analytical uncertainty. In this document, composition uncertainty and its components are treated in terms of variances and variance components or univariate situations, covariance matrices and covariance components for multivariate situations. The importance of variance and covariance components stems from their crucial role in properly estimating uncertainty In values calculated from a set of observations on a process batch. Two general types of methods for estimating uncertainty are discussed: (1) methods based on data, and (2) methods based on knowledge, assumptions, and opinions about the vitrification process. Data-based methods for estimating variances and covariance matrices are well known. Several types of data-based methods exist for estimation of variance components; those based on the statistical method analysis of variance are discussed, as are the strengths and weaknesses of this approach.
Regional Scaling of Airborne Eddy Covariance Flux Observation
Sachs, T.; Serafimovich, A.; Metzger, S.; Kohnert, K.; Hartmann, J.
2014-12-01
The earth's surface is tightly coupled to the global climate system by the vertical exchange of energy and matter. Thus, to better understand and potentially predict changes to our climate system, it is critical to quantify the surface-atmosphere exchange of heat, water vapor, and greenhouse gases on climate-relevant spatial and temporal scales. Currently, most flux observations consist of ground-based, continuous but local measurements. These provide a good basis for temporal integration, but may not be representative of the larger regional context. This is particularly true for the Arctic, where site selection is additionally bound by logistical constraints, among others. Airborne measurements can overcome this limitation by covering distances of hundreds of kilometers over time periods of a few hours. The Airborne Measurements of Methane Fluxes (AIRMETH) campaigns are designed to quantitatively and spatially explicitly address this issue: The research aircraft POLAR 5 is used to acquire thousands of kilometers of eddy-covariance flux data. During the AIRMETH-2012 and AIRMETH-2013 campaigns we measured the turbulent exchange of energy, methane, and (in 2013) carbon dioxide over the North Slope of Alaska, USA, and the Mackenzie Delta, Canada. Here, we present the potential of environmental response functions (ERFs) for quantitatively linking flux observations to meteorological and biophysical drivers in the flux footprints. We use wavelet transforms of the original high-frequency data to improve spatial discretization of the flux observations. This also enables the quantification of continuous and biophysically relevant land cover properties in the flux footprint of each observation. A machine learning technique is then employed to extract and quantify the functional relationships between flux observations and the meteorological and biophysical drivers. The resulting ERFs are used to extrapolate fluxes over spatio-temporally explicit grids of the study area. The
Informed Conditioning on Clinical Covariates Increases Power in Case-Control Association Studies
Zaitlen, Noah; Lindström, Sara; Pasaniuc, Bogdan; Cornelis, Marilyn; Genovese, Giulio; Pollack, Samuela; Barton, Anne; Bickeböller, Heike; Bowden, Donald W.; Eyre, Steve; Freedman, Barry I.; Friedman, David J.; Field, John K.; Groop, Leif; Haugen, Aage; Heinrich, Joachim; Henderson, Brian E.; Hicks, Pamela J.; Hocking, Lynne J.; Kolonel, Laurence N.; Landi, Maria Teresa; Langefeld, Carl D.; Le Marchand, Loic; Meister, Michael; Morgan, Ann W.; Raji, Olaide Y.; Risch, Angela; Rosenberger, Albert; Scherf, David; Steer, Sophia; Walshaw, Martin; Waters, Kevin M.; Wilson, Anthony G.; Wordsworth, Paul; Zienolddiny, Shanbeh; Tchetgen, Eric Tchetgen; Haiman, Christopher; Hunter, David J.; Plenge, Robert M.; Worthington, Jane; Christiani, David C.; Schaumberg, Debra A.; Chasman, Daniel I.; Altshuler, David; Voight, Benjamin; Kraft, Peter; Patterson, Nick; Price, Alkes L.
2012-01-01
Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low–BMI cases are larger than those estimated from high–BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment) or phenotype and clinical covariates (case-control-covariate ascertainment). While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled false-positive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1×10−9). The improvement varied across diseases with a 16% median increase in χ2 test statistics and a
Informed conditioning on clinical covariates increases power in case-control association studies.
Noah Zaitlen
Full Text Available Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI, smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low-BMI cases are larger than those estimated from high-BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment or phenotype and clinical covariates (case-control-covariate ascertainment. While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled false-positive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1 × 10(-9. The improvement varied across diseases with a 16% median increase in χ(2 test statistics
Covariant and quasi-covariant quantum dynamics in Robertson-Walker space-times
Buchholz, D; Summers, S J; Buchholz, Detlev; Mund, Jens; Summers, Stephen J.
2002-01-01
We propose a canonical description of the dynamics of quantum systems on a class of Robertson-Walker space-times. We show that the worldline of an observer in such space-times determines a unique orbit in the local conformal group SO(4,1) of the space-time and that this orbit determines a unique transport on the space-time. For a quantum system on the space-time modeled by a net of local algebras, the associated dynamics is expressed via a suitable family of ``propagators''. In the best of situations, this dynamics is covariant, but more typically the dynamics will be ``quasi-covariant'' in a sense we make precise. We then show by using our technique of ``transplanting'' states and nets of local algebras from de Sitter space to Robertson-Walker space that there exist quantum systems on Robertson-Walker spaces with quasi-covariant dynamics. The transplanted state is locally passive, in an appropriate sense, with respect to this dynamics.
Jang, Eunice Eunhee; Roussos, Louis
2007-01-01
This article reports two studies to illustrate methodologies for conducting a conditional covariance-based nonparametric dimensionality assessment using data from two forms of the Test of English as a Foreign Language (TOEFL). Study 1 illustrates how to assess overall dimensionality of the TOEFL including all three subtests. Study 2 is aimed at…
Baldwin, Jennifer S.; Dadds, Mark R.
2008-01-01
Attention-deficit hyperactivity disorder (ADHD) is comorbid with a range of other disorders, including anxiety disorders. The aim was to examine different explanations for the covariation of these symptom domains in children according to the framework provided by (Lilienfeld, S. O. Comorbidity between and within childhood externalizing and…
Variance and covariance components for liability of piglet survival during different periods
Su, G; Sorensen, D; Lund, M S
2008-01-01
Variance and covariance components for piglet survival in different periods were estimated from individual records of 133 004 Danish Landrace piglets and 89 928 Danish Yorkshire piglets, using a liability threshold model including both direct and maternal additive genetic effects. At the individual...
Schubert, Sebastian
2015-01-01
One of the most relevant weather regimes in the mid latitudes atmosphere is the persistent deviation from the approximately zonally symmetric jet stream to the emergence of so-called blocking patterns. Such configurations are usually connected to exceptional local stability properties of the flow which come along with an improved local forecast skills during the phenomenon. It is instead extremely hard to predict onset and decay of blockings. Covariant Lyapunov Vectors (CLVs) offer a suitable characterization of the linear stability of a chaotic flow, since they represent the full tangent linear dynamics by a covariant basis which explores linear perturbations at all time scales. Therefore, we will test whether CLVs feature a signature of the blockings. We examine the CLVs for a quasi-geostrophic beta-plane two-layer model in a periodic channel baroclinically driven by a meridional temperature gradient $\\Delta T$. An orographic forcing enhances the emergence of localized blocked regimes. We detect the blockin...
Claudio CARERE, Doretta CARAMASCHI, Tim W. FAWCETT
2010-12-01
Full Text Available In the past decade there has been a profusion of studies highlighting covariation between individual differences in stress physiology and behavioural profiles, here called personalities. Such individual differences in ways of coping with stress are relevant both in biomedicine, since different personalities may experience a different stress and disease vulnerability, and in behavioural ecology, since their adaptive value and evolutionary maintenance are the subject of debate. However, the precise way in which individual stress differences and personalities are linked is unclear. Here we provide an updated overview of this covariation across different species and taxa, consider its functional significance and present working hypotheses for how behavioural and physiological responses to stress might be causally linked, affecting life-history traits such as dispersal and life-span [Current Zoology 56 (6: 728–740, 2010].
Strangeness $S=-1$ hyperon-nucleon scattering at leading order in the covariant Weinberg's approach
Li, Kai-Wen; Geng, Li-Sheng
2016-01-01
Inspired by the success of covariant baryon chiral perturbation theory in the one baryon sector and in the heavy-light systems, we explore the relevance of relativistic effects in the construction of the strangeness $S=-1$ hyperon-nucleon interaction using chiral perturbation theory. Due to the non-perturbative nature of the hyperon-nucleon interaction, we follow the covariant Weinberg's approach recently proposed by Epelbaum and Gegelia to sum the leading order chiral potential using the Kadyshevsky equation (Epelbaum, 2012) in this exploratory work. By fitting the five low-energy constants to available experimental data, we find that the cutoff dependence is mitigated compared with the results obtained in the Weinberg's approach for both partial wave phase shifts and the description of experimental data. Nevertheless, at leading order, the description of experimental data remains quantitatively similar. We discuss in detail the cutoff dependence of the partial wave phase shifts and cross sections in the Wei...
On How the Scalar Propagator Transforms Covariantly in Spinless Quantum Electrodynamics
Sánchez, Yajaira Concha; Villanueva-Sandoval, Victor M; Raya, Alfredo
2013-01-01
Gauge covariance properties of the scalar propagator in spinless/scalar quantum electrodynamics (SQED) are explored in the light of the corresponding Landau-Khalatnikov-Fradkin transformation (LKFT). These transformations are non perturbative in nature and describe how each Green function of the gauge theory changes under a variation of the gauge parameter. With a simple strategy, considering the scalar propagator at the tree level in Landau gauge, we derive a non perturbative expression for this propagator in an arbitrary covariant gauge and three as well as four space-time dimensions. Some relevant kinematical limits are discussed. Particularly, we compare our findings in the weak coupling regime with the direct one-loop calculation of the said propagator and observe perfect agreement up to an expected gauge independent term. We further notice that some of the coefficients of the all-order expansion for the propagator are fixed directly from the LKFT, a fact that makes this set of transformations appealing ...
Rathbun, Stephen L; Shiffman, Saul
2016-03-01
Cigarette smoking is a prototypical example of a recurrent event. The pattern of recurrent smoking events may depend on time-varying covariates including mood and environmental variables. Fixed effects and frailty models for recurrent events data assume that smokers have a common association with time-varying covariates. We develop a mixed effects version of a recurrent events model that may be used to describe variation among smokers in how they respond to those covariates, potentially leading to the development of individual-based smoking cessation therapies. Our method extends the modified EM algorithm of Steele (1996) for generalized mixed models to recurrent events data with partially observed time-varying covariates. It is offered as an alternative to the method of Rizopoulos, Verbeke, and Lesaffre (2009) who extended Steele's (1996) algorithm to a joint-model for the recurrent events data and time-varying covariates. Our approach does not require a model for the time-varying covariates, but instead assumes that the time-varying covariates are sampled according to a Poisson point process with known intensity. Our methods are well suited to data collected using Ecological Momentary Assessment (EMA), a method of data collection widely used in the behavioral sciences to collect data on emotional state and recurrent events in the every-day environments of study subjects using electronic devices such as Personal Digital Assistants (PDA) or smart phones.
Khoury, Justin; Tolley, Andrew J
2014-01-01
Traditional derivations of general relativity from the graviton degrees of freedom assume space-time Lorentz covariance as an axiom. In this essay, we survey recent evidence that general relativity is the unique spatially-covariant effective field theory of the transverse, traceless graviton degrees of freedom. The Lorentz covariance of general relativity, having not been assumed in our analysis, is thus plausibly interpreted as an accidental or emergent symmetry of the gravitational sector. From this point of view, Lorentz covariance is a necessary feature of low-energy graviton dynamics, not a property of space-time. This result has revolutionary implications for fundamental physics.
Fibromyalgia is characterized by altered frontal and cerebellar structural covariance brain networks
Kim, Hyungjun; Kim, Jieun; Loggia, Marco L.; Cahalan, Christine; Garcia, Ronald G.; Vangel, Mark G.; Wasan, Ajay D.; Edwards, Robert R.; Napadow, Vitaly
2015-01-01
Altered brain morphometry has been widely acknowledged in chronic pain, and recent studies have implicated altered network dynamics, as opposed to properties of individual brain regions, in supporting persistent pain. Structural covariance analysis determines the inter-regional association in morphological metrics, such as gray matter volume, and such structural associations may be altered in chronic pain. In this study, voxel-based morphometry structural covariance networks were compared between fibromyalgia patients (N = 42) and age- and sex-matched pain-free adults (N = 63). We investigated network topology using spectral partitioning, which can delineate local network submodules with consistent structural covariance. We also explored white matter connectivity between regions comprising these submodules and evaluated the association between probabilistic white matter tractography and pain-relevant clinical metrics. Our structural covariance network analysis noted more connections within the cerebellum for fibromyalgia patients, and more connections in the frontal lobe for healthy controls. For fibromyalgia patients, spectral partitioning identified a distinct submodule with cerebellar connections to medial prefrontal and temporal and right inferior parietal lobes, whose gray matter volume was associated with the severity of depression in these patients. Volume for a submodule encompassing lateral orbitofrontal, inferior frontal, postcentral, lateral temporal, and insular cortices was correlated with evoked pain sensitivity. Additionally, the number of white matter fibers between specific submodule regions was also associated with measures of evoked pain sensitivity and clinical pain interference. Hence, altered gray and white matter morphometry in cerebellar and frontal cortical regions may contribute to, or result from, pain-relevant dysfunction in chronic pain patients. PMID:25844321
Fibromyalgia is characterized by altered frontal and cerebellar structural covariance brain networks
Hyungjun Kim
2015-01-01
Full Text Available Altered brain morphometry has been widely acknowledged in chronic pain, and recent studies have implicated altered network dynamics, as opposed to properties of individual brain regions, in supporting persistent pain. Structural covariance analysis determines the inter-regional association in morphological metrics, such as gray matter volume, and such structural associations may be altered in chronic pain. In this study, voxel-based morphometry structural covariance networks were compared between fibromyalgia patients (N = 42 and age- and sex-matched pain-free adults (N = 63. We investigated network topology using spectral partitioning, which can delineate local network submodules with consistent structural covariance. We also explored white matter connectivity between regions comprising these submodules and evaluated the association between probabilistic white matter tractography and pain-relevant clinical metrics. Our structural covariance network analysis noted more connections within the cerebellum for fibromyalgia patients, and more connections in the frontal lobe for healthy controls. For fibromyalgia patients, spectral partitioning identified a distinct submodule with cerebellar connections to medial prefrontal and temporal and right inferior parietal lobes, whose gray matter volume was associated with the severity of depression in these patients. Volume for a submodule encompassing lateral orbitofrontal, inferior frontal, postcentral, lateral temporal, and insular cortices was correlated with evoked pain sensitivity. Additionally, the number of white matter fibers between specific submodule regions was also associated with measures of evoked pain sensitivity and clinical pain interference. Hence, altered gray and white matter morphometry in cerebellar and frontal cortical regions may contribute to, or result from, pain-relevant dysfunction in chronic pain patients.
Into the Bulk: A Covariant Approach
Engelhardt, Netta
2016-01-01
I propose a general, covariant way of defining when one region is "deeper in the bulk" than another. This definition is formulated outside of an event horizon (or in the absence thereof) in generic geometries; it may be applied to both points and surfaces, and may be used to compare the depth of bulk points or surfaces relative to a particular boundary subregion or relative to the entire boundary. Using the recently proposed "lightcone cut" formalism, the comparative depth between two bulk points can be determined from the singularity structure of Lorentzian correlators in the dual field theory. I prove that, by this definition, causal wedges of progressively larger regions probe monotonically deeper in the bulk. The definition furthermore matches expectations in pure AdS and in static AdS black holes with isotropic spatial slices, where a well-defined holographic coordinate exists. In terms of holographic RG flow, this new definition of bulk depth makes contact with coarse-graining over both large distances ...
A fully covariant description of CMB anisotropies
Dunsby, P K S
1997-01-01
Starting from the exact non-linear description of matter and radiation, a fully covariant and gauge-invariant formula for the observed temperature anisotropy of the cosmic microwave background (CBR) radiation, expressed in terms of the electric ($E_{ab}$) and magnetic ($H_{ab}$) parts of the Weyl tensor, is obtained by integrating photon geodesics from last scattering to the point of observation today. This improves and extends earlier work by Russ et al where a similar formula was obtained by taking first order variations of the redshift. In the case of scalar (density) perturbations, $E_{ab}$ is related to the harmonic components of the gravitational potential $\\Phi_k$ and the usual dominant Sachs-Wolfe contribution $\\delta T_R/\\bar{T}_R\\sim\\Phi_k$ to the temperature anisotropy is recovered, together with contributions due to the time variation of the potential (Rees-Sciama effect), entropy and velocity perturbations at last scattering and a pressure suppression term important in low density universes. We a...
General Covariance from the Quantum Renormalization Group
Shyam, Vasudev
2016-01-01
The Quantum renormalization group (QRG) is a realisation of holography through a coarse graining prescription that maps the beta functions of a quantum field theory thought to live on the `boundary' of some space to holographic actions in the `bulk' of this space. A consistency condition will be proposed that translates into general covariance of the gravitational theory in the $D + 1$ dimensional bulk. This emerges from the application of the QRG on a planar matrix field theory living on the $D$ dimensional boundary. This will be a particular form of the Wess--Zumino consistency condition that the generating functional of the boundary theory needs to satisfy. In the bulk, this condition forces the Poisson bracket algebra of the scalar and vector constraints of the dual gravitational theory to close in a very specific manner, namely, the manner in which the corresponding constraints of general relativity do. A number of features of the gravitational theory will be fixed as a consequence of this form of the Po...
New covariant Lagrange formulation for field theories
Ootsuka, T
2012-01-01
A novel approach for Lagrange formulation for field theories is proposed in terms of Kawaguchi geometry (areal metric space). On the extended configuration space M for classical field theory composed of spacetime and field configuration space, one can define a geometrical structure called Kawaguchi areal metric K from the field Lagrangian and (M,K) can be regarded as Kawaguchi manifold. The geometrical action functional is given by K and the dynamics of field is determined by covariant Euler-Lagrange equation derived from the variational principle of the action. The solution to the equation becomes a minimal hypersurface on (M,K) which has the same dimension as spacetime. We propose that this hypersurface is what we should regard as our real spacetime manifold, while the usual way to understand spacetime is to consider it as the parameter spacetime (base manifold) of a fibre bundle. In this way, the dynamics of field and spacetime structure is unified by Kawaguchi geometry. The theory has the property of stro...
Historical Hamiltonian Dynamics: symplectic and covariant
Lachieze-Rey, M
2016-01-01
This paper presents a "historical" formalism for dynamical systems, in its Hamiltonian version (Lagrangian version was presented in a previous paper). It is universal, in the sense that it applies equally well to time dynamics and to field theories on space-time. It is based on the notion of (Hamiltonian) histories, which are sections of the (extended) phase space bundle. It is developed in the space of sections, in contradistinction with the usual formalism which works in the bundle manifold. In field theories, the formalism remains covariant and does not require a spitting of space-time. It considers space-time exactly in the same manner than time in usual dynamics, both being particular cases of the evolution domain. It applies without modification when the histories (the fields) are forms rather than scalar functions, like in electromagnetism or in tetrad general relativity. We develop a differential calculus in the infinite dimensional space of histories. It admits a (generalized) symplectic form which d...
The covariance of GPS coordinates and frames
Lachieze-Rey, Marc [CNRS APC, UMR 7164 Service d' Astrophysique, CE Saclay, 91191 Gif sur Yvette Cedex (France)
2006-05-21
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.
CMB lens sample covariance and consistency relations
Motloch, Pavel; Hu, Wayne; Benoit-Lévy, Aurélien
2017-02-01
Gravitational lensing information from the two and higher point statistics of the cosmic microwave background (CMB) temperature and polarization fields are intrinsically correlated because they are lensed by the same realization of structure between last scattering and observation. Using an analytic model for lens sample covariance, we show that there is one mode, separately measurable in the lensed CMB power spectra and lensing reconstruction, that carries most of this correlation. Once these measurements become lens sample variance dominated, this mode should provide a useful consistency check between the observables that is largely free of sampling and cosmological parameter errors. Violations of consistency could indicate systematic errors in the data and lens reconstruction or new physics at last scattering, any of which could bias cosmological inferences and delensing for gravitational waves. A second mode provides a weaker consistency check for a spatially flat universe. Our analysis isolates the additional information supplied by lensing in a model-independent manner but is also useful for understanding and forecasting CMB cosmological parameter errors in the extended Λ cold dark matter parameter space of dark energy, curvature, and massive neutrinos. We introduce and test a simple but accurate forecasting technique for this purpose that neither double counts lensing information nor neglects lensing in the observables.
Schwinger mechanism in linear covariant gauges
Aguilar, A C; Papavassiliou, J
2016-01-01
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 modelled by means of certain physically motivated Ans\\"atze. The gauge-dependent terms contributing to this ke...
Comparison between covariant and orthogonal Lyapunov vectors.
Yang, Hong-liu; Radons, Günter
2010-10-01
Two sets of vectors, covariant Lyapunov vectors (CLVs) and orthogonal Lyapunov vectors (OLVs), are currently used to characterize the linear stability of chaotic systems. A comparison is made to show their similarity and difference, especially with respect to the influence on hydrodynamic Lyapunov modes (HLMs). Our numerical simulations show that in both Hamiltonian and dissipative systems HLMs formerly detected via OLVs survive if CLVs are used instead. Moreover, the previous classification of two universality classes works for CLVs as well, i.e., the dispersion relation is linear for Hamiltonian systems and quadratic for dissipative systems, respectively. The significance of HLMs changes in different ways for Hamiltonian and dissipative systems with the replacement of OLVs with CLVs. For general dissipative systems with nonhyperbolic dynamics the long-wavelength structure in Lyapunov vectors corresponding to near-zero Lyapunov exponents is strongly reduced if CLVs are used instead, whereas for highly hyperbolic dissipative systems the significance of HLMs is nearly identical for CLVs and OLVs. In contrast the HLM significance of Hamiltonian systems is always comparable for CLVs and OLVs irrespective of hyperbolicity. We also find that in Hamiltonian systems different symmetry relations between conjugate pairs are observed for CLVs and OLVs. Especially, CLVs in a conjugate pair are statistically indistinguishable in consequence of the microreversibility of Hamiltonian systems. Transformation properties of Lyapunov exponents, CLVs, and hyperbolicity under changes of coordinate are discussed in appendices.
Frame Indifferent (Truly Covariant) Formulation of Electrodynamics
Christov, Christo
2010-10-01
The Electromagnetic field is considered from the point of view of mechanics of continuum. It is shown that Maxwell's equations are mathematically strict corollaries form the equation of motions of an elastic incompressible liquid. If the concept of frame-indifference (material invariance) is applied to the model of elastic liquid, then the partial time derivatives have to be replaced by the convective time derivative in the momentum equations, and by the Oldroyd upper-convected derivative in the constitutive relation. The convective/convected terms involve the velocity at a point of the field, and as a result, when deriving the Maxwell form of the equations, one arrives at equations which contain both the terms of Maxwell's equation and the so-called laws of motional EMF: Faraday's, Oersted--Ampere's, and the Lorentz-force law. Thus a unification of the electromagnetism is achieved. Since the new model is frame indifferent, it is truly covariant in the sense that the governing system is invariant when changing to a coordinate frame that can accelerate or even deform in time.
IMPROVED COVARIANCE DRIVEN BLIND SUBSPACE IDENTIFICATION METHOD
ZHANG Zhiyi; FAN Jiangling; HUA Hongxing
2006-01-01
An improved covariance driven subspace identification method is presented to identify the weakly excited modes. In this method, the traditional Hankel matrix is replaced by a reformed one to enhance the identifiability of weak characteristics. The robustness of eigenparameter estimation to noise contamination is reinforced by the improved Hankel matrix. In combination with component energy index (CEI) which indicates the vibration intensity of signal components, an alternative stabilization diagram is adopted to effectively separate spurious and physical modes. Simulation of a vibration system of multiple-degree-of-freedom and experiment of a frame structure subject to wind excitation are presented to demonstrate the improvement of the proposed blind method. The performance of this blind method is assessed in terms of its capability in extracting the weak modes as well as the accuracy of estimated parameters. The results have shown that the proposed blind method gives a better estimation of the weak modes from response signals of small signal to noise ratio (SNR)and gives a reliable separation of spurious and physical estimates.
On the bilinear covariants associated to mass dimension one spinors
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.)
Validity of covariance models for the analysis of geographical variation
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...
Perturbative approach to covariance matrix of the matter power spectrum
Mohammed, Irshad [Fermilab; Seljak, Uros [UC, Berkeley, Astron. Dept.; Vlah, Zvonimir [Stanford U., ITP
2016-06-30
We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (beat coupling or super-sample variance), and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10\\% level up to $k \\sim 1 h {\\rm Mpc^{-1}}$. We show that all the connected components are dominated by the large-scale modes ($k<0.1 h {\\rm Mpc^{-1}}$), regardless of the value of the wavevectors $k,\\, k'$ of the covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher $k$ it is dominated by a single eigenmode. The full covariance matrix can be approximated as the disconnected part only, with the connected part being treated as an external nuisance parameter with a known scale dependence, and a known prior on its variance for a given survey volume. Finally, we provide a prescription for how to evaluate the covariance matrix from small box simulations without the need to simulate large volumes.
Validity of covariance models for the analysis of geographical variation
Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio
2014-01-01
attention lately and show that the conditions under which they are valid mathematical models have been overlooked so far. 3. We provide rigorous results for the construction of valid covariance models in this family. 4. We also outline how to construct alternative covariance models for the analysis...
Covariation Is a Poor Measure of Molecular Coevolution.
Talavera, David; Lovell, Simon C; Whelan, Simon
2015-09-01
Recent developments in the analysis of amino acid covariation are leading to breakthroughs in protein structure prediction, protein design, and prediction of the interactome. It is assumed that observed patterns of covariation are caused by molecular coevolution, where substitutions at one site affect the evolutionary forces acting at neighboring sites. Our theoretical and empirical results cast doubt on this assumption. We demonstrate that the strongest coevolutionary signal is a decrease in evolutionary rate and that unfeasibly long times are required to produce coordinated substitutions. We find that covarying substitutions are mostly found on different branches of the phylogenetic tree, indicating that they are independent events that may or may not be attributable to coevolution. These observations undermine the hypothesis that molecular coevolution is the primary cause of the covariation signal. In contrast, we find that the pairs of residues with the strongest covariation signal tend to have low evolutionary rates, and that it is this low rate that gives rise to the covariation signal. Slowly evolving residue pairs are disproportionately located in the protein's core, which explains covariation methods' ability to detect pairs of residues that are close in three dimensions. These observations lead us to propose the "coevolution paradox": The strength of coevolution required to cause coordinated changes means the evolutionary rate is so low that such changes are highly unlikely to occur. As modern covariation methods may lead to breakthroughs in structural genomics, it is critical to recognize their biases and limitations.
A pure S-wave covariant model for the nucleon
Gross, F; Peña, M T; Gross, Franz
2006-01-01
Using the manifestly covariant spectator theory, and modeling the nucleon as a system of three constituent quarks with their own electromagnetic structure, we show that all four nucleon electromagnetic form factors can be very well described by a manifestly covariant nucleon wave function with zero orbital angular momentum.
On the bilinear covariants associated to mass dimension one spinors
da Silva, J M Hoff; Rogerio, R J Bueno; Scatena, E
2016-01-01
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. Moreover, the possible generalizations to the recently presented new dual structure are performed.
Perturbative approach to covariance matrix of the matter power spectrum
Mohammed, Irshad; Seljak, Uroš; Vlah, Zvonimir
2017-04-01
We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (supersample variance) and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10 per cent level up to k ˜ 1 h Mpc-1. We show that all the connected components are dominated by the large-scale modes (k covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher k, it is dominated by a single eigenmode. The full covariance matrix can be approximated as the disconnected part only, with the connected part being treated as an external nuisance parameter with a known scale dependence, and a known prior on its variance for a given survey volume. Finally, we provide a prescription for how to evaluate the covariance matrix from small box simulations without the need to simulate large volumes.
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
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
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...
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
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...
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.
Gaussian covariance matrices for anisotropic galaxy clustering measurements
Grieb, Jan Niklas; Salazar-Albornoz, Salvador; Vecchia, Claudio dalla
2015-01-01
Measurements of the redshift-space galaxy clustering have been a prolific source of cosmological information in recent years. In the era of precision cosmology, accurate covariance estimates are an essential step for the validation of galaxy clustering models of the redshift-space two-point statistics. For cases where only a limited set of simulations is available, assessing the data covariance is not possible or only leads to a noisy estimate. Also, relying on simulated realisations of the survey data means that tests of the cosmology dependence of the covariance are expensive. With these two points in mind, this work aims at presenting a simple theoretical model for the linear covariance of anisotropic galaxy clustering observations with synthetic catalogues. Considering the Legendre moments (`multipoles') of the two-point statistics and projections into wide bins of the line-of-sight parameter (`clustering wedges'), we describe the modelling of the covariance for these anisotropic clustering measurements f...
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.
High-dimensional covariance matrix estimation in approximate factor models
Fan, Jianqing; Mincheva, Martina; 10.1214/11-AOS944
2012-01-01
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 [J. Amer. Statist. Assoc. 106 (2011) 672--684], 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 studi...
Newton law in covariant unimodular $F(R)$ gravity
Nojiri, S; Oikonomou, V K
2016-01-01
We propose a covariant ghost-free unimodular $F(R)$ gravity theory, which contains a three-form field and study its structure using the analogy of the proposed theory with a quantum system which describes a charged particle in uniform magnetic field. Newton's law in non-covariant unimodular $F(R)$ gravity as well as in unimodular Einstein gravity is derived and it is shown to be just the same as in General Relativity. The derivation of Newton's law in covariant unimodular $F(R)$ gravity shows that it is modified precisely in the same way as in the ordinary $F(R)$ theory. We also demonstrate that the cosmology of a Friedmann-Robertson-Walker background, is equivalent in the non-covariant and covariant formulations of unimodular $F(R)$ theory.
Least-Squares Data Adjustment with Rank-Deficient Data Covariance Matrices
Williams, J.G. [The University of Arizona, Tucson, AZ 85721-0119 (United States)
2011-07-01
A derivation of the linear least-squares adjustment formulae is required that avoids the assumption that the covariance matrix of prior parameters can be inverted. Possible proofs are of several kinds, including: (i) extension of standard results for the linear regression formulae, and (ii) minimization by differentiation of a quadratic form of the deviations in parameters and responses. In this paper, the least-squares adjustment equations are derived in both these ways, while explicitly assuming that the covariance matrix of prior parameters is singular. It will be proved that the solutions are unique and that, contrary to statements that have appeared in the literature, the least-squares adjustment problem is not ill-posed. No modification is required to the adjustment formulae that have been used in the past in the case of a singular covariance matrix for the priors. In conclusion: The linear least-squares adjustment formula that has been used in the past is valid in the case of a singular covariance matrix for the covariance matrix of prior parameters. Furthermore, it provides a unique solution. Statements in the literature, to the effect that the problem is ill-posed are wrong. No regularization of the problem is required. This has been proved in the present paper by two methods, while explicitly assuming that the covariance matrix of prior parameters is singular: i) extension of standard results for the linear regression formulae, and (ii) minimization by differentiation of a quadratic form of the deviations in parameters and responses. No modification is needed to the adjustment formulae that have been used in the past. (author)
PRELIMINARY CROSS SECTION AND NU-BAR COVARIANCES FOR WPEC SUBGROUP 26
ROCHMAN,D.
2007-01-31
We report preliminary cross section covariances developed for the WPEC Subgroup 26 for 45 out of 52 requested materials. The covariances were produced in 15- and 187-group representations as follows: (1) 36 isotopes ({sup 16}O, {sup 19}F, {sup 23}Na, {sup 27}Al, {sup 28}Si, {sup 52}Cr, {sup 56,56}Fe, {sup 58}Ni, {sup 90,91,92,94}Zr, {sup 166,167,168,170}Er, {sup 206,207,208}Pb, {sup 209}Bi, {sup 233,234,236}U, {sup 237}Np, {sup 238,240,241,242}Pu, {sup 241,242m,243}Am, {sup 242,243,244,245}Cm) were evaluated using the BNL-LANL methodology. For the thermal region and the resolved and unresolved resonance regions, the methodology has been based on the Atlas-Kalman approach, in the fast neutron region the Empire-Kalman method has been used; (2) 6 isotopes ({sup 155,156,157,158,160}Gd and {sup 232}Th) were taken from ENDF/B-VII.0; and (3) 3 isotopes ({sup 1}H, {sup 238}U and {sup 239}Pu) were taken from JENDL-3.3. For 6 light nuclei ({sup 4}He, {sup 6,7}Li, {sup 9}Be, {sup 10}B, {sup 12}C), only partial cross section covariance results were obtained, additional work is needed and they do not report the results here. Likewise, the cross section covariances for {sup 235}U, which they recommend to take from JENDL-3.3, will be included once the multigroup processing is successfully completed. Covariances for the average number of neutrons per fission, total {nu}-bar, are provided for 10 actinides identified as priority by SG26. Further work is needed to resolve some of the issues and to produce covariances for the full set of 52 materials.
Towards a network of Urban Forest Eddy Covariance stations: a unique case study in Naples
Guidolotti, Gabriele; Pallozzi, Emanuele; Esposito, Raffaela; Mattioni, Michele; Calfapietra, Carlo
2015-04-01
Urban forests are by definition integrated in highly human-made areas, and interact with different components of our cities. Thanks to those interactions, urban forests provide to people and to the urban environment a number of ecosystem services, including the absorption of CO2 and air pollutants thus influencing the local air quality. Moreover, in urban areas a relevant role is played by the photochemical pollution which is strongly influenced by the interactions between volatile organic compounds (VOC) and nitrogen oxides (NOx). In several cities, a high percentage of VOC is of biogenic origin mainly emitted from the urban trees. Despite their importance, experimental sites monitoring fluxes of trace gases fluxes in urban forest ecosystems are still scarce. Here we show the preliminary results of an innovative experimental site located in the Royal Park of Capodimonte within the city of Naples (40°51'N-14°15'E, 130 m above sea level). The site is mainly characterised by Quercus ilex with some patches of Pinus pinea and equipped with an eddy-covariance tower measuring the exchange of CO2, H2O, N2O, CH4, O3, PM, VOCs and NOx using state-of-the art instrumentations; it is running since the end of 2014 and it is part of the large infrastructural I-AMICA project. We suggest that the experience gained with research networks such as Fluxnet and ICOS should be duplicated for urban forests. This is crucial for carbon as there is now the ambition to include urban forests in the carbon stocks accounting system. This is even more important to understand the difficult interactions between anthropogenic and biogenic sources that often have negative implications for urban air quality. Urban environment can thus become an extraordinary case study and a network of such kind of stations might represent an important strategy both from the scientific and the applicative point of view.
Recurrence Analysis of Eddy Covariance Fluxes
Lange, Holger; Flach, Milan; Foken, Thomas; Hauhs, Michael
2015-04-01
The eddy covariance (EC) method is one key method to quantify fluxes in biogeochemical cycles in general, and carbon and energy transport across the vegetation-atmosphere boundary layer in particular. EC data from the worldwide net of flux towers (Fluxnet) have also been used to validate biogeochemical models. The high resolution data are usually obtained at 20 Hz sampling rate but are affected by missing values and other restrictions. In this contribution, we investigate the nonlinear dynamics of EC fluxes using Recurrence Analysis (RA). High resolution data from the site DE-Bay (Waldstein-Weidenbrunnen) and fluxes calculated at half-hourly resolution from eight locations (part of the La Thuile dataset) provide a set of very long time series to analyze. After careful quality assessment and Fluxnet standard gapfilling pretreatment, we calculate properties and indicators of the recurrent structure based both on Recurrence Plots as well as Recurrence Networks. Time series of RA measures obtained from windows moving along the time axis are presented. Their interpretation is guided by three different questions: (1) Is RA able to discern periods where the (atmospheric) conditions are particularly suitable to obtain reliable EC fluxes? (2) Is RA capable to detect dynamical transitions (different behavior) beyond those obvious from visual inspection? (3) Does RA contribute to an understanding of the nonlinear synchronization between EC fluxes and atmospheric parameters, which is crucial for both improving carbon flux models as well for reliable interpolation of gaps? (4) Is RA able to recommend an optimal time resolution for measuring EC data and for analyzing EC fluxes? (5) Is it possible to detect non-trivial periodicities with a global RA? We will demonstrate that the answers to all five questions is affirmative, and that RA provides insights into EC dynamics not easily obtained otherwise.
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.
Greco, Johnny P
2016-01-01
The recovery of an exoplanet's atmospheric parameters from its spectrum requires accurate knowledge of the spectral errors and covariances. Unfortunately, the complex image processing used in high-contrast integral-field spectrograph (IFS) observations generally produces spectral covariances that are poorly understood and often ignored. In this work, we show how to measure the spectral errors and covariances and include them self-consistently in parameter retrievals. By combining model exoplanet spectra with a realistic noise model generated from GPI early science data, we show that ignoring spectral covariance in high-contrast IFS data can both bias inferred parameters and lead to unreliable confidence regions on those parameters. This problem is made worse by the common practice of scaling the $\\chi^2$ per degree of freedom to unity; the input parameters then fall outside the $95\\%$ confidence regions in as many as ${\\sim}80\\%$ of noise realizations. Accounting for realistic priors in fully Bayesian paramet...
Relevance theory: pragmatics and cognition.
Wearing, Catherine J
2015-01-01
Relevance Theory is a cognitively oriented theory of pragmatics, i.e., a theory of language use. It builds on the seminal work of H.P. Grice(1) to develop a pragmatic theory which is at once philosophically sensitive and empirically plausible (in both psychological and evolutionary terms). This entry reviews the central commitments and chief contributions of Relevance Theory, including its Gricean commitment to the centrality of intention-reading and inference in communication; the cognitively grounded notion of relevance which provides the mechanism for explaining pragmatic interpretation as an intention-driven, inferential process; and several key applications of the theory (lexical pragmatics, metaphor and irony, procedural meaning). Relevance Theory is an important contribution to our understanding of the pragmatics of communication.
Baryon oscillations in galaxy and matter power-spectrum covariance matrices
Neyrinck, Mark C
2007-01-01
We investigate large-amplitude baryon acoustic oscillations (BAO's) in off-diagonal entries of cosmological power-spectrum covariance matrices. These covariance-matrix BAO's describe the increased attenuation of power-spectrum BAO's caused by upward fluctuations in large-scale power. We derive an analytic approximation to covariance-matrix entries in the BAO regime, and check the analytical predictions using N-body simulations. These BAO's look much stronger than the BAO's in the power spectrum, but seem detectable only at about a one-sigma level in gigaparsec-scale galaxy surveys. In estimating cosmological parameters using matter or galaxy power spectra, including the covariance-matrix BAO's can have a several-percent effect on error-bar widths for some parameters directly related to the BAO's, such as the baryon fraction. Also, we find that including the numerous galaxies in small haloes in a survey can reduce error bars in these cosmological parameters more than the simple reduction in shot noise might su...
Lioma, Christina; Larsen, Birger; Petersen, Casper
2016-01-01
train a Recurrent Neural Network (RNN) on existing relevant information to that query. We then use the RNN to "deep learn" a single, synthetic, and we assume, relevant document for that query. We design a crowdsourcing experiment to assess how relevant the "deep learned" document is, compared......What if Information Retrieval (IR) systems did not just retrieve relevant information that is stored in their indices, but could also "understand" it and synthesise it into a single document? We present a preliminary study that makes a first step towards answering this question. Given a query, we...... to existing relevant documents. Users are shown a query and four wordclouds (of three existing relevant documents and our deep learned synthetic document). The synthetic document is ranked on average most relevant of all....
Contextualized Network Analysis: Theory and Methods for Networks with Node Covariates
Binkiewicz, Norbert M.
Biological and social systems consist of myriad interacting units. The interactions can be intuitively represented in the form of a graph or network. Measurements of these graphs can reveal the underlying structure of these interactions, which provides insight into the systems that generated the graphs. Moreover, in applications such as neuroconnectomics, social networks, and genomics, graph data is accompanied by contextualizing measures on each node. We leverage these node covariates to help uncover latent communities, using a modification of spectral clustering. Statistical guarantees are provided under a joint mixture model called the node contextualized stochastic blockmodel, including a bound on the mis-clustering rate. For most simulated conditions, covariate assisted spectral clustering yields superior results relative to both regularized spectral clustering without node covariates and an adaptation of canonical correlation analysis. We apply covariate assisted spectral clustering to large brain graphs derived from diffusion MRI, using the node locations or neurological regions as covariates. In both cases, covariate assisted spectral clustering yields clusters that are easier to interpret neurologically. A low rank update algorithm is developed to reduce the computational cost of determining the tuning parameter for covariate assisted spectral clustering. As simulations demonstrate, the low rank update algorithm increases the speed of covariate assisted spectral clustering up to ten-fold, while practically matching the clustering performance of the standard algorithm. Graphs with node attributes are sometimes accompanied by ground truth labels that align closely with the latent communities in the graph. We consider the example of a mouse retina neuron network accompanied by the neuron spatial location and neuronal cell types. In this example, the neuronal cell type is considered a ground truth label. Current approaches for defining neuronal cell type vary
FLUXNET2015 Dataset: Batteries included
Pastorello, G.; Papale, D.; Agarwal, D.; Trotta, C.; Chu, H.; Canfora, E.; Torn, M. S.; Baldocchi, D. D.
2016-12-01
The synthesis datasets have become one of the signature products of the FLUXNET global network. They are composed from contributions of individual site teams to regional networks, being then compiled into uniform data products - now used in a wide variety of research efforts: from plant-scale microbiology to global-scale climate change. The FLUXNET Marconi Dataset in 2000 was the first in the series, followed by the FLUXNET LaThuile Dataset in 2007, with significant additions of data products and coverage, solidifying the adoption of the datasets as a research tool. The FLUXNET2015 Dataset counts with another round of substantial improvements, including extended quality control processes and checks, use of downscaled reanalysis data for filling long gaps in micrometeorological variables, multiple methods for USTAR threshold estimation and flux partitioning, and uncertainty estimates - all of which accompanied by auxiliary flags. This "batteries included" approach provides a lot of information for someone who wants to explore the data (and the processing methods) in detail. This inevitably leads to a large number of data variables. Although dealing with all these variables might seem overwhelming at first, especially to someone looking at eddy covariance data for the first time, there is method to our madness. In this work we describe the data products and variables that are part of the FLUXNET2015 Dataset, and the rationale behind the organization of the dataset, covering the simplified version (labeled SUBSET), the complete version (labeled FULLSET), and the auxiliary products in the dataset.
Quantification of Covariance in Tropical Cyclone Activity across Teleconnected Basins
Tolwinski-Ward, S. E.; Wang, D.
2015-12-01
Rigorous statistical quantification of natural hazard covariance across regions has important implications for risk management, and is also of fundamental scientific interest. We present a multivariate Bayesian Poisson regression model for inferring the covariance in tropical cyclone (TC) counts across multiple ocean basins and across Saffir-Simpson intensity categories. Such covariability results from the influence of large-scale modes of climate variability on local environments that can alternately suppress or enhance TC genesis and intensification, and our model also simultaneously quantifies the covariance of TC counts with various climatic modes in order to deduce the source of inter-basin TC covariability. The model explicitly treats the time-dependent uncertainty in observed maximum sustained wind data, and hence the nominal intensity category of each TC. Differences in annual TC counts as measured by different agencies are also formally addressed. The probabilistic output of the model can be probed for probabilistic answers to such questions as: - Does the relationship between different categories of TCs differ statistically by basin? - Which climatic predictors have significant relationships with TC activity in each basin? - Are the relationships between counts in different basins conditionally independent given the climatic predictors, or are there other factors at play affecting inter-basin covariability? - How can a portfolio of insured property be optimized across space to minimize risk? Although we present results of our model applied to TCs, the framework is generalizable to covariance estimation between multivariate counts of natural hazards across regions and/or across peril types.
Covariance of maximum likelihood evolutionary distances between sequences aligned pairwise.
Dessimoz, Christophe; Gil, Manuel
2008-06-23
The estimation of a distance between two biological sequences is a fundamental process in molecular evolution. It is usually performed by maximum likelihood (ML) on characters aligned either pairwise or jointly in a multiple sequence alignment (MSA). Estimators for the covariance of pairs from an MSA are known, but we are not aware of any solution for cases of pairs aligned independently. In large-scale analyses, it may be too costly to compute MSAs every time distances must be compared, and therefore a covariance estimator for distances estimated from pairs aligned independently is desirable. Knowledge of covariances improves any process that compares or combines distances, such as in generalized least-squares phylogenetic tree building, orthology inference, or lateral gene transfer detection. In this paper, we introduce an estimator for the covariance of distances from sequences aligned pairwise. Its performance is analyzed through extensive Monte Carlo simulations, and compared to the well-known variance estimator of ML distances. Our covariance estimator can be used together with the ML variance estimator to form covariance matrices. The estimator performs similarly to the ML variance estimator. In particular, it shows no sign of bias when sequence divergence is below 150 PAM units (i.e. above ~29% expected sequence identity). Above that distance, the covariances tend to be underestimated, but then ML variances are also underestimated.
Generalized linear models with coarsened covariates: a practical Bayesian approach.
Johnson, Timothy R; Wiest, Michelle M
2014-06-01
Coarsened covariates are a common and sometimes unavoidable phenomenon encountered in statistical modeling. Covariates are coarsened when their values or categories have been grouped. This may be done to protect privacy or to simplify data collection or analysis when researchers are not aware of their drawbacks. Analyses with coarsened covariates based on ad hoc methods can compromise the validity of inferences. One valid method for accounting for a coarsened covariate is to use a marginal likelihood derived by summing or integrating over the unknown realizations of the covariate. However, algorithms for estimation based on this approach can be tedious to program and can be computationally expensive. These are significant obstacles to their use in practice. To overcome these limitations, we show that when expressed as a Bayesian probability model, a generalized linear model with a coarsened covariate can be posed as a tractable missing data problem where the missing data are due to censoring. We also show that this model is amenable to widely available general-purpose software for simulation-based inference for Bayesian probability models, providing researchers a very practical approach for dealing with coarsened covariates.
Gauge-covariant canonical formalism revisited with application to the proton spin decomposition
Lorcé, Cédric
2013-01-01
We revisit the gauge-covariant canonical formalism by separating explicitly physical and gauge degrees of freedom. We show in particular that the gauge-invariant linear and angular momentum operators proposed by Chen et al. can consistently be derived from the standard procedure based on the Noether's theorem. Finally, we demonstrate that this approach is essentially equivalent to the gauge-invariant canonical formalism based on the concept of Dirac variables. Because of many similarities with the background field method, the formalism developed here should also be relevant to general relativity and any metric theories.
Soil Respiration in Eddy Covariance Footprints using Forced Diffusion
Nickerson, N.; Gabriel, C. E.; Creelman, C.
2016-12-01
Eddy covariance (EC) has been widely used across the globe for more than 20 years, offering researchers invaluable measurements of parameters including Net Ecosystem Exchange and ecosystem respiration. However, research suggests that EC assumptions and technical obstacles can cause biased gas exchange estimates. Measurements of soil respiration (RS) at the ground level may help alleviate these biases; for example, by allowing researchers to reconcile nocturnal EC flux data with RS or by providing a means to inform gap-filling models. RS measurements have been used sparingly alongside EC towers because of the large cost required to scale chamber systems to the EC footprint and data integration and processing burdens. Here we present the Forced Diffusion (FD) method for the measurement of RS at EC sites. The FD method allows for inexpensive and autonomous measurements, providing a scalable approach to matching the EC footprint compared to other RS systems. A pilot study at the Howland Forest AmeriFlux site was carried out from July 15, 2016 to Dec., 2016 using EC, custom-made automated chambers, and FD chambers in tandem. These results emphasize how RS measurements, like those from the eosFD, can identify decoupling of above and below canopy air masses and assist in informing and parameterizing gap-filling techniques. Uncertainty in nocturnal EC fluxes has been extensively characterized at Howland Forest with EC measurements spanning more than 20 years. Similarly, long term automated measurements of RS are also made at Howland, and have already been used to inform EC gap-filling models, making Howland the ideal site for such a study. This study has been designed to reproduce previous findings from Howland using the FD approach, aiming to demonstrate that the measurements taken using the eosFD correlate well with the existing chamber systems and can be used with equal efficacy to inform gap filling models or for other other eddy covariance QA/QC procedures, including
Reality conditions for Ashtekar gravity from Lorentz-covariant formulation
Alexandrov, Sergei [Institute for Theoretical Physics and Spinoza Institute, Utrecht University, Postbus 80.195, 3508 TD Utrecht (Netherlands)
2006-03-21
We study the limit of the Lorentz-covariant canonical formulation where the Immirzi parameter approaches {beta} = i. We show that, formulated in terms of a shifted spacetime connection, which also plays a crucial role in the covariant quantization, the limit is smooth and reproduces the canonical structure of the self-dual Ashtekar gravity. The reality conditions of Ashtekar gravity can be incorporated by means of the Dirac brackets derived from the covariant formulation and defined on an extended phase space which involves, besides the self-dual variables, also their anti-self-dual counterparts.
Poincaré covariance of relativistic quantum position
Farkas, S; Weiner, M D; Farkas, Sz.
2002-01-01
A great number of problems of relativistic position in quantum mechanics are due to the use of coordinates which are not inherent objects of spacetime, cause unnecessary complications and can lead to misconceptions. We apply a coordinate-free approach to rule out such problems. Thus it will be clear, for example, that the Lorentz covariance of position, required usually on the analogy of Lorentz covariance of spacetime coordinates, is not well posed and we show that in a right setting the Newton--Wigner position is Poincar\\'e covariant, in contradiction with the usual assertions.
Bayes linear covariance matrix adjustment for multivariate dynamic linear models
Wilkinson, Darren J
2008-01-01
A methodology is developed for the adjustment of the covariance matrices underlying a multivariate constant time series dynamic linear model. The covariance matrices are embedded in a distribution-free inner-product space of matrix objects which facilitates such adjustment. This approach helps to make the analysis simple, tractable and robust. To illustrate the methods, a simple model is developed for a time series representing sales of certain brands of a product from a cash-and-carry depot. The covariance structure underlying the model is revised, and the benefits of this revision on first order inferences are then examined.
Covariate-adjusted measures of discrimination for survival data
White, Ian R; Rapsomaniki, Eleni; Frikke-Schmidt, Ruth
2015-01-01
MOTIVATION: Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled...... 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...
Universal correlations and power-law tails in financial covariance matrices
Akemann, G.; Fischmann, J.; Vivo, P.
2010-07-01
We investigate whether quantities such as the global spectral density or individual eigenvalues of financial covariance matrices can be best modelled by standard random matrix theory or rather by its generalisations displaying power-law tails. In order to generate individual eigenvalue distributions a chopping procedure is devised, which produces a statistical ensemble of asset-price covariances from a single instance of financial data sets. Local results for the smallest eigenvalue and individual spacings are very stable upon reshuffling the time windows and assets. They are in good agreement with the universal Tracy-Widom distribution and Wigner surmise, respectively. This suggests a strong degree of robustness especially in the low-lying sector of the spectra, most relevant for portfolio selections. Conversely, the global spectral density of a single covariance matrix as well as the average over all unfolded nearest-neighbour spacing distributions deviate from standard Gaussian random matrix predictions. The data are in fair agreement with a recently introduced generalised random matrix model, with correlations showing a power-law decay.
Fuzziness and Relevance Theory
Grace Qiao Zhang
2005-01-01
This paper investigates how the phenomenon of fuzzy language, such as `many' in `Mary has many friends', can be explained by Relevance Theory. It is concluded that fuzzy language use conforms with optimal relevance in that it can achieve the greatest positive effect with the least processing effort. It is the communicators themselves who decide whether or not optimal relevance is achieved, rather than the language form (fuzzy or non-fuzzy) used. People can skillfully adjust the deployment of different language forms or choose appropriate interpretations to suit different situations and communication needs. However, there are two challenges to RT: a. to extend its theory from individual relevance to group relevance; b. to embrace cultural considerations (because when relevance principles and cultural protocols are in conflict, the latter tends to prevail).
Perceptions of document relevance
Peter eBruza
2014-07-01
Full Text Available This article presents a study of how humans perceive the relevance of documents.Humans are adept at making reasonably robust and quick decisions about what information is relevant to them, despite the ever increasing complexity and volume of their surrounding information environment. The literature on document relevance has identified various dimensions of relevance (e.g., topicality, novelty, etc., however little is understood about how these dimensions may interact.We performed a crowdsourced study of how human subjects judge two relevance dimensions in relation to document snippets retrieved from an internet search engine.The order of the judgement was controlled.For those judgements exhibiting an order effect, a q-test was performed to determine whether the order effects can be explained by a quantum decision model based on incompatible decision perspectives.Some evidence of incompatibility was found which suggests incompatible decision perspectives is appropriate for explaining interacting dimensions of relevance.
Noether Symmetries and Covariant Conservation Laws in Classical, Relativistic and Quantum Physics
Lorenzo Fatibene
2010-04-01
Full Text Available We review the Lagrangian formulation of (generalised Noether symmetries in the framework of Calculus of Variations in Jet Bundles, with a special attention to so-called “Natural Theories” and “Gauge-Natural Theories” that include all relevant Field Theories and physical applications (from Mechanics to General Relativity, to Gauge Theories, Supersymmetric Theories, Spinors, etc.. It is discussed how the use of Poincar´e–Cartan forms and decompositions of natural (or gauge-natural variational operators give rise to notions such as “generators of Noether symmetries”, energy and reduced energy flow, Bianchi identities, weak and strong conservation laws, covariant conservation laws, Hamiltonian-like conservation laws (such as, e.g., so-calledADMlaws in General Relativity with emphasis on the physical interpretation of the quantities calculated in specific cases (energy, angular momentum, entropy, etc.. A few substantially new and very recent applications/examples are presented to better show the power of the methods introduced: one in Classical Mechanics (definition of strong conservation laws in a frame-independent setting and a discussion on the way in which conserved quantities depend on the choice of an observer; one in Classical Field Theories (energy and entropy in General Relativity, in its standard formulation, in its spin-frame formulation, in its first order formulation “à la Palatini” and in its extensions to Non-Linear Gravity Theories; one in Quantum Field Theories (applications to conservation laws in Loop Quantum Gravity via spin connections and Barbero–Immirzi connections.
Relevance Theory in Translation
Shao Jun; Jiang Min
2008-01-01
In perspective of relevance theory, translation is regarded as communication. According to relevance theory, communication not only requires encoding, transfer and decoding processes, but also involves inference in addition. As communication, translation decision-making is also based on the human beings' inferential mental faculty. Concentrating on relevance theory, this paper tries to analyze and explain some translation phenomena in two English versions of Cai Gen Tan-My Crude Philosophy of Life.
Measuring the biosphere-atmosphere exchange of total reactive nitrogen by eddy covariance
Ammann, C.; Wolff, V.; Marx, O.; Brümmer, C.; Neftel, A.
2012-11-01
The (net) exchange of reactive nitrogen (Nr) with the atmosphere is an important driver for ecosystem productivity and greenhouse gas exchange. The exchange of airborne Nr includes various trace compounds that usually require different specific measurement techniques, and up to now fast response instruments suitable for eddy covariance measurements are only available for few of these compounds. Here we present eddy covariance flux measurements with a recently introduced converter (TRANC) for the sum of all Nr compounds (∑Nr). Measurements were performed over a managed grassland field with phases of net emission and net deposition of ∑Nr and alternating dominance of oxidized (NOX) and reduced species (NH3). Spectral analysis of the eddy covariance data exhibited the existence of covariance function peaks at a reasonable time lag related to the sampling tube residence time under stationary conditions. Using ogive analysis, the high-frequency damping was quantified to 19%-26% for a low measurement height of 1.2 m and to about 10% for 4.8 m measurement height. ∑Nr concentrations and fluxes were compared to parallel NO and NO2 measurements by dynamic chambers and NH3 measurements by the aerodynamic gradient technique. The average concentration results indicate that the main compounds NO2 and NH3 were converted by the TRANC system with an efficiency of near 100%. With an optimised sample inlet also the fluxes of these compounds were recovered reasonably well including net deposition and net emission phases. The study shows that the TRANC system is suitable for fast response measurements of oxidized and reduced nitrogen compounds and can be used for continuous eddy covariance flux measurements of total reactive nitrogen.
Measuring the biosphere-atmosphere exchange of total reactive nitrogen by eddy covariance
C. Ammann
2012-11-01
Full Text Available The (net exchange of reactive nitrogen (N_{r} with the atmosphere is an important driver for ecosystem productivity and greenhouse gas exchange. The exchange of airborne N_{r} includes various trace compounds that usually require different specific measurement techniques, and up to now fast response instruments suitable for eddy covariance measurements are only available for few of these compounds.
Here we present eddy covariance flux measurements with a recently introduced converter (TRANC for the sum of all N_{r} compounds (∑N_{r}. Measurements were performed over a managed grassland field with phases of net emission and net deposition of ∑N_{r} and alternating dominance of oxidized (NO_{X} and reduced species (NH_{3}. Spectral analysis of the eddy covariance data exhibited the existence of covariance function peaks at a reasonable time lag related to the sampling tube residence time under stationary conditions. Using ogive analysis, the high-frequency damping was quantified to 19%–26% for a low measurement height of 1.2 m and to about 10% for 4.8 m measurement height.
∑N_{r} concentrations and fluxes were compared to parallel NO and NO_{2} measurements by dynamic chambers and NH_{3} measurements by the aerodynamic gradient technique. The average concentration results indicate that the main compounds NO_{2} and NH_{3} were converted by the TRANC system with an efficiency of near 100%. With an optimised sample inlet also the fluxes of these compounds were recovered reasonably well including net deposition and net emission phases. The study shows that the TRANC system is suitable for fast response measurements of oxidized and reduced nitrogen compounds and can be used for continuous eddy covariance flux measurements of total reactive nitrogen.
Measuring the biosphere-atmosphere exchange of total reactive nitrogen by eddy covariance
C. Ammann
2012-06-01
Full Text Available The (net exchange of reactive nitrogen (N_{r} with the atmosphere is an important driver for ecosystem productivity and greenhouse gas exchange. The exchange of airborne N_{r} includes various trace compounds that usually require different specific measurement techniques, and up to now fast response instruments suitable for eddy covariance measurements are only available for few of these compounds.
Here we present eddy covariance flux measurements with a recently introduced converter (TRANC for the sum of all N_{r} compounds (∑N_{r}. Measurements were performed over a managed grassland field with phases of net emission and net deposition of ∑N_{r} and alternating dominance of oxidized (NO_{x} and reduced species (NH_{3}. Spectral analysis of the eddy covariance data exhibited the existence of covariance function peaks at a reasonable time lag related to the sampling tube residence time under stationary conditions. Using ogive analysis, the high-frequency damping was quantified to 19–26% for a low measurement height of 1.2 m and to about 10% for 4.8 m measurement height.
∑N_{r} concentrations and fluxes were compared to parallel NO and NO_{2} measurements by dynamic chambers and NH_{3} measurements by the aerodynamic gradient technique. The average concentration results indicate that close-to-full conversion of the main compounds NO_{2} and NH_{3} was generally obtained by the TRANC system. With an optimised sample inlet also the fluxes of these compounds were recovered fairly including net deposition and net emission phases. The study shows that the TRANC system is suitable for fast response measurements of oxidized and reduced nitrogen compounds and can be used for continuous eddy covariance flux measurements of total reactive nitrogen.
Parallel ICA identifies sub-components of resting state networks that covary with behavioral indices
Timothy eMeier
2012-10-01
Full Text Available Parallel Independent Component Analysis (para-ICA is a multivariate method that can identify complex relationships between different data modalities by simultaneously performing Independent Component Analysis on each data set while finding mutual information between the two data sets. We use para-ICA to test the hypothesis that spatial sub-components of common resting state networks (RSNs covary with specific behavioral measures. Resting state scans and a battery of behavioral indices were collected from 24 younger adults. Group ICA was performed and common RSNs were identified by spatial correlation to publically available templates. Nine RSNs were identified and para-ICA was run on each network with a matrix of behavioral measures serving as the second data type. Five networks had spatial sub-components that significantly correlated with behavioral components. These included a sub-component of the temporo-parietal attention network that differentially covaried with different trial-types of a sustained attention task, sub-components of default mode networks that covaried with attention and working memory tasks, and a sub-component of the bilateral frontal network that split the left inferior frontal gyrus into three clusters according to its cytoarchitecture that differentially covaried with working memory performance. Additionally, we demonstrate the validity of para-ICA in cases with unbalanced dimensions using simulated data.
Ryu, Duchwan
2010-09-28
We consider nonparametric regression analysis in a generalized linear model (GLM) framework for data with covariates that are the subject-specific random effects of longitudinal measurements. The usual assumption that the effects of the longitudinal covariate processes are linear in the GLM may be unrealistic and if this happens it can cast doubt on the inference of observed covariate effects. Allowing the regression functions to be unknown, we propose to apply Bayesian nonparametric methods including cubic smoothing splines or P-splines for the possible nonlinearity and use an additive model in this complex setting. To improve computational efficiency, we propose the use of data-augmentation schemes. The approach allows flexible covariance structures for the random effects and within-subject measurement errors of the longitudinal processes. The posterior model space is explored through a Markov chain Monte Carlo (MCMC) sampler. The proposed methods are illustrated and compared to other approaches, the "naive" approach and the regression calibration, via simulations and by an application that investigates the relationship between obesity in adulthood and childhood growth curves. © 2010, The International Biometric Society.
Ryu, Duchwan; Li, Erning; Mallick, Bani K
2011-06-01
We consider nonparametric regression analysis in a generalized linear model (GLM) framework for data with covariates that are the subject-specific random effects of longitudinal measurements. The usual assumption that the effects of the longitudinal covariate processes are linear in the GLM may be unrealistic and if this happens it can cast doubt on the inference of observed covariate effects. Allowing the regression functions to be unknown, we propose to apply Bayesian nonparametric methods including cubic smoothing splines or P-splines for the possible nonlinearity and use an additive model in this complex setting. To improve computational efficiency, we propose the use of data-augmentation schemes. The approach allows flexible covariance structures for the random effects and within-subject measurement errors of the longitudinal processes. The posterior model space is explored through a Markov chain Monte Carlo (MCMC) sampler. The proposed methods are illustrated and compared to other approaches, the "naive" approach and the regression calibration, via simulations and by an application that investigates the relationship between obesity in adulthood and childhood growth curves.
Structural covariance in the hallucinating brain: a voxel-based morphometry study
Modinos, Gemma; Vercammen, Ans; Mechelli, Andrea; Knegtering, Henderikus; McGuire, Philip K.; Aleman, André
2009-01-01
Background Neuroimaging studies have indicated that a number of cortical regions express altered patterns of structural covariance in schizophrenia. The relation between these alterations and specific psychotic symptoms is yet to be investigated. We used voxel-based morphometry to examine regional grey matter volumes and structural covariance associated with severity of auditory verbal hallucinations. Methods We applied optimized voxel-based morphometry to volumetric magnetic resonance imaging data from 26 patients with medication-resistant auditory verbal hallucinations (AVHs); statistical inferences were made at p < 0.05 after correction for multiple comparisons. Results Grey matter volume in the left inferior frontal gyrus was positively correlated with severity of AVHs. Hallucination severity influenced the pattern of structural covariance between this region and the left superior/middle temporal gyri, the right inferior frontal gyrus and hippocampus, and the insula bilaterally. Limitations The results are based on self-reported severity of auditory hallucinations. Complementing with a clinician-based instrument could have made the findings more compelling. Future studies would benefit from including a measure to control for other symptoms that may covary with AVHs and for the effects of antipsychotic medication. Conclusion The results revealed that overall severity of AVHs modulated cortical intercorrelations between frontotemporal regions involved in language production and verbal monitoring, supporting the critical role of this network in the pathophysiology of hallucinations. PMID:19949723
Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease
Ouyang, Xin; Sun, Xiaoyu; Guo, Ting; Sun, Qiaoyue; Chen, Kewei; Yao, Li; Wu, Xia; Guo, Xiaojuan
2014-03-01
Alzheimer's disease (AD) is a progressive neurodegenerative disease with the clinical symptom of the continuous deterioration of cognitive and memory functions. Multiple diffusion tensor imaging (DTI) indices such as fractional anisotropy (FA) and mean diffusivity (MD) can successfully explain the white matter damages in AD patients. However, most studies focused on the univariate measures (voxel-based analysis) to examine the differences between AD patients and normal controls (NCs). In this investigation, we applied a multivariate independent component analysis (ICA) to investigate the white matter covariances based on FA measurement from DTI data in 35 AD patients and 45 NCs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We found that six independent components (ICs) showed significant FA reductions in white matter covariances in AD compared with NC, including the genu and splenium of corpus callosum (IC-1 and IC-2), middle temporal gyral of temporal lobe (IC-3), sub-gyral of frontal lobe (IC-4 and IC-5) and sub-gyral of parietal lobe (IC-6). Our findings revealed covariant white matter loss in AD patients and suggest that the unsupervised data-driven ICA method is effective to explore the changes of FA in AD. This study assists us in understanding the mechanism of white matter covariant reductions in the development of AD.
López-Fanjul, Carlos; Fernández, Almudena; Toro, Miguel A
2006-03-21
The effect of population bottlenecks on the components of the genetic variance/covariance generated by n neutral independent additive x additive loci has been studied theoretically. In its simplest version, this situation can be modelled by specifying the allele frequencies and homozygous effects at each locus, and an additional factor measuring the strength of the n-th order epistatic interaction. The variance/covariance components in an infinitely large panmictic population (ancestral components) were compared with their expected values at equilibrium over replicates randomly derived from the base population, after t bottlenecks of size N (derived components). Formulae were obtained giving the derived components (and the between-line variance) as functions of the ancestral ones (alternatively, in terms of allele frequencies and effects) and the corresponding inbreeding coefficient F(t). The n-th order derived component of the genetic variance/covariance is continuously eroded by inbreeding, but the remaining components may increase initially until a critical F(t) value is attained, which is inversely related to the order of the pertinent component, and subsequently decline to zero. These changes can be assigned to the between-line variances/covariances of gene substitution and epistatic effects induced by drift. Numerical examples indicate that: (1) the derived additive variance/covariance component will generally exceed its ancestral value unless epistasis is weak; (2) the derived epistatic variance/covariance components will generally exceed their ancestral values unless allele frequencies are extreme; (3) for systems showing equal ancestral additive and total non-additive variance/covariance components, those including a smaller number of epistatic loci may generate a larger excess in additive variance/covariance after bottlenecks than others involving a larger number of loci, provided that F(t) is low. Our results indicate that it is unlikely that the rate of
Berge Léonie
2016-01-01
Full Text Available As the need for precise handling of nuclear data covariances grows ever stronger, no information about covariances of prompt fission neutron spectra (PFNS are available in the evaluated library JEFF-3.2, although present in ENDF/B-VII.1 and JENDL-4.0 libraries for the main fissile isotopes. The aim of this work is to provide an estimation of covariance matrices related to PFNS, in the frame of some commonly used models for the evaluated files, such as the Maxwellian spectrum, the Watt spectrum, or the Madland-Nix spectrum. The evaluation of PFNS through these models involves an adjustment of model parameters to available experimental data, and the calculation of the spectrum variance-covariance matrix arising from experimental uncertainties. We present the results for thermal neutron induced fission of 235U. The systematic experimental uncertainties are propagated via the marginalization technique available in the CONRAD code. They are of great influence on the final covariance matrix, and therefore, on the spectrum uncertainty band width. In addition to this covariance estimation work, we have also investigated the importance on a reactor calculation of the fission spectrum model choice. A study of the vessel fluence depending on the PFNS model is presented. This is done through the propagation of neutrons emitted from a fission source in a simplified PWR using the TRIPOLI-4® code. This last study includes thermal fission spectra from the FIFRELIN Monte-Carlo code dedicated to the simulation of prompt particles emission during fission.
Berge, Léonie; Litaize, Olivier; Serot, Olivier; Archier, Pascal; De Saint Jean, Cyrille; Pénéliau, Yannick; Regnier, David
2016-02-01
As the need for precise handling of nuclear data covariances grows ever stronger, no information about covariances of prompt fission neutron spectra (PFNS) are available in the evaluated library JEFF-3.2, although present in ENDF/B-VII.1 and JENDL-4.0 libraries for the main fissile isotopes. The aim of this work is to provide an estimation of covariance matrices related to PFNS, in the frame of some commonly used models for the evaluated files, such as the Maxwellian spectrum, the Watt spectrum, or the Madland-Nix spectrum. The evaluation of PFNS through these models involves an adjustment of model parameters to available experimental data, and the calculation of the spectrum variance-covariance matrix arising from experimental uncertainties. We present the results for thermal neutron induced fission of 235U. The systematic experimental uncertainties are propagated via the marginalization technique available in the CONRAD code. They are of great influence on the final covariance matrix, and therefore, on the spectrum uncertainty band width. In addition to this covariance estimation work, we have also investigated the importance on a reactor calculation of the fission spectrum model choice. A study of the vessel fluence depending on the PFNS model is presented. This is done through the propagation of neutrons emitted from a fission source in a simplified PWR using the TRIPOLI-4® code. This last study includes thermal fission spectra from the FIFRELIN Monte-Carlo code dedicated to the simulation of prompt particles emission during fission.
Schwabe, Inga; Boomsma, Dorret I; Zeeuw, Eveline L de; Berg, Stéphanie M van den
2016-07-01
The often-used ACE model which decomposes phenotypic variance into additive genetic (A), common-environmental (C) and unique-environmental (E) parts can be extended to include covariates. Collection of these variables however often leads to a large amount of missing data, for example when self-reports (e.g. questionnaires) are not fully completed. The usual approach to handle missing covariate data in twin research results in reduced power to detect statistical effects, as only phenotypic and covariate data of individual twins with complete data can be used. Here we present a full information approach to handle missing covariate data that makes it possible to use all available data. A simulation study shows that, independent of missingness scenario, number of covariates or amount of missingness, the full information approach is more powerful than the usual approach. To illustrate the new method, we applied it to test scores on a Dutch national school achievement test (Eindtoets Basisonderwijs) in the final grade of primary school of 990 twin pairs. The effects of school-aggregated measures (e.g. school denomination, pedagogical philosophy, school size) and the effect of the sex of a twin on these test scores were tested. None of the covariates had a significant effect on individual differences in test scores.
Genome-Wide Scan for Adaptive Divergence and Association with Population-Specific Covariates.
Gautier, Mathieu
2015-12-01
In population genomics studies, accounting for the neutral covariance structure across population allele frequencies is critical to improve the robustness of genome-wide scan approaches. Elaborating on the BayEnv model, this study investigates several modeling extensions (i) to improve the estimation accuracy of the population covariance matrix and all the related measures, (ii) to identify significantly overly differentiated SNPs based on a calibration procedure of the XtX statistics, and (iii) to consider alternative covariate models for analyses of association with population-specific covariables. In particular, the auxiliary variable model allows one to deal with multiple testing issues and, providing the relative marker positions are available, to capture some linkage disequilibrium information. A comprehensive simulation study was carried out to evaluate the performances of these different models. Also, when compared in terms of power, robustness, and computational efficiency to five other state-of-the-art genome-scan methods (BayEnv2, BayScEnv, BayScan, flk, and lfmm), the proposed approaches proved highly effective. For illustration purposes, genotyping data on 18 French cattle breeds were analyzed, leading to the identification of 13 strong signatures of selection. Among these, four (surrounding the KITLG, KIT, EDN3, and ALB genes) contained SNPs strongly associated with the piebald coloration pattern while a fifth (surrounding PLAG1) could be associated to morphological differences across the populations. Finally, analysis of Pool-Seq data from 12 populations of Littorina saxatilis living in two different ecotypes illustrates how the proposed framework might help in addressing relevant ecological issues in nonmodel species. Overall, the proposed methods define a robust Bayesian framework to characterize adaptive genetic differentiation across populations. The BayPass program implementing the different models is available at http://www1.montpellier.inra.fr/CBGP/software/baypass/.
The bispectrum covariance beyond Gaussianity: A log-normal approach
Martin, Sandra; Simon, Patrick
2011-01-01
To investigate and specify the statistical properties of cosmological fields with particular attention to possible non-Gaussian features, accurate formulae for the bispectrum and the bispectrum covariance are required. The bispectrum is the lowest-order statistic providing an estimate for non-Gaussianities of a distribution, and the bispectrum covariance depicts the errors of the bispectrum measurement and their correlation on different scales. Currently, there do exist fitting formulae for the bispectrum and an analytical expression for the bispectrum covariance, but the former is not very accurate and the latter contains several intricate terms and only one of them can be readily evaluated from the power spectrum of the studied field. Neglecting all higher-order terms results in the Gaussian approximation of the bispectrum covariance. We study the range of validity of this Gaussian approximation for two-dimensional non-Gaussian random fields. For this purpose, we simulate Gaussian and non-Gaussian random fi...
Electron localization functions and local measures of the covariance
Paul W Ayers
2005-09-01
The electron localization measure proposed by Becke and Edgecombe is shown to be related to the covariance of the electron pair distribution. Just as with the electron localization function, the local covariance does not seem to be, in and of itself, a useful quantity for elucidating shell structure. A function of the local covariance, however, is useful for this purpose. A different function, based on the hyperbolic tangent, is proposed to elucidate the shell structure encapsulated by the local covariance; this function also seems to work better for the electron localization measure of Becke and Edgecombe. In addition, we propose a different measure for the electron localization that incorporates both the electron localization measure of Becke and Edgecombe and the Laplacian of the electron density; preliminary indications are that this measure is especially good at elucidating the shell structure in valence regions. Methods for evaluating electron localization functions directly from the electron density, without recourse to the Kohn-Sham orbitals, are discussed.
Progress of Covariance Evaluation at the China Nuclear Data Center
Xu, R., E-mail: xuruirui@ciae.ac.cn [China Nuclear Data Center, P.O. Box, 275(41), Beijing 102413 (China); Zhang, Q. [China Nuclear Data Center, P.O. Box, 275(41), Beijing 102413 (China); Shanxi Normal University, Linfen, Shanxi Province 041004 (China); Zhang, Y.; Liu, T.; Ge, Z.; Lu, H.; Sun, Z.; Yu, B. [China Nuclear Data Center, P.O. Box, 275(41), Beijing 102413 (China); Tang, G. [Peking University, Beijing 100871 (China)
2015-01-15
Covariance evaluations at the China Nuclear Data Center focus on the cross sections of structural materials and actinides in the fast neutron energy range. In addition to the well-known Least-squares approach, a method based on the analysis of the sources of experimental uncertainties is especially introduced to generate a covariance matrix for a particular reaction for which multiple measurements are available. The scheme of the covariance evaluation flow is presented, and an example of n+{sup 90}Zr is given to illuminate the whole procedure. It is proven that the accuracy of measurements can be properly incorporated into the covariance and the long-standing small uncertainty problem can be avoided.
Lorentz Covariant Canonical Symplectic Algorithms for Dynamics of Charged Particles
Wang, Yulei; Qin, Hong
2016-01-01
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 (LCCSA) 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 discrete symplectic structure and Lorentz symmetry of the system. For situations with time-dependent electromagnetic fields, which is 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 th...
Group Lasso estimation of high-dimensional covariance matrices
Bigot, Jérémie; Loubes, Jean-Michel; Alvarez, Lilian Muniz
2010-01-01
In this paper, we consider the Group Lasso estimator of the covariance matrix of a stochastic process corrupted by an additive noise. We propose to estimate the covariance matrix in a high-dimensional setting under the assumption that the process has a sparse representation in a large dictionary of basis functions. Using a matrix regression model, we propose a new methodology for high-dimensional covariance matrix estimation based on empirical contrast regularization by a group Lasso penalty. Using such a penalty, the method selects a sparse set of basis functions in the dictionary used to approximate the process, leading to an approximation of the covariance matrix into a low dimensional space. Consistency of the estimator is studied in Frobenius and operator norms and an application to sparse PCA is proposed.
Trouble shooting for covariance fitting in highly correlated data
Yoon, Boram; Lee, Weonjong; Jung, Chulwoo
2011-01-01
We report a possible solution to the trouble that the covariance fitting fails when the data is highly correlated and the covariance matrix has small eigenvalues. As an example, we choose the data analysis of highly correlated $B_K$ data on the basis of the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have an accurate fitting function so that we cannot fit the highly correlated and precise data. When some eigenvalues of the covariance matrix are small, even a tiny error of fitting function can produce large chi-square and spoil the fitting procedure. We have applied a number of prescriptions available in the market such as diagonal approximation and cutoff method. In addition, we present a new method, the eigenmode shift method which fine-tunes the fitting function while keeping the covariance matrix untouched.
Covariance fitting of highly correlated $B_K$ data
Yoon, Boram; Jung, Chulwoo; Lee, Weonjong
2011-01-01
We present the reason why we use the diagonal approximation (uncorrelated fitting) when we perform the data analysis of highly correlated $B_K$ data on the basis of the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have enough statistics to determine the small eigenvalues of the covariance matrix with a high precision. As a result, we have the smallest eigenvalue, which is smaller than the statistical error of the covariance matrix, corresponding to an unphysical eigenmode. We have applied a number of prescriptions available in the market such as the cutoff method and modified covariance matrix method. It turns out that the cutoff method is not a good prescription and the modified covariance matrix method is an even worse one. The diagonal approximation turns out to be a good prescription if the data points are somehow correlated and the statistics are relatively poor.
Covariance of metabolic and hemostatic risk indicators in men and women
Riese, H; Vrijkotte, TGM; Meijer, P; Kluft, C; de Geus, Eco J.
2001-01-01
Background and objective: Multivariate analyses on clusters of metabolic and hemostatic risk indicators implicitly assume good test-retest reliability of these variables, substantial covariance among the various indicators, stability of covariance structure over time, and comparable covariance struc
Some covariance models based on normal scale mixtures
Schlather, Martin
2011-01-01
Modelling spatio-temporal processes has become an important issue in current research. Since Gaussian processes are essentially determined by their second order structure, broad classes of covariance functions are of interest. Here, a new class is described that merges and generalizes various models presented in the literature, in particular models in Gneiting (J. Amer. Statist. Assoc. 97 (2002) 590--600) and Stein (Nonstationary spatial covariance functions (2005) Univ. Chicago). Furthermore, new models and a multivariate extension are introduced.
Web Tool for Constructing a Covariance Matrix from EXFOR Uncertainties
Zerkin V.
2012-05-01
Full Text Available The experimental nuclear reaction database EXFOR contains almost no covariance data because most experimentalists provide experimental data only with uncertainties. With the tool described here a user can construct an experimental covariance matrix from uncertainties using general assumptions when uncertainty information given in EXFOR is poor (or even absent. The tool is publically available in the IAEA EXFOR Web retrieval system [1].
A Generalized Autocovariance Least-Squares Method for Covariance Estimation
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....
Comparison of Methods for Handling Missing Covariate Data
Johansson, Åsa M.; Karlsson, Mats O
2013-01-01
Missing covariate data is a common problem in nonlinear mixed effects modelling of clinical data. The aim of this study was to implement and compare methods for handling missing covariate data in nonlinear mixed effects modelling under different missing data mechanisms. Simulations generated data for 200 individuals with a 50% difference in clearance between males and females. Three different types of missing data mechanisms were simulated and information about sex was missing for 50% of the ...
High-dimensional covariance matrix estimation with missing observations
Lounici, Karim
2014-01-01
In this paper, we study the problem of high-dimensional covariance matrix estimation with missing observations. We propose a simple procedure computationally tractable in high-dimension and that does not require imputation of the missing data. We establish non-asymptotic sparsity oracle inequalities for the estimation of the covariance matrix involving the Frobenius and the spectral norms which are valid for any setting of the sample size, probability of a missing observation and the dimensio...
Eick, Charles; Deutsch, Bill; Fuller, Jennifer; Scott, Fletcher
2008-01-01
Science teachers are always looking for ways to demonstrate the relevance of science to students. By connecting science learning to important societal issues, teachers can motivate students to both enjoy and engage in relevant science (Bennet, Lubben, and Hogarth 2007). To develop that connection, teachers can help students take an active role in…
Perturbative approach to covariance matrix of the matter power spectrum
Mohammed, Irshad; Vlah, Zvonimir
2016-01-01
We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (beat coupling or super-sample variance), and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10\\% level up to $k \\sim 1 h {\\rm Mpc^{-1}}$. We show that all the connected components are dominated by the large-scale modes ($k<0.1 h {\\rm Mpc^{-1}}$), regardless of the value of the wavevectors $k,\\, k'$ of the covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher $k$ it is dominated by a single eigenmode. The full cova...
[Clinical research XIX. From clinical judgment to analysis of covariance].
Pérez-Rodríguez, Marcela; Palacios-Cruz, Lino; Moreno, Jorge; Rivas-Ruiz, Rodolfo; Talavera, Juan O
2014-01-01
The analysis of covariance (ANCOVA) is based on the general linear models. This technique involves a regression model, often multiple, in which the outcome is presented as a continuous variable, the independent variables are qualitative or are introduced into the model as dummy or dichotomous variables, and factors for which adjustment is required (covariates) can be in any measurement level (i.e. nominal, ordinal or continuous). The maneuvers can be entered into the model as 1) fixed effects, or 2) random effects. The difference between fixed effects and random effects depends on the type of information we want from the analysis of the effects. ANCOVA effect separates the independent variables from the effect of co-variables, i.e., corrects the dependent variable eliminating the influence of covariates, given that these variables change in conjunction with maneuvers or treatments, affecting the outcome variable. ANCOVA should be done only if it meets three assumptions: 1) the relationship between the covariate and the outcome is linear, 2) there is homogeneity of slopes, and 3) the covariate and the independent variable are independent from each other.
Gaussian covariance matrices for anisotropic galaxy clustering measurements
Grieb, Jan Niklas; Sánchez, Ariel G.; Salazar-Albornoz, Salvador; Dalla Vecchia, Claudio
2016-04-01
Measurements of the redshift-space galaxy clustering have been a prolific source of cosmological information in recent years. Accurate covariance estimates are an essential step for the validation of galaxy clustering models of the redshift-space two-point statistics. Usually, only a limited set of accurate N-body simulations is available. Thus, assessing the data covariance is not possible or only leads to a noisy estimate. Further, relying on simulated realizations of the survey data means that tests of the cosmology dependence of the covariance are expensive. With these points in mind, this work presents a simple theoretical model for the linear covariance of anisotropic galaxy clustering observations with synthetic catalogues. Considering the Legendre moments (`multipoles') of the two-point statistics and projections into wide bins of the line-of-sight parameter (`clustering wedges'), we describe the modelling of the covariance for these anisotropic clustering measurements for galaxy samples with a trivial geometry in the case of a Gaussian approximation of the clustering likelihood. As main result of this paper, we give the explicit formulae for Fourier and configuration space covariance matrices. To validate our model, we create synthetic halo occupation distribution galaxy catalogues by populating the haloes of an ensemble of large-volume N-body simulations. Using linear and non-linear input power spectra, we find very good agreement between the model predictions and the measurements on the synthetic catalogues in the quasi-linear regime.
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.
Metagenomic covariation along densely sampled environmental gradients in the Red Sea
Thompson, Luke R
2016-07-15
Oceanic microbial diversity covaries with physicochemical parameters. Temperature, for example, explains approximately half of global variation in surface taxonomic abundance. It is unknown, however, whether covariation patterns hold over narrower parameter gradients and spatial scales, and extending to mesopelagic depths. We collected and sequenced 45 epipelagic and mesopelagic microbial metagenomes on a meridional transect through the eastern Red Sea. We asked which environmental parameters explain the most variation in relative abundances of taxonomic groups, gene ortholog groups, and pathways—at a spatial scale of <2000 km, along narrow but well-defined latitudinal and depth-dependent gradients. We also asked how microbes are adapted to gradients and extremes in irradiance, temperature, salinity, and nutrients, examining the responses of individual gene ortholog groups to these parameters. Functional and taxonomic metrics were equally well explained (75–79%) by environmental parameters. However, only functional and not taxonomic covariation patterns were conserved when comparing with an intruding water mass with different physicochemical properties. Temperature explained the most variation in each metric, followed by nitrate, chlorophyll, phosphate, and salinity. That nitrate explained more variation than phosphate suggested nitrogen limitation, consistent with low surface N:P ratios. Covariation of gene ortholog groups with environmental parameters revealed patterns of functional adaptation to the challenging Red Sea environment: high irradiance, temperature, salinity, and low nutrients. Nutrient-acquisition gene ortholog groups were anti-correlated with concentrations of their respective nutrient species, recapturing trends previously observed across much larger distances and environmental gradients. This dataset of metagenomic covariation along densely sampled environmental gradients includes online data exploration supplements, serving as a community
Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families
Dörte Wittenburg
2016-09-01
Full Text Available In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs, to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression methods. In this study, dependencies between SNPs due to linkage and linkage disequilibrium among the chromosome segments were explicitly considered in methods used to estimate the effects of SNPs. The population structure affects the extent of such dependencies, so the covariance among SNP genotypes was derived for half-sib families, which are typical in livestock populations. Conditional on the SNP haplotypes of the common parent (sire, the theoretical covariance was determined using the haplotype frequencies of the population from which the individual parent (dam was derived. The resulting covariance matrix was included in a statistical model for a trait of interest, and this covariance matrix was then used to specify prior assumptions for SNP effects in a Bayesian framework. The approach was applied to one family in simulated scenarios (few and many quantitative trait loci and using semireal data obtained from dairy cattle to identify genome segments that affect performance traits, as well as to investigate the impact on predictive ability. Compared with a method that does not explicitly consider any of the relationship among predictor variables, the accuracy of genetic value prediction was improved by 10–22%. The results show that the inclusion of dependence is particularly important for genomic inference based on small sample sizes.
Environmental covariates of Anopheles arabiensis in a rice agroecosystem in Mwea, Central Kenya.
Mwangangi, Joseph M; Muturi, Ephantus J; Shililu, Josephat I; Muriu, Simon; Jacob, Benjamin; Kabiru, Ephantus W; Mbogo, Charles M; Githure, John I; Novak, Robert J
2007-12-01
Water quality of aquatic habitats is an important determinant of female mosquito oviposition and successful larval development. This study examined the influence of environmental covariates on Anopheles arabiensis mosquito abundance in the Mwea Irrigation Scheme, Central Province of Kenya, prior to implementation of a malaria vector control program. Experimental rice plots were used to examine the environmental covariates responsible for regulating abundance and diversity of the aquatic stages of malaria vectors. Mosquito larval sampling and water quality analysis were done weekly from the flooding stage to the rice maturation stage. Sampling for mosquito larvae was conducted using standard dipping technique. During each larval collection, environmental covariates such as pH, temperature, conductivity, salinity, dissolved oxygen, water depth, and rice stage were measured. Anopheles arabiensis larval density was highest between 1 wk before transplanting and 4 wk after transplanting with peaks at weeks 0, 3, and 8. The fluctuation in values of the various environmental covariates showed characteristic patterns in different rice growth phases depending on the changes taking place due to the agronomic practices. Using a backward linear regression model, the factors that were found to be associated with abundance of An. arabiensis larvae at any of the rice growing phases included the following: dissolved oxygen, pH, turbidity, water depth, rice height, number of rice tillers, salinity, conductivity, and temperature. The environmental covariates associated with abundance of An. arabiensis were associated with early vegetative stage of the rice growth. For effective control of developmental stages of mosquito larvae, the application of larvicides should be done at the vegetative stage and the larvicides should persist until the beginning of the reproductive stage of the rice.
Generation of integral experiment covariance data and their impact on criticality safety validation
Stuke, Maik; Peters, Elisabeth; Sommer, Fabian
2016-11-15
The quantification of statistical dependencies in data of critical experiments and how to account for them properly in validation procedures has been discussed in the literature by various groups. However, these subjects are still an active topic in the Expert Group on Uncertainty Analysis for Criticality Safety Assessment (UACSA) of the OECDNEA Nuclear Science Committee. The latter compiles and publishes the freely available experimental data collection, the International Handbook of Evaluated Criticality Safety Benchmark Experiments, ICSBEP. Most of the experiments were performed as series and share parts of experimental setups, consequently leading to correlation effects in the results. The correct consideration of correlated data seems to be inevitable if the experimental data in a validation procedure is limited or one cannot rely on a sufficient number of uncorrelated data sets, e.g. from different laboratories using different setups. The general determination of correlations and the underlying covariance data as well as the consideration of them in a validation procedure is the focus of the following work. We discuss and demonstrate possible effects on calculated k{sub eff}'s, their uncertainties, and the corresponding covariance matrices due to interpretation of evaluated experimental data and its translation into calculation models. The work shows effects of various modeling approaches, varying distribution functions of parameters and compares and discusses results from the applied Monte-Carlo sampling method with available data on correlations. Our findings indicate that for the reliable determination of integral experimental covariance matrices or the correlation coefficients a detailed study of the underlying experimental data, the modeling approach and assumptions made, and the resulting sensitivity analysis seems to be inevitable. Further, a Bayesian method is discussed to include integral experimental covariance data when estimating an
Covariation of Adolescent Physical Activity and Dietary Behaviors over 12-Months
Rosenberg, Dori; Norman, Gregory J.; Sallis, James F.; Calfas, Karen J.; Patrick, Kevin
2007-01-01
Purpose This study examined covariation among changes in dietary, physical activity, and sedentary behaviors over 12 months among adolescents participating in a health behavior intervention. Evidence of covariation among behaviors would suggest multi-behavior interventions could have synergistic effects. Methods Prospective analyses were conducted with baseline and 12 month assessments from a randomized controlled trial to promote improved diet, physical activity and sedentary behaviors (experimental condition) or SUN protection behaviors (comparison condition). Participants were adolescent girls and boys (N = 878) aged 11 to 15 years on entry. The main outcomes were: diet, based on multiple 24-hour recalls (total fat, grams of fiber, servings of fruit and vegetables, total calories); average daily energy expenditure (kcals/kg) based on 7-Day physical activity recall interviews; daily minutes of moderate-vigorous physical activity minutes from accelerometery; and self-reported daily hours of sedentary behavior. Results Covariation was found between fat and calories (r = .16), fiber and calories (r = .53), fiber and fruit/vegetables (r = .53), calories and fruit/vegetables (r = .34), and fruit and vegetables and sedentary behavior (r = -.12) for the total sample (all p < .01). The pattern of findings was similar for most subgroups defined by sex and study condition. Conclusions The strongest covariation was observed for diet variables that are inherently related (calories and fat, fiber, and fruit/vegetables). Little covariation was detected within or between other diet, physical activity and sedentary behavior domains suggesting that interventions to improve these behaviors in adolescents need to include specific program components for each target behavior of interest. PMID:17950167
Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families.
Wittenburg, Dörte; Teuscher, Friedrich; Klosa, Jan; Reinsch, Norbert
2016-09-08
In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs), to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression methods. In this study, dependencies between SNPs due to linkage and linkage disequilibrium among the chromosome segments were explicitly considered in methods used to estimate the effects of SNPs. The population structure affects the extent of such dependencies, so the covariance among SNP genotypes was derived for half-sib families, which are typical in livestock populations. Conditional on the SNP haplotypes of the common parent (sire), the theoretical covariance was determined using the haplotype frequencies of the population from which the individual parent (dam) was derived. The resulting covariance matrix was included in a statistical model for a trait of interest, and this covariance matrix was then used to specify prior assumptions for SNP effects in a Bayesian framework. The approach was applied to one family in simulated scenarios (few and many quantitative trait loci) and using semireal data obtained from dairy cattle to identify genome segments that affect performance traits, as well as to investigate the impact on predictive ability. Compared with a method that does not explicitly consider any of the relationship among predictor variables, the accuracy of genetic value prediction was improved by 10-22%. The results show that the inclusion of dependence is particularly important for genomic inference based on small sample sizes.
Electron scattering disintegration processes on light nuclei in covariant approach
Kuznietsov, P. E.; Kasatkin, Yu. A.; Klepikov, V. F.
2016-07-01
We provide general analysis of electro-break up process of compound scalar system. We use covariant approach with conserved EM current, which gives the ability to include strong interaction into QED. Therefore, we receive the ability to describe disintegration processes on nonlocal matter fields applying standard Feynman rules of QED. Inclusion of phase exponent into wave function receives a physical sense while we deal with the dominance of strong interaction in the process. We apply Green's function (GF) formalism to describe disintegration processes. Generalized gauge invariant electro-break up process amplitude is considered. One is a sum of traditional pole series and the regular part. We explore the deposits of regular part of amplitude, and its physical sense. A transition from virtual to real photon considered in photon point limit. The general analysis for electro-break up process of component scalar system is given. Precisely conserved nuclear electromagnetic currents at arbitrary square of transited momentum are received. The only undefined quantity in theory is vertex function. Therefore, we have the opportunity to describe electron scattering processes taking into account minimal necessary set of parameters.
Electron scattering disintegration processes on light nuclei in covariant approach
Kuznietsov P.E.
2016-01-01
Full Text Available We provide general analysis of electro-break up process of compound scalar system. We use covariant approach with conserved EM current, which gives the ability to include strong interaction into QED. Therefore, we receive the ability to describe disintegration processes on nonlocal matter fields applying standard Feynman rules of QED. Inclusion of phase exponent into wave function receives a physical sense while we deal with the dominance of strong interaction in the process. We apply Green’s function (GF formalism to describe disintegration processes. Generalized gauge invariant electro-break up process amplitude is considered. One is a sum of traditional pole series and the regular part. We explore the deposits of regular part of amplitude, and its physical sense. A transition from virtual to real photon considered in photon point limit. The general analysis for electro-break up process of component scalar system is given. Precisely conserved nuclear electromagnetic currents at arbitrary square of transited momentum are received. The only undefined quantity in theory is vertex function. Therefore, we have the opportunity to describe electron scattering processes taking into account minimal necessary set of parameters.
Averaged universe confronted to cosmological observations: a fully covariant approach
Wijenayake, Tharake; Ishak, Mustapha
2016-01-01
One of the outstanding problems in general relativistic cosmology is that of the averaging. That is, how the lumpy universe that we observe at small scales averages out to a smooth Friedmann-Lemaitre-Robertson-Walker (FLRW) model. The root of the problem is that averaging does not commute with the Einstein equations that govern the dynamics of the model. This leads to the well-know question of backreaction in cosmology. In this work, we approach the problem using the covariant framework of Macroscopic Gravity (MG). We use its cosmological solution with a flat FLRW macroscopic background where the result of averaging cosmic inhomogeneities has been encapsulated into a backreaction density parameter denoted $\\Omega_\\mathcal{A}$. We constrain this averaged universe using available cosmological data sets of expansion and growth including, for the first time, a full CMB analysis from Planck temperature anisotropy and polarization data, the supernovae data from Union 2.1, the galaxy power spectrum from WiggleZ, the...
Baryon spectrum analysis using Dirac's covariant constraint dynamics
Whitney, Joshua F.; Crater, Horace W.
2014-01-01
We present a relativistic quark model for the baryons that combines three related relativistic formalisms. The three-body constraint formalism of Sazdjian is used to recast three relativistic two-body equations for the three pairs of interacting quarks into a single relativistically covariant three-body equation for the bound state energies, having a Schrodinger-like structure. The two-body equations are the two-body Dirac equations of constraint dynamics derived by Crater and Van Alstine for combined world vector and scalar interactions providing the necessary spin dependent and spin independent interaction terms. The minimal quasipotential formalism of Todorov is used to provide an invariant framework for the vector and scalar dynamics used in the two-body Dirac equations into which is inserted a local simplified version of the Richardson potential. The spectral results are analyzed and compared to experiment using a best fit method and several different algorithms, including a gradient approach, and a Monte Carlo method.
Marital, reproductive, and educational behaviors covary with life expectancy.
Krupp, Daniel Brian
2012-12-01
Theories of "life history evolution" suggest that individuals might adjust the timing of marriage and reproduction, as well as their propensity to terminate a marriage or pregnancy and invest in skill development, in response to indicators of the locally prevailing level of life expectancy. In particular, such theories generate the hypothesis that foreshortened time horizons lead to hastened reproduction and marriage whereas lengthier time horizons increase the likelihood of reproductive and marital termination and lead to greater investment in education. Here, I show that the scheduling and occurrence of marital and reproductive behavior (including both initiation and termination), as well as levels of educational attainment and investment, covary with life expectancy, even after controlling for the effects of affluence. In analyses of variation in marital, reproductive, and educational behaviors at two jurisdictional levels in Canada, life expectancy was positively correlated with patterns of age-specific fertility, age at first marriage, divorce, abortion, conferral of high school and higher education degrees (with the exception of the trades) and mean number of years of schooling. The large and highly consistent relationships observed between life expectancy and the behaviors under investigation suggest that these associations may be mediated by individual "perceptions" of life expectancy, though more research is needed before conclusions can be firmly reached.
Electromagnetic structure of the low-lying baryons in covariant chiral perturbation theory
Camalich, J Martin; Geng, L S; Vacas, M J Vicente
2009-01-01
We report a calculation of the low-lying baryon magnetic moments using covariant chiral perturbation theory within the extended-on-mass-shell renormalization scheme including intermediate octet and decuplet contributions. For the case of the baryon octet, we succeed to improve the Coleman-Glashow description by including the leading SU(3)$_F$-breaking effects coming from the lowest-order loops. We compare with previous attempts at the same order using heavy-baryon and covariant infrared chiral perturbation theory, and discuss the source of the differences. For the case of the decuplet-baryons we fix the only unknown LEC with the well measured magnetic dipole moment of the $\\Omega^-$ and predict the corresponding ones of the $\\Delta(1232)$ isospin multiplet. In particular we obtain $\\mu_{\\Delta^{++}}=6.0(6) \\mu_N$ and $\\mu_{\\Delta^{+}}=2.84(34) \\mu_N$ that compare well with the current experimental information.
A VLBI variance-covariance analysis interactive computer program. M.S. Thesis
Bock, Y.
1980-01-01
An interactive computer program (in FORTRAN) for the variance covariance analysis of VLBI experiments is presented for use in experiment planning, simulation studies and optimal design problems. The interactive mode is especially suited to these types of analyses providing ease of operation as well as savings in time and cost. The geodetic parameters include baseline vector parameters and variations in polar motion and Earth rotation. A discussion of the theroy on which the program is based provides an overview of the VLBI process emphasizing the areas of interest to geodesy. Special emphasis is placed on the problem of determining correlations between simultaneous observations from a network of stations. A model suitable for covariance analyses is presented. Suggestions towards developing optimal observation schedules are included.
Quantifying the Effect of Component Covariances in CMB Extraction from Multi-frequency Data
Phillips, Nicholas G.
2008-01-01
Linear combination methods provide a global method for component separation of multi-frequency data. We present such a method that allows for consideration of possible covariances between the desired cosmic microwave background signal and various foreground signals that are also present. We also recover information on the foregrounds including the number of foregrounds, their spectra and templates. In all this, the covariances, which we would only expect to vanish 'in the mean' are included as parameters expressing the fundamental uncertainty due to this type of cosmic variance. When we make the reasonable assumption that the CMB is Gaussian, we can compute both a mean recovered CMB map and also an RMS error map, The mean map coincides with WMAP's Internal Linear Combination map.
Neutral pion photoproduction on protons in fully covariant ChPT with Delta(1232) loop contributions
Blin, Astrid Hiller; Vacas, Manuel Vicente
2015-01-01
We study the neutral pion photoproduction at near-threshold energies in fully covariant chiral perturbation theory up to O(p^3). When including only nucleonic virtual states in the model, the convergence is too slow. Therefore we test the model when introducing the Delta(1232) resonance as an additional degree of freedom. Some low-energy constants were fitted, converging to values in good agreement with those expected from literature.
Informed Conditioning on Clinical Covariates Increases Power in Case-Control Association Studies
Zaitlen, Noah; Lindstroem, Sara; Pasaniuc, Bogdan; Cornelis, Marilyn; Genovese, Giulio; Pollack, Samuela; Barton, Anne; Bickeboeller, Heike; Donald W. Bowden; Eyre, Steve; Barry I Freedman; Friedman, David J.; Field, John K.; Groop, Leif; Haugen, Aage
2012-01-01
Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low-BMI cases are larger than those estimated from high-BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals...
Criticisms of Relevance Theory
尚静; 孟晔; 焦丽芳
2006-01-01
This paper briefly introduces first the notion of Sperber and Wilson's Relevance Theory. Then, the motivation of S & W putting forward their RT is also mentioned. Secondly, the paper gives some details about the methodology of RT, in which ostensive-inferential communication, context and optimal relevance are highlighted. Thirdly, the paper focuses on the criticisms of RT from different areas of research on human language and communication. Finally, the paper draws a conclusion on the great importance of RT in pragmatics.
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 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.
A simple procedure for the comparison of covariance matrices.
Garcia, Carlos
2012-11-21
Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing the variance explained in each sample by the eigenvectors of its own covariance matrix with that explained by the covariance matrix eigenvectors of the other sample. The rationale of this procedure is that the matrix eigenvectors of two similar samples would explain similar amounts of variance in the two samples. I use computer simulation and morphological covariance matrices from the two morphs in a marine snail hybrid zone to show how the proposed procedure can be used to measure the contribution of the matrices orientation and shape to the overall differentiation. I show how this procedure can detect even modest differences between matrices calculated with moderately sized samples, and how it can be used as the basis for more detailed analyses of the nature of these differences. The new procedure constitutes a useful resource for the comparison of covariance matrices. It could fill the gap between procedures resulting in a single, overall measure of differentiation, and analytical methods based on multiple model comparison not providing such a measure.
A simple procedure for the comparison of covariance matrices
2012-01-01
Background Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing the variance explained in each sample by the eigenvectors of its own covariance matrix with that explained by the covariance matrix eigenvectors of the other sample. The rationale of this procedure is that the matrix eigenvectors of two similar samples would explain similar amounts of variance in the two samples. I use computer simulation and morphological covariance matrices from the two morphs in a marine snail hybrid zone to show how the proposed procedure can be used to measure the contribution of the matrices orientation and shape to the overall differentiation. Results I show how this procedure can detect even modest differences between matrices calculated with moderately sized samples, and how it can be used as the basis for more detailed analyses of the nature of these differences. Conclusions The new procedure constitutes a useful resource for the comparison of covariance matrices. It could fill the gap between procedures resulting in a single, overall measure of differentiation, and analytical methods based on multiple model comparison not providing such a measure. PMID:23171139
A simple procedure for the comparison of covariance matrices
Garcia Carlos
2012-11-01
Full Text Available Abstract Background Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing the variance explained in each sample by the eigenvectors of its own covariance matrix with that explained by the covariance matrix eigenvectors of the other sample. The rationale of this procedure is that the matrix eigenvectors of two similar samples would explain similar amounts of variance in the two samples. I use computer simulation and morphological covariance matrices from the two morphs in a marine snail hybrid zone to show how the proposed procedure can be used to measure the contribution of the matrices orientation and shape to the overall differentiation. Results I show how this procedure can detect even modest differences between matrices calculated with moderately sized samples, and how it can be used as the basis for more detailed analyses of the nature of these differences. Conclusions The new procedure constitutes a useful resource for the comparison of covariance matrices. It could fill the gap between procedures resulting in a single, overall measure of differentiation, and analytical methods based on multiple model comparison not providing such a measure.
Covariant Lyapunov vectors of chaotic Rayleigh-Bénard convection.
Xu, M; Paul, M R
2016-06-01
We explore numerically the high-dimensional spatiotemporal chaos of Rayleigh-Bénard convection using covariant Lyapunov vectors. We integrate the three-dimensional and time-dependent Boussinesq equations for a convection layer in a shallow square box geometry with an aspect ratio of 16 for very long times and for a range of Rayleigh numbers. We simultaneously integrate many copies of the tangent space equations in order to compute the covariant Lyapunov vectors. The dynamics explored has fractal dimensions of 20≲D_{λ}≲50, and we compute on the order of 150 covariant Lyapunov vectors. We use the covariant Lyapunov vectors to quantify the degree of hyperbolicity of the dynamics and the degree of Oseledets splitting and to explore the temporal and spatial dynamics of the Lyapunov vectors. Our results indicate that the chaotic dynamics of Rayleigh-Bénard convection is nonhyperbolic for all of the Rayleigh numbers we have explored. Our results yield that the entire spectrum of covariant Lyapunov vectors that we have computed are tangled as indicated by near tangencies with neighboring vectors. A closer look at the spatiotemporal features of the Lyapunov vectors suggests contributions from structures at two different length scales with differing amounts of localization.
Madrasi, Kumpal; Chaturvedula, Ayyappa; Haberer, Jessica E; Sale, Mark; Fossler, Michael J; Bangsberg, David; Baeten, Jared M; Celum, Connie; Hendrix, Craig W
2016-12-06
Adherence is a major factor in the effectiveness of preexposure prophylaxis (PrEP) for HIV prevention. Modeling patterns of adherence helps to identify influential covariates of different types of adherence as well as to enable clinical trial simulation so that appropriate interventions can be developed. We developed a Markov mixed-effects model to understand the covariates influencing adherence patterns to daily oral PrEP. Electronic adherence records (date and time of medication bottle cap opening) from the Partners PrEP ancillary adherence study with a total of 1147 subjects were used. This study included once-daily dosing regimens of placebo, oral tenofovir disoproxil fumarate (TDF), and TDF in combination with emtricitabine (FTC), administered to HIV-uninfected members of serodiscordant couples. One-coin and first- to third-order Markov models were fit to the data using NONMEM(®) 7.2. Model selection criteria included objective function value (OFV), Akaike information criterion (AIC), visual predictive checks, and posterior predictive checks. Covariates were included based on forward addition (α = 0.05) and backward elimination (α = 0.001). Markov models better described the data than 1-coin models. A third-order Markov model gave the lowest OFV and AIC, but the simpler first-order model was used for covariate model building because no additional benefit on prediction of target measures was observed for higher-order models. Female sex and older age had a positive impact on adherence, whereas Sundays, sexual abstinence, and sex with a partner other than the study partner had a negative impact on adherence. Our findings suggest adherence interventions should consider the role of these factors.
Multichannel Shopper Segments and Their Covariates
Konus, Umut; Verhoef, Peter C.; Neslin, Scott A.
2008-01-01
The proliferation of channels has created new challenges for research, including understanding how consumers may be segmented with respect to their information search and purchase behavior in multichannel environment. This research considers shopping a dynamic process that consists of search and pur
Multichannel Shopper Segments and Their Covariates
Konus, Umut; Verhoef, Peter C.; Neslin, Scott A.
2008-01-01
The proliferation of channels has created new challenges for research, including understanding how consumers may be segmented with respect to their information search and purchase behavior in multichannel environment. This research considers shopping a dynamic process that consists of search and
Predicting Covariance Matrices with Financial Conditions Indexes
A. Opschoor (Anne); D.J.C. van Dijk (Dick); M. van der Wel (Michel)
2013-01-01
textabstractWe model the impact of financial conditions on asset market volatility and correlation. We propose extensions of (factor-)GARCH models for volatility and DCC models for correlation that allow for including indexes that measure financial conditions. In our empirical application we
Predicting Covariance Matrices with Financial Conditions Indexes
A. Opschoor (Anne); D.J.C. van Dijk (Dick); M. van der Wel (Michel)
2013-01-01
textabstractWe model the impact of financial conditions on asset market volatility and correlation. We propose extensions of (factor-)GARCH models for volatility and DCC models for correlation that allow for including indexes that measure financial conditions. In our empirical application we conside
Duality Covariant Solutions in Extended Field Theories
Rudolph, Felix J
2016-01-01
Double field theory and exceptional field theory are formulations of supergravity that make certain dualities manifest symmetries of the action. To achieve this, the geometry is extended by including dual coordinates corresponding to winding modes of the fundamental objects. This geometrically unifies the spacetime metric and the gauge fields (and their local symmetries) in a generalized geometry. Solutions to these extended field theories take the simple form of waves and monopoles in the extended space. From a supergravity point of view they appear as 1/2 BPS objects such as the string, the membrane and the fivebrane in ordinary spacetime. In this thesis double field theory and exceptional field theory are introduced, solutions to their equations of motion are constructed and their properties are analyzed. Further it is established how isometries in the extended space give rise to duality relations between the supergravity solutions. Extensions to these core ideas include studying Goldstone modes, probing s...
Area group: an example of style and paste compositional covariation in Maya pottery
Bishop, R.L.; Reents, D.J.; Harbottle, G.; Sayre, E.V.; van Zelst, L.
1983-06-12
This paper has addressed aspects of ceramic style and iconography as found in Late Classic Maya ceramic art, including the supplemental perspective afforded by the analysis of ceramic paste. The chemical data provide a means to assess the extent of stylistic-paste compositional covariation. Depending upon the strength of that covariation various inferences may be drawn about craft specialization, exchange and information flow within Maya society. At the least, it provides an empirical means of comparing stylistically similar vessels; and when they are members of a chemically homogeneous group, it permits style to be addressed in terms of its variation. Additionally, compositionally defined site or region specific reference units provide a chemical background against which the non-provenienced vessels may be compared, allowing the whole vessels to be related to the archaelogically recovered fragmentary material. Finally, this multidisciplinary approach has been illustrated by preliminary findings concerning a specific group of polychrome vessels, The Area Group.
Hamiltonian approach to GR - Part 2: covariant theory of quantum gravity
Cremaschini, Claudio
2016-01-01
A non-perturbative quantum field theory of General Relativity is presented which leads to a new realization of the theory of Covariant Quantum-Gravity (CQG-theory). The treatment is founded on the recently-identified Hamiltonian structure associated with the classical space-time, i.e., the corresponding manifestly-covariant Hamilton equations and the related Hamilton-Jacobi theory. As shown here the connection with CQG-theory is achieved via the classical GR Hamilton-Jacobi equation, leading to the realization of the CQG-wave equation in 4-scalar form for the corresponding CQG-state and wave-function. The new quantum wave equation exhibits well-known formal properties characteristic of quantum mechanics, including the validity of quantum hydrodynamic equations and suitably-generalized Heisenberg inequalities. In addition, it recovers the classical GR equations in the semiclassical limit, while admitting the possibility of developing further perturbative approximation schemes. Applications of the theory are po...
PRACTICAL METHOD FOR ESTIMATING NEUTRON CROSS SECTION COVARIANCES IN THE RESONANCE REGION
Cho, Y.S.; Oblozinsky, P.; Mughabghab,S.F.; Mattoon,C.M.; Herman,M.
2010-04-30
Recent evaluations of neutron cross section covariances in the resolved resonance region reveal the need for further research in this area. Major issues include declining uncertainties in multigroup representations and proper treatment of scattering radius uncertainty. To address these issues, the present work introduces a practical method based on kernel approximation using resonance parameter uncertainties from the Atlas of Neutron Resonances. Analytical expressions derived for average cross sections in broader energy bins along with their sensitivities provide transparent tool for determining cross section uncertainties. The role of resonance-resonance and bin-bin correlations is specifically studied. As an example we apply this approach to estimate (n,{gamma}) and (n,el) covariances for the structural material {sup 55}Mn.
DEVELOPMENT OF ENDF/B-VII.1 AND ITS COVARIANCE COMPONENT
Herman, M.
2010-04-30
The US nuclear data community, coordinated by CSEWG, is preparing release of the ENDF/B-VII.1 library. This new release will address deficiencies identified in ENDF/B-VII.0, include improved evaluations for some 50-60 materials and provide covariances for more than 110 materials. The major players in this undertaking are LANL, BNL, ORNL, and LLNL. We summarize deficiencies in the ENDF/B-VII.0 and outline development of the new library. We concentrate on the BNL activities which aim in providing covariances for the materials important for the design of the innovative reactors. Finally we outline a futuristic approach, known as assimilation that tries to link nuclear reaction theory and integral experiments.
Extreme eigenvalues of sample covariance and correlation matrices
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...... of the problem at hand. We develop a theory for the point process of the normalized eigenvalues of the sample covariance matrix in the case where rows and columns of the data are linearly dependent. Based on the weak convergence of this point process we derive the limit laws of various functionals...... of the eigenvalues. In the second part, we show that the largest and smallest eigenvalues of a highdimensional sample correlation matrix possess almost sure non-random limits if the truncated variance of the entry distribution is “almost slowly varying”, a condition we describe via moment properties of self...
Residual noise covariance for Planck low-resolution data analysis
Keskitalo, R; Cabella, P; Kisner, T; Poutanen, T; Stompor, R; Bartlett, J G; Borrill, J; Cantalupo, C; De Gasperis, G; De Rosa, A; de Troia, G; Eriksen, H K; Finelli, F; Górski, K M; Gruppuso, A; Hivon, E; Jaffe, A; Keihanen, E; Kurki-Suonio, H; Lawrence, C R; Natoli, P; Paci, F; Polenta, G; Rocha, G
2009-01-01
Aims: Develop and validate tools to estimate residual noise covariance in Planck frequency maps. Quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derive analytical estimates of covariance of the residual noise contained in low-resolution maps produced using a number of map-making approaches. We test these analytical predictions using Monte Carlo simulations and their impact on angular power spectrum estimation. We use simulations to quantify the level of signal errors incurred in different resolution downgrading schemes considered in this work. Results: We find an excellent agreement between the optimal residual noise covariance matrices and Monte Carlo noise maps. For destriping map-makers, the extent of agreement is dictated by the knee frequency of the correlated noise component and the chosen baseline offset length. The significance of signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that...
Adaptive Covariance Inflation in a Multi-Resolution Assimilation Scheme
Hickmann, K. S.; Godinez, H. C.
2015-12-01
When forecasts are performed using modern data assimilation methods observation and model error can be scaledependent. During data assimilation the blending of error across scales can result in model divergence since largeerrors at one scale can be propagated across scales during the analysis step. Wavelet based multi-resolution analysiscan be used to separate scales in model and observations during the application of an ensemble Kalman filter. However,this separation is done at the cost of implementing an ensemble Kalman filter at each scale. This presents problemswhen tuning the covariance inflation parameter at each scale. We present a method to adaptively tune a scale dependentcovariance inflation vector based on balancing the covariance of the innovation and the covariance of observations ofthe ensemble. Our methods are demonstrated on a one dimensional Kuramoto-Sivashinsky (K-S) model known todemonstrate non-linear interactions between scales.
Galaxy-galaxy lensing estimators and their covariance properties
Singh, Sukhdeep; Seljak, Uroš; Slosar, Anže; Gonzalez, Jose Vazquez
2016-01-01
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 catalogs and lenses (specifically the BOSS LOWZ sample). Using mock catalogs 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 density field instead of the over-density field, and that this leads to a significant error increase 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 over-density, we find that the errors are dominated by the shape noise and lens clustering, that empirically estimated covarianc...
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
Analysis of the covariance structure of digital ridge counts in the offspring of monozygotic twins.
Cantor, R M; Nance, W E; Eaves, L J; Winter, P M; Blanchard, M M
1983-03-01
Improved methods for analysis of covariance structures now permit the rigorous testing of multivariate genetic hypotheses. Using Jöreskog's Lisrel IV computer program we have conducted a confirmatory factor analysis of dermal ridge counts on the individual fingers of 509 offspring of 107 monozygotic twin pairs. Prior to the initiation of the model-fitting procedure, the sex-adjusted ridge counts for the offspring of male and female twins were partitioned by a multivariate nested analysis of variance yielding five 10 X 10 variance-covariance matrices containing a total of 275 distinctly observed parameters with which to estimate latent sources of genetic and environmental variation and test hypotheses about the factor structure of those latent causes. To provide an adequate explanation for the observed patterns of covariation, it was necessary to include additive genetic, random environmental, epistatic and maternal effects in the model and a structure for the additive genetic effects which included a general factor and allowed for hand asymmetry and finger symmetry. The results illustrate the value of these methods for the analysis of interrelated metric traits.
Burba, George; Madsen, Rod; Feese, Kristin
2013-04-01
The Eddy Covariance method is a micrometeorological technique for direct high-speed measurements of the transport of gases, heat, and momentum between the earth's surface and the atmosphere. Gas fluxes, emission and exchange rates are carefully characterized from single-point in-situ measurements using permanent or mobile towers, or moving platforms such as automobiles, helicopters, airplanes, etc. Since the early 1990s, this technique has been widely used by micrometeorologists across the globe for quantifying CO2 emission rates from various natural, urban and agricultural ecosystems [1,2], including areas of agricultural carbon sequestration. Presently, over 600 eddy covariance stations are in operation in over 120 countries. In the last 3-5 years, advancements in instrumentation and software have reached the point when they can be effectively used outside the area of micrometeorology, and can prove valuable for geological carbon capture and sequestration, landfill emission measurements, high-precision agriculture and other non-micrometeorological industrial and regulatory applications. In the field of geological carbon capture and sequestration, the magnitude of CO2 seepage fluxes depends on a variety of factors. Emerging projects utilize eddy covariance measurement to monitor large areas where CO2 may escape from the subsurface, to detect and quantify CO2 leakage, and to assure the efficiency of CO2 geological storage [3,4,5,6,7,8]. Although Eddy Covariance is one of the most direct and defensible ways to measure and calculate turbulent fluxes, the method is mathematically complex, and requires careful setup, execution and data processing tailor-fit to a specific site and a project. With this in mind, step-by-step instructions were created to introduce a novice to the conventional Eddy Covariance technique [9], and to assist in further understanding the method through more advanced references such as graduate-level textbooks, flux networks guidelines, journals
Averill, M.; Briggle, A.
2006-12-01
Science policy and knowledge production lately have taken a pragmatic turn. Funding agencies increasingly are requiring scientists to explain the relevance of their work to society. This stems in part from mounting critiques of the "linear model" of knowledge production in which scientists operating according to their own interests or disciplinary standards are presumed to automatically produce knowledge that is of relevance outside of their narrow communities. Many contend that funded scientific research should be linked more directly to societal goals, which implies a shift in the kind of research that will be funded. While both authors support the concept of useful science, we question the exact meaning of "relevance" and the wisdom of allowing it to control research agendas. We hope to contribute to the conversation by thinking more critically about the meaning and limits of the term "relevance" and the trade-offs implicit in a narrow utilitarian approach. The paper will consider which interests tend to be privileged by an emphasis on relevance and address issues such as whose goals ought to be pursued and why, and who gets to decide. We will consider how relevance, narrowly construed, may actually limit the ultimate utility of scientific research. The paper also will reflect on the worthiness of research goals themselves and their relationship to a broader view of what it means to be human and to live in society. Just as there is more to being human than the pragmatic demands of daily life, there is more at issue with knowledge production than finding the most efficient ways to satisfy consumer preferences or fix near-term policy problems. We will conclude by calling for a balanced approach to funding research that addresses society's most pressing needs but also supports innovative research with less immediately apparent application.
Positive semidefinite integrated covariance estimation, factorizations and asynchronicity
Sauri, Orimar; Lunde, Asger; Laurent, Sébastien;
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...... observations as possible. The estimator is positive semidefinite by construction. We derive asymptotic results and confirm their good finite sample properties by means of a Monte Carlo simulation. In the application we forecast portfolio Value-at-Risk and sector risk exposures for a portfolio of 52 stocks. We...
The covariant electromagnetic Casimir effect for real conducting spherical shells
Razmi, H
2016-01-01
Using the covariant electromagnetic Casimir effect (previously introduced for real conducting cylindrical shells [1]), the Casimir force experienced by a spherical shell, under Dirichlet boundary condition, is calculated. The renormalization procedure is based on the plasma cut-off frequency for real conductors. The real case of a gold (silver) sphere is considered and the corresponding electromagnetic Casimir force is computed. In the covariant approach, there isn't any decomposition of fields to TE and TM modes; thus, we do not need to consider the Neumann boundary condition in parallel to the Dirichlet problem and then add their corresponding results.
Some Algorithms for the Conditional Mean Vector and Covariance Matrix
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.
A Blind Detection Algorithm Utilizing Statistical Covariance in Cognitive Radio
Yingxue Li
2012-11-01
Full Text Available As the expression of performance parameters are obtained using asymptotic method in most blind covariance detection algorithm, the paper presented a new blind detection algorithm using cholesky factorization. Utilizing random matrix theory, we derived the performance parameters using non-asymptotic method. The proposed method overcomes the noise uncertainty problem and performs well without any information about the channel, primary user and noise. Numerical simulation results demonstrate that the performance parameters expressions are correct and the new detector outperforms the other blind covariance detectors.
On spectral distribution of high dimensional covariation matrices
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....
Fission yield covariances for JEFF: A Bayesian Monte Carlo method
Leray Olivier
2017-01-01
Full Text Available The JEFF library does not contain fission yield covariances, but simply best estimates and uncertainties. This situation is not unique as all libraries are facing this deficiency, firstly due to the lack of a defined format. An alternative approach is to provide a set of random fission yields, themselves reflecting covariance information. In this work, these random files are obtained combining the information from the JEFF library (fission yields and uncertainties and the theoretical knowledge from the GEF code. Examples of this method are presented for the main actinides together with their impacts on simple burn-up and decay heat calculations.
Neutron Resonance Parameters and Covariance Matrix of 239Pu
Derrien, Herve [ORNL; Leal, Luiz C [ORNL; Larson, Nancy M [ORNL
2008-08-01
In order to obtain the resonance parameters in a single energy range and the corresponding covariance matrix, a reevaluation of 239Pu was performed with the code SAMMY. The most recent experimental data were analyzed or reanalyzed in the energy range thermal to 2.5 keV. The normalization of the fission cross section data was reconsidered by taking into account the most recent measurements of Weston et al. and Wagemans et al. A full resonance parameter covariance matrix was generated. The method used to obtain realistic uncertainties on the average cross section calculated by SAMMY or other processing codes was examined.
High-dimensional covariance matrix estimation with missing observations
Lounici, Karim
2012-01-01
In this paper, we study the problem of high-dimensional approximately low-rank covariance matrix estimation with missing observations. We propose a simple procedure computationally tractable in high-dimension and that does not require imputation of the missing data. We establish non-asymptotic sparsity oracle inequalities for the estimation of the covariance matrix with the Frobenius and spectral norms, valid for any setting of the sample size and the dimension of the observations. We further establish minimax lower bounds showing that our rates are minimax optimal up to a logarithmic factor.
Estimating surface fluxes using eddy covariance and numerical ogive optimization
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...
On Variance and Covariance for Bounded Linear Operators
Chia Shiang LIN
2001-01-01
In this paper we initiate a study of covariance and variance for two operators on a Hilbert space, proving that the c-v (covariance-variance) inequality holds, which is equivalent to the CauchySchwarz inequality. As for applications of the c-v inequality we prove uniformly the Bernstein-type incqualities and equalities, and show the generalized Heinz-Kato-Furuta-type inequalities and equalities,from which a generalization and sharpening of Reid's inequality is obtained. We show that every operator can be expressed as a p-hyponormal-type, and a hyponornal-type operator. Finally, some new characterizations of the Furuta inequality are given.
Covariances for Gamma Spectrometer Efficiency Calibrations
Williams John G.
2016-01-01
Full Text Available An essential part of the efficiency calibration of gamma spectrometers is the determination of uncertainties on the results. Although this is routinely done, it often does not include the correlations between efficiencies at different energies. These can be important in the subsequent use of the detectors to obtain activities for a set of dosimetry reactions. If those values are not mutually independent, then obviously that fact could impact the validity of adjustments or of other conclusions resulting from the analysis. Examples are given of detector calibrations in which the correlations are calculated and propagated through an analysis of measured activities.
Methane fluxes above the Hainich forest by True Eddy Accumulation and Eddy Covariance
Siebicke, Lukas; Gentsch, Lydia; Knohl, Alexander
2016-04-01
Understanding the role of forests for the global methane cycle requires quantifying vegetation-atmosphere exchange of methane, however observations of turbulent methane fluxes remain scarce. Here we measured turbulent fluxes of methane (CH4) above a beech-dominated old-growth forest in the Hainich National Park, Germany, and validated three different measurement approaches: True Eddy Accumulation (TEA, closed-path laser spectroscopy), and eddy covariance (EC, open-path and closed-path laser spectroscopy, respectively). The Hainich flux tower is a long-term Fluxnet and ICOS site with turbulent fluxes and ecosystem observations spanning more than 15 years. The current study is likely the first application of True Eddy Accumulation (TEA) for the measurement of turbulent exchange of methane and one of the very few studies comparing open-path and closed-path eddy covariance (EC) setups side-by-side. We observed uptake of methane by the forest during the day (a methane sink with a maximum rate of 0.03 μmol m-2 s-1 at noon) and no or small fluxes of methane from the forest to the atmosphere at night (a methane source of typically less than 0.01 μmol m-2 s-1) based on continuous True Eddy Accumulation measurements in September 2015. First results comparing TEA to EC CO2 fluxes suggest that True Eddy Accumulation is a valid option for turbulent flux quantifications using slow response gas analysers (here CRDS laser spectroscopy, other potential techniques include mass spectroscopy). The TEA system was one order of magnitude more energy efficient compared to closed-path eddy covariance. The open-path eddy covariance setup required the least amount of user interaction but is often constrained by low signal-to-noise ratios obtained when measuring methane fluxes over forests. Closed-path eddy covariance showed good signal-to-noise ratios in the lab, however in the field it required significant amounts of user intervention in addition to a high power consumption. We conclude
A comparison of covariance structure in wild and laboratory muroid crania.
Jamniczky, Heather A; Hallgrímsson, Benedikt
2009-06-01
Mutations have the ability to produce dramatic changes to covariance structure by altering the variance of covariance-generating developmental processes. Several evolutionary mechanisms exist that may be acting interdependently to stabilize covariance structure, despite this developmental potential for variation within species. We explore covariance structure in the crania of laboratory mouse mutants exhibiting mild-to-significant developmental perturbations of the cranium, and contrast it with covariance structure in related wild muroid taxa. Phenotypic covariance structure is conserved among wild muroidea, but highly variable and mutation-dependent within the laboratory group. We show that covariance structures in natural populations of related species occupy a more restricted portion of covariance structure space than do the covariance structures resulting from single mutations of significant effect or the almost nonexistent genetic differences that separate inbred mouse strains. Our results suggest that developmental constraint is not the primary mechanism acting to stabilize covariance structure, and imply a more important role for other mechanisms.
Zeng, Rongping; Petrick, Nicholas; Gavrielides, Marios A; Myers, Kyle J
2011-10-07
Multi-slice computed tomography (MSCT) scanners have become popular volumetric imaging tools. Deterministic and random properties of the resulting CT scans have been studied in the literature. Due to the large number of voxels in the three-dimensional (3D) volumetric dataset, full characterization of the noise covariance in MSCT scans is difficult to tackle. However, as usage of such datasets for quantitative disease diagnosis grows, so does the importance of understanding the noise properties because of their effect on the accuracy of the clinical outcome. The goal of this work is to study noise covariance in the helical MSCT volumetric dataset. We explore possible approximations to the noise covariance matrix with reduced degrees of freedom, including voxel-based variance, one-dimensional (1D) correlation, two-dimensional (2D) in-plane correlation and the noise power spectrum (NPS). We further examine the effect of various noise covariance models on the accuracy of a prewhitening matched filter nodule size estimation strategy. Our simulation results suggest that the 1D longitudinal, 2D in-plane and NPS prewhitening approaches can improve the performance of nodule size estimation algorithms. When taking into account computational costs in determining noise characterizations, the NPS model may be the most efficient approximation to the MSCT noise covariance matrix.
Reid, J M; Arcese, P; Losdat, S
2014-10-01
The evolutionary trajectories of reproductive systems, including both male and female multiple mating and hence polygyny and polyandry, are expected to depend on the additive genetic variances and covariances in and among components of male reproductive success achieved through different reproductive tactics. However, genetic covariances among key components of male reproductive success have not been estimated in wild populations. We used comprehensive paternity data from socially monogamous but genetically polygynandrous song sparrows (Melospiza melodia) to estimate additive genetic variance and covariance in the total number of offspring a male sired per year outside his social pairings (i.e. his total extra-pair reproductive success achieved through multiple mating) and his liability to sire offspring produced by his socially paired female (i.e. his success in defending within-pair paternity). Both components of male fitness showed nonzero additive genetic variance, and the estimated genetic covariance was positive, implying that males with high additive genetic value for extra-pair reproduction also have high additive genetic propensity to sire their socially paired female's offspring. There was consequently no evidence of a genetic or phenotypic trade-off between male within-pair paternity success and extra-pair reproductive success. Such positive genetic covariance might be expected to facilitate ongoing evolution of polygyny and could also shape the ongoing evolution of polyandry through indirect selection. © 2014 The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.
Classical covariant Poisson structures and Deformation Quantization
Berra-Montiel, Jasel; Palacios-García, César D
2014-01-01
Starting with the well-defined product of quantum fields at two spacetime points, we explore an associated Poisson structure for classical field theories within the deformation quantization formalism. We realize that the induced star-product is naturally related to the standard Moyal product through the causal Green functions connecting points in the space of classical solutions to the equations of motion. Our results resemble the Peierls-DeWitt bracket analyzed in the multisymplectic context. Once our star-product is defined we are able to apply the Wigner-Weyl map in order to introduce a generalized version of Wick's theorem. Finally, we include a couple of examples to explicitly test our method: the real scalar field and the bosonic string. For both models we have encountered generalizations of the creation/annihilation relations, and also a generalization of the Virasoro algebra in the bosonic string case.
Integration measure and extended BRST covariant quantization
Geyer, B; Nersessian, A P; Geyer, Bodo; Lavrov, Petr; Nersessian, Armen
2001-01-01
We propose an extended BRST invariant Lagrangian quantization scheme of general gauge theories based on an explicit realization of the modified triplectic algebra that was announced in our previous investigation (hep-th/0104189). The algebra includes, besides the odd operators $V^a$ appearing in the triplectic formalism, also the odd operators $U^a$ introduced within modified triplectic quantization, both of which being anti-Hamiltonian vector fields. We show that some even supersymplectic structure defined on the space of fields and antifields provides the extended BRST path integral with a well-defined integration measure. All the known Lagrangian quantization schemes based on the extended BRST symmetry are obtained by specifying the (free) parameters of that method.
Lorentz Transformation and General Covariance Principle
Kleyn, Aleks
2008-01-01
I tell about different mathematical tool that is important in general relativity. The text of the book includes definition of geometrical object, concept of reference frame, geometry of metric-affinne manifold. Using this concept I learn few physical applications: dynamics and Lorentz transformation in gravitational fields, Doppler shift. A reference frame in event space is a smooth field of orthonormal bases. Every reference frame is equipped by anholonomic coordinates. Using anholonomic coordinates allows to find out relative speed of two observers and appropriate Lorentz transformation. Synchronization of a reference frame is an anholonomic time coordinate. Simple calculations show how synchronization influences time measurement in the vicinity of the Earth. Measurement of Doppler shift from the star orbiting the black hole helps to determine mass of the black hole. We call a manifold with torsion and nonmetricity the metric\\hyph affine manifold. The nonmetricity leads to a difference between the auto para...
Leitão, Sofia; Stadler, Alfred; Peña, M. T.; Biernat, Elmar P.
2017-01-01
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.
Leitão, Sofia; Peña, M T; Biernat, Elmar P
2016-01-01
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.
Dunham, L. L.
1971-01-01
The "legacy" of the humanities is discussed in terms of relevance, involvement, and other philosophical considerations. Reasons for studying foreign literature in language classes are developed in the article. Comment is also made on attitudes and ideas culled from the writings of Clifton Fadiman, Jean Paul Sartre, and James Baldwin. (RL)
Müller, Emmanuel; Assent, Ira; Günnemann, Stephan
2009-01-01
. We prove that computation of this model is NP-hard. For RESCU, we propose an approximative solution that shows high accuracy with respect to our relevance model. Thorough experiments on synthetic and real world data show that RESCU successfully reduces the result to manageable sizes. It reliably...... achieves top clustering quality while competing approaches show greatly varying performance....
Is Information Still Relevant?
Ma, Lia
2013-01-01
Introduction: The term "information" in information science does not share the characteristics of those of a nomenclature: it does not bear a generally accepted definition and it does not serve as the bases and assumptions for research studies. As the data deluge has arrived, is the concept of information still relevant for information…
Müller, Emmanuel; Assent, Ira; Günnemann, Stephan;
2009-01-01
Subspace clustering aims at detecting clusters in any subspace projection of a high dimensional space. As the number of possible subspace projections is exponential in the number of dimensions, the result is often tremendously large. Recent approaches fail to reduce results to relevant subspace c...
Sheng Zhong
2016-10-01
Full Text Available We consider the problem of genetic association testing of a binary trait in a sample that contains related individuals, where we adjust for relevant covariates and allow for missing data. We propose CERAMIC, an estimating equation approach that can be viewed as a hybrid of logistic regression and linear mixed-effects model (LMM approaches. CERAMIC extends the recently proposed CARAT method to allow samples with related individuals and to incorporate partially missing data. In simulations, we show that CERAMIC outperforms existing LMM and generalized LMM approaches, maintaining high power and correct type 1 error across a wider range of scenarios. CERAMIC results in a particularly large power increase over existing methods when the sample includes related individuals with some missing data (e.g., when some individuals with phenotype and covariate information have missing genotype, because CERAMIC is able to make use of the relationship information to incorporate partially missing data in the analysis while correcting for dependence. Because CERAMIC is based on a retrospective analysis, it is robust to misspecification of the phenotype model, resulting in better control of type 1 error and higher power than that of prospective methods, such as GMMAT, when the phenotype model is misspecified. CERAMIC is computationally efficient for genomewide analysis in samples of related individuals of almost any configuration, including small families, unrelated individuals and even large, complex pedigrees. We apply CERAMIC to data on type 2 diabetes (T2D from the Framingham Heart Study. In a genome scan, 9 of the 10 smallest CERAMIC p-values occur in or near either known T2D susceptibility loci or plausible candidates, verifying that CERAMIC is able to home in on the important loci in a genome scan.
Hamiltonian approach to GR. Pt. 1. Covariant theory of classical gravity
Cremaschini, Claudio [Silesian University in Opava, Faculty of Philosophy and Science, Institute of Physics and Research Center for Theoretical Physics and Astrophysics, Opava (Czech Republic); Tessarotto, Massimo [University of Trieste, Department of Mathematics and Geosciences, Trieste (Italy); Silesian University in Opava, Faculty of Philosophy and Science, Institute of Physics, Opava (Czech Republic)
2017-05-15
A challenging issue in General Relativity concerns the determination of the manifestly covariant continuum Hamiltonian structure underlying the Einstein field equations and the related formulation of the corresponding covariant Hamilton-Jacobi theory. The task is achieved by adopting a synchronous variational principle requiring distinction between the prescribed deterministic metric tensor g(r) ≡ {g_μ_ν(r)} solution of the Einstein field equations which determines the geometry of the background space-time and suitable variational fields x ≡ {g,π} obeying an appropriate set of continuum Hamilton equations, referred to here as GR-Hamilton equations. It is shown that a prerequisite for reaching such a goal is that of casting the same equations in evolutionary form by means of a Lagrangian parametrization for a suitably reduced canonical state. As a result, the corresponding Hamilton-Jacobi theory is established in manifestly covariant form. Physical implications of the theory are discussed. These include the investigation of the structural stability of the GR-Hamilton equations with respect to vacuum solutions of the Einstein equations, assuming that wave-like perturbations are governed by the canonical evolution equations. (orig.)
An Adaptive Approach to Mitigate Background Covariance Limitations in the Ensemble Kalman Filter
Song, Hajoon
2010-07-01
A new approach is proposed to address the background covariance limitations arising from undersampled ensembles and unaccounted model errors in the ensemble Kalman filter (EnKF). The method enhances the representativeness of the EnKF ensemble by augmenting it with new members chosen adaptively to add missing information that prevents the EnKF from fully fitting the data to the ensemble. The vectors to be added are obtained by back projecting the residuals of the observation misfits from the EnKF analysis step onto the state space. The back projection is done using an optimal interpolation (OI) scheme based on an estimated covariance of the subspace missing from the ensemble. In the experiments reported here, the OI uses a preselected stationary background covariance matrix, as in the hybrid EnKF–three-dimensional variational data assimilation (3DVAR) approach, but the resulting correction is included as a new ensemble member instead of being added to all existing ensemble members. The adaptive approach is tested with the Lorenz-96 model. The hybrid EnKF–3DVAR is used as a benchmark to evaluate the performance of the adaptive approach. Assimilation experiments suggest that the new adaptive scheme significantly improves the EnKF behavior when it suffers from small size ensembles and neglected model errors. It was further found to be competitive with the hybrid EnKF–3DVAR approach, depending on ensemble size and data coverage.
Terranova, Nicholas; Serot, Olivier; Archier, Pascal; De Saint Jean, Cyrille; Sumini, Marco
2017-09-01
Fission product yields (FY) are fundamental nuclear data for several applications, including decay heat, shielding, dosimetry, burn-up calculations. To be safe and sustainable, modern and future nuclear systems require accurate knowledge on reactor parameters, with reduced margins of uncertainty. Present nuclear data libraries for FY do not provide consistent and complete uncertainty information which are limited, in many cases, to only variances. In the present work we propose a methodology to evaluate covariance matrices for thermal and fast neutron induced fission yields. The semi-empirical models adopted to evaluate the JEFF-3.1.1 FY library have been used in the Generalized Least Square Method available in CONRAD (COde for Nuclear Reaction Analysis and Data assimilation) to generate covariance matrices for several fissioning systems such as the thermal fission of U235, Pu239 and Pu241 and the fast fission of U238, Pu239 and Pu240. The impact of such covariances on nuclear applications has been estimated using deterministic and Monte Carlo uncertainty propagation techniques. We studied the effects on decay heat and reactivity loss uncertainty estimation for simplified test case geometries, such as PWR and SFR pin-cells. The impact on existing nuclear reactors, such as the Jules Horowitz Reactor under construction at CEA-Cadarache, has also been considered.
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
Analysis of inadvertent microprocessor lag time on eddy covariance results
Karl Zeller; Gary Zimmerman; Ted Hehn; Evgeny Donev; Diane Denny; Jeff Welker
2001-01-01
Researchers using the eddy covariance approach to measuring trace gas fluxes are often hoping to measure carbon dioxide and energy fluxes for ecosystem intercomparisons. This paper demonstrates a systematic microprocessor- caused lag of 20.1 to 20.2 s in a commercial sonic anemometer-analog-to-digital datapacker system operated at 10 Hz. The result of the inadvertent...
Experimental Uncertainty and Covariance Information in EXFOR Library
Schillebeeckx P.
2012-05-01
Full Text Available Compilation of experimental uncertainty and covariance information in the EXFOR Library is discussed. Following the presentation of a brief history of information provided in the EXFOR Library, the current EXFOR Formats and their limitations are reviewed. Proposed extensions for neutron-induced reaction cross sections in the fast neutron region and resonance region are also presented.
How many longitudinal covariate measurements are needed for risk prediction?
Reinikainen, Jaakko; Karvanen, Juha; Tolonen, Hanna
2016-01-01
In epidemiologic follow-up studies, many key covariates, such as smoking, use of medication, blood pressure, and cholesterol, are time varying. Because of practical and financial limitations, time-varying covariates cannot be measured continuously, but only at certain prespecified time points. We study how the number of these longitudinal measurements can be chosen cost-efficiently by evaluating the usefulness of the measurements for risk prediction. The usefulness is addressed by measuring the improvement in model discrimination between models using different amounts of longitudinal information. We use simulated follow-up data and the data from the Finnish East-West study, a follow-up study, with eight longitudinal covariate measurements carried out between 1959 and 1999. In a simulation study, we show how the variability and the hazard ratio of a time-varying covariate are connected to the importance of remeasurements. In the East-West study, it is seen that for older people, the risk predictions obtained using only every other measurement are almost equivalent to the predictions obtained using all eight measurements. Decisions about the study design have significant effects on the costs. The cost-efficiency can be improved by applying the measures of model discrimination to data from previous studies and simulations. Copyright © 2016 Elsevier Inc. All rights reserved.
Nonlinear wave mechanics from classical dynamics and scale covariance
Hammad, F. [Departement TC-SETI, Universite A.Mira de Bejaia, Route Targa Ouzemmour, 06000 Bejaia (Algeria)], E-mail: fayhammad@yahoo.fr
2007-10-29
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.
Covariation of spectral and nonlinear EEG measures with alpha biofeedback.
Fell, J.; Elfadil, H.; Klaver, P.; Roschke, J.; Elger, C.E.; Fernandez, G.S.E.
2002-01-01
This study investigated how different spectral and nonlinear EEG measures covaried with alpha power during auditory alpha biofeedback training, performed by 13 healthy subjects. We found a significant positive correlation of alpha power with the largest Lyapunov-exponent, pointing to an increased
Leading order covariant chiral nucleon-nucleon interaction
Ren, Xiu-Lei; Geng, Li-Sheng; Long, Bing-Wei; Ring, Peter; Meng, Jie
2016-01-01
Motivated by the successes of relativistic theories in studies of atomic/molecular and nuclear systems and the strong need for a covariant chiral force in relativistic nuclear structure studies, we develop a new covariant scheme to construct the nucleon-nucleon interaction in the framework of chiral effective field theory. The chiral interaction is formulated up to leading order with a covariant power counting and a Lorentz invariant chiral Lagrangian. We find that the covariant scheme induces all the six invariant spin operators needed to describe the nuclear force, which are also helpful to achieve cutoff independence for certain partial waves. A detailed investigation of the partial wave potentials shows a better description of the scattering phase shifts with low angular momenta than the leading order Weinberg approach. Particularly, the description of the $^1S_0$, $^3P_0$, and $^1P_1$ partial waves is similar to that of the next-to-leading order Weinberg approach. Our study shows that the relativistic fr...
Hawking Radiation from Plane Symmetric Black Hole Covariant Anomaly
ZENG Xiao-Xiong; HAN Yi-Wen; YANG Shu-Zheng
2009-01-01
Based on the covariant anomaly cancellation method, which is believed to be more refined than the initial approach of Robinson and Wilczek, we discuss Hawking radiation from the plane symmetric black hole. The result shows that Hawking radiation from the non-spherical symmetric black holes also can be derived from the viewpoint of anomaly.
On a new normalization for tractor covariant derivatives
Hammerl, Matthias; Soucek, Vladimir; Silhan, Josef
2010-01-01
A regular normal parabolic geometry of type $G/P$ on a manifold $M$ gives rise to sequences $D_i$ of invariant differential operators, known as the curved version of the BGG resolution. These sequences are constructed from the normal covariant derivative $\
Spectral Density of Sample Covariance Matrices of Colored Noise
Dolezal, Emil
2008-01-01
We study the dependence of the spectral density of the covariance matrix ensemble on the power spectrum of the underlying multivariate signal. The white noise signal leads to the celebrated Marchenko-Pastur formula. We demonstrate results for some colored noise signals.
Negative refraction and positive refraction are not Lorentz covariant
Mackay, Tom G., E-mail: T.Mackay@ed.ac.u [School of Mathematics and Maxwell Institute for Mathematical Sciences, University of Edinburgh, Edinburgh EH9 3JZ (United Kingdom)] [NanoMM - Nanoengineered Metamaterials Group, Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA 16802-6812 (United States); Lakhtakia, Akhlesh, E-mail: akhlesh@psu.ed [NanoMM - Nanoengineered Metamaterials Group, Department of Engineering Science and Mechanics, Pennsylvania State University, University Park, PA 16802-6812 (United States)
2009-12-28
Refraction into a half-space occupied by a pseudochiral omega material moving at constant velocity was studied by directly implementing the Lorentz transformations of electric and magnetic fields. Numerical studies revealed that negative refraction, negative phase velocity and counterposition are not Lorentz-covariant phenomenons in general.
Equivalence between the Covariant and Bardeen Perturbation Formalisms
Vitenti, S D P; Pinto-Neto, N
2013-01-01
In a previous work we obtained a set of necessary conditions for the linear approximation in cosmology. Here we discuss the relations of this approach with the so called covariant perturbations. It is often argued in the literature that one of the main advantages of the covariant approach to describe the cosmological perturbations is that the Bardeen formalism is coordinate dependent. In this paper we will reformulate the Bardeen approach in a completely covariant manner. For that, we introduce the notion of pure and mixed tensors that yields an adequate language to treat both perturbative approaches in a common framework. Additionally, we define full non-linear tensors that at first order correspond to the three known gauge invariant variables $\\Phi$, $\\Psi$ and $\\Xi$. We also stress that in the referred covariant approach one necessarily introduces an additional hyper-surface choice to the problem, and the same tensor combinations above at first order are also hyper-surface invariant making the gauge invari...
A Superfield Formalism of osp(1,2) Covariant Quantization
Lavrov, P M
2001-01-01
We propose a superfield description of osp(1,2) covariant quantization by extending the set of admissibility conditions for the quantum action. We realize a superfield form of the generating equations, specify the vacuum functional and obtain the corresponding transformations of extended BRST symmetry.
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 asymmet
Covariate-adjusted measures of discrimination for survival data
White, Ian R.; Rapsomaniki, Eleni; Wannamethee, S. G.; Morris, R. W.; Willeit, J.; Willeit, P.; Santer, P.; Kiechl, S.; Wald, N.; Ebrahim, S.; Lawlor, D. A.; Gallacher, J.; Yarnell, J. W G; Ben-Shlomo, Y.; Casiglia, E.; Tikhonoff, V.; Sutherland, S. E.; Nietert, P. J.; Keil, J. E.; Bachman, D. L.; Psaty, B. M.; Cushman, M.; Nordestgaard, B. G.; Tybjærg-Hansen, A.; Frikke-Schmidt, R.; Giampaoli, S.; Palmieri, L.; Panico, S.; Pilotto, L.; Vanuzzo, D.; Simons, L. A.; Friedlander, Y.; McCallum, J.; Price, J. F.; McLachlan, S.; Taylor, J. O.; Guralnik, J. M.; Wallace, R. B.; Kohout, F. J.; Cornoni-Huntley, J. C.; Guralnik, J. M.; Blazer, D. G.; Guralnik, J. M.; Phillips, C. L.; Phillips, C. L.; Guralnik, J. M.; Wareham, N. J.; Khaw, K. T.; Brenner, H.; Schöttker, B.; Müller, H. T.; Rothenbacher, D.; Nissinen, A.; Donfrancesco, C.; Giampaoli, S.; Harald, K.; Jousilahti, P. R.; Vartiainen, E.; Salomaa, V.; D'Agostino, R. B.; Wolf, P. A.; Vasan, R. S.; Daimon, M.; Oizumi, T.; Kayama, T.; Kato, T.; Chetrit, A.; Dankner, R.; Lubin, F.; Welin, L.; Svärdsudd, K.; Eriksson, H.; Lappas, G.; Lissner, L.; Mehlig, K.; Björkelund, C.; Nagel, D.; Kiyohara, Y.; Arima, H.; Ninomiya, T.; Hata, J.; Rodriguez, B.; Dekker, J. M.; Nijpels, G.; Stehouwer, C. D A; Iso, H.; Kitamura, A.; Yamagishi, K.; Noda, H.; Goldbourt, U.; Kauhanen, J.; Salonen, J. T.; Tuomainen, T. P.; Meade, T. W.; DeStavola, B. L.; Blokstra, A.; Verschuren, W. M M; Cushman, M.; de Boer, I. H.; Folsom, A. R.; Psaty, B. M.; Koenig, W.; Meisinger, C.; Peters, A.; Verschuren, W. M M; Bueno-de-Mesquita, H. B.; Blokstra, A.; Rosengren, A.; Wilhelmsen, L.; Lappas, G.; Kuller, L. H.; Grandits, G.; Cooper, J. A.; Bauer, K. A.; Davidson, K. W.; Kirkland, S.; Shaffer, J. A.; Shimbo, D.; Kitamura, A.; Iso, H.; Sato, S.; Dullaart, R. P F; Bakker, S. J L; Gansevoort, R. T.; Ducimetiere, P.; Amouyel, P.; Arveiler, D.; Evans, A.; Ferrières, J.; Schulte, H.; Assmann, G.; Jukema, J. W.; Westendorp, R. G J; Sattar, N.; Cantin, B.; Lamarche, B.; Després, J. P.; Wingard, D. L.; Daniels, L. B.; Gudnason, V.; Aspelund, T.; Trevisan, M.; Hofman, A.; Franco, O. H.; Tunstall-Pedoe, H.; Tavendale, R.; Lowe, G. D O; Woodward, M.; Howard, W. J.; Howard, B. V.; Zhang, Y.; Best, L. G.; Umans, J.; Ben-Shlomo, Y.; Davey-Smith, G.; Onat, A.; Nakagawa, H.; Sakurai, M.; Nakamura, K.; Morikawa, Y.; Njølstad, I.; Mathiesen, E. B.; Wilsgaard, T.; Sundström, J.; Gaziano, J. M.; Ridker, P. M.; Marmot, M.; Clarke, R.; Collins, R.; Fletcher, A.; Brunner, E.; Shipley, M.; Kivimaki, M.; Ridker, P. M.; Buring, J.; Rifai, N.; Cook, N.; Ford, I.; Robertson, M.; Marín Ibañez, A.; Feskens, E. J M; Geleijnse, J. M.
2015-01-01
Motivation: Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the
Globally covering a-priori regional gravity covariance models
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`
Genomic variance estimates: With or without disequilibrium covariances?
Lehermeier, C; de Los Campos, G; Wimmer, V; Schön, C-C
2017-06-01
Whole-genome regression methods are often used for estimating genomic heritability: the proportion of phenotypic variance that can be explained by regression on marker genotypes. Recently, there has been an intensive debate on whether and how to account for the contribution of linkage disequilibrium (LD) to genomic variance. Here, we investigate two different methods for genomic variance estimation that differ in their ability to account for LD. By analysing flowering time in a data set on 1,057 fully sequenced Arabidopsis lines with strong evidence for diversifying selection, we observed a large contribution of covariances between quantitative trait loci (QTL) to the genomic variance. The classical estimate of genomic variance that ignores covariances underestimated the genomic variance in the data. The second method accounts for LD explicitly and leads to genomic variance estimates that when added to error variance estimates match the sample variance of phenotypes. This method also allows estimating the covariance between sets of markers when partitioning the genome into subunits. Large covariance estimates between the five Arabidopsis chromosomes indicated that the population structure in the data led to strong LD also between physically unlinked QTL. By consecutively removing population structure from the phenotypic variance using principal component analysis, we show how population structure affects the magnitude of LD contribution and the genomic variance estimates obtained with the two methods. © 2017 Blackwell Verlag GmbH.
Efficient retrieval of landscape Hessian: forced optimal covariance adaptive learning.
Shir, Ofer M; Roslund, Jonathan; Whitley, Darrell; Rabitz, Herschel
2014-06-01
Knowledge of the Hessian matrix at the landscape optimum of a controlled physical observable offers valuable information about the system robustness to control noise. The Hessian can also assist in physical landscape characterization, which is of particular interest in quantum system control experiments. The recently developed landscape theoretical analysis motivated the compilation of an automated method to learn the Hessian matrix about the global optimum without derivative measurements from noisy data. The current study introduces the forced optimal covariance adaptive learning (FOCAL) technique for this purpose. FOCAL relies on the covariance matrix adaptation evolution strategy (CMA-ES) that exploits covariance information amongst the control variables by means of principal component analysis. The FOCAL technique is designed to operate with experimental optimization, generally involving continuous high-dimensional search landscapes (≳30) with large Hessian condition numbers (≳10^{4}). This paper introduces the theoretical foundations of the inverse relationship between the covariance learned by the evolution strategy and the actual Hessian matrix of the landscape. FOCAL is presented and demonstrated to retrieve the Hessian matrix with high fidelity on both model landscapes and quantum control experiments, which are observed to possess nonseparable, nonquadratic search landscapes. The recovered Hessian forms were corroborated by physical knowledge of the systems. The implications of FOCAL extend beyond the investigated studies to potentially cover other physically motivated multivariate landscapes.
Covariate-adjusted measures of discrimination for survival data
White, Ian R.; Rapsomaniki, Eleni; Wannamethee, S. G.; Morris, R. W.; Willeit, J.; Willeit, P.; Santer, P.; Kiechl, S.; Wald, N.; Ebrahim, S.; Lawlor, D. A.; Gallacher, J.; Yarnell, J. W G; Ben-Shlomo, Y.; Casiglia, E.; Tikhonoff, V.; Sutherland, S. E.; Nietert, P. J.; Keil, J. E.; Bachman, D. L.; Psaty, B. M.; Cushman, M.; Nordestgaard, B. G.; Tybjærg-Hansen, A.; Frikke-Schmidt, R.; Giampaoli, S.; Palmieri, L.; Panico, S.; Pilotto, L.; Vanuzzo, D.; Simons, L. A.; Friedlander, Y.; McCallum, J.; Price, J. F.; McLachlan, S.; Taylor, J. O.; Guralnik, J. M.; Wallace, R. B.; Kohout, F. J.; Cornoni-Huntley, J. C.; Guralnik, J. M.; Blazer, D. G.; Guralnik, J. M.; Phillips, C. L.; Phillips, C. L.; Guralnik, J. M.; Wareham, N. J.; Khaw, K. T.; Brenner, H.; Schöttker, B.; Müller, H. T.; Rothenbacher, D.; Nissinen, A.; Donfrancesco, C.; Giampaoli, S.; Harald, K.; Jousilahti, P. R.; Vartiainen, E.; Salomaa, V.; D'Agostino, R. B.; Wolf, P. A.; Vasan, R. S.; Daimon, M.; Oizumi, T.; Kayama, T.; Kato, T.; Chetrit, A.; Dankner, R.; Lubin, F.; Welin, L.; Svärdsudd, K.; Eriksson, H.; Lappas, G.; Lissner, L.; Mehlig, K.; Björkelund, C.; Nagel, D.; Kiyohara, Y.; Arima, H.; Ninomiya, T.; Hata, J.; Rodriguez, B.; Dekker, J. M.; Nijpels, G.; Stehouwer, C. D A; Iso, H.; Kitamura, A.; Yamagishi, K.; Noda, H.; Goldbourt, U.; Kauhanen, J.; Salonen, J. T.; Tuomainen, T. P.; Meade, T. W.; DeStavola, B. L.; Blokstra, A.; Verschuren, W. M M; Cushman, M.; de Boer, I. H.; Folsom, A. R.; Psaty, B. M.; Koenig, W.; Meisinger, C.; Peters, A.; Verschuren, W. M M; Bueno-de-Mesquita, H. B.; Blokstra, A.; Rosengren, A.; Wilhelmsen, L.; Lappas, G.; Kuller, L. H.; Grandits, G.; Cooper, J. A.; Bauer, K. A.; Davidson, K. W.; Kirkland, S.; Shaffer, J. A.; Shimbo, D.; Kitamura, A.; Iso, H.; Sato, S.; Dullaart, R. P F; Bakker, S. J L; Gansevoort, R. T.; Ducimetiere, P.; Amouyel, P.; Arveiler, D.; Evans, A.; Ferrières, J.; Schulte, H.; Assmann, G.; Jukema, J. W.; Westendorp, R. G J; Sattar, N.; Cantin, B.; Lamarche, B.; Després, J. P.; Wingard, D. L.; Daniels, L. B.; Gudnason, V.; Aspelund, T.; Trevisan, M.; Hofman, A.; Franco, O. H.; Tunstall-Pedoe, H.; Tavendale, R.; Lowe, G. D O; Woodward, M.; Howard, W. J.; Howard, B. V.; Zhang, Y.; Best, L. G.; Umans, J.; Ben-Shlomo, Y.; Davey-Smith, G.; Onat, A.; Nakagawa, H.; Sakurai, M.; Nakamura, K.; Morikawa, Y.; Njølstad, I.; Mathiesen, E. B.; Wilsgaard, T.; Sundström, J.; Gaziano, J. M.; Ridker, P. M.; Marmot, M.; Clarke, R.; Collins, R.; Fletcher, A.; Brunner, E.; Shipley, M.; Kivimaki, M.; Ridker, P. M.; Buring, J.; Rifai, N.; Cook, N.; Ford, I.; Robertson, M.; Marín Ibañez, A.; Feskens, E. J M; Geleijnse, J. M.
2015-01-01
Motivation: Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the
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.
High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods
Johnson, Christopher C; Ravikumar, Pradeep
2011-01-01
In this paper we consider the task of estimating the non-zero pattern of the sparse inverse covariance matrix of a zero-mean Gaussian random vector from a set of iid samples. Note that this is also equivalent to recovering the underlying graph structure of a sparse Gaussian Markov Random Field (GMRF). We present two novel greedy approaches to solving this problem. The first estimates the non-zero covariates of the overall inverse covariance matrix using a series of global forward and backward greedy steps. The second estimates the neighborhood of each node in the graph separately, again using greedy forward and backward steps, and combines the intermediate neighborhoods to form an overall estimate. The principal contribution of this paper is a rigorous analysis of the sparsistency, or consistency in recovering the sparsity pattern of the inverse covariance matrix. Surprisingly, we show that both the local and global greedy methods learn the full structure of the model with high probability given just $O(d\\log...
Covariance matrices for use in criticality safety predictability studies
Derrien, H.; Larson, N.M.; Leal, L.C.
1997-09-01
Criticality predictability applications require as input the best available information on fissile and other nuclides. In recent years important work has been performed in the analysis of neutron transmission and cross-section data for fissile nuclei in the resonance region by using the computer code SAMMY. The code uses Bayes method (a form of generalized least squares) for sequential analyses of several sets of experimental data. Values for Reich-Moore resonance parameters, their covariances, and the derivatives with respect to the adjusted parameters (data sensitivities) are obtained. In general, the parameter file contains several thousand values and the dimension of the covariance matrices is correspondingly large. These matrices are not reported in the current evaluated data files due to their large dimensions and to the inadequacy of the file formats. The present work has two goals: the first is to calculate the covariances of group-averaged cross sections from the covariance files generated by SAMMY, because these can be more readily utilized in criticality predictability calculations. The second goal is to propose a more practical interface between SAMMY and the evaluated files. Examples are given for {sup 235}U in the popular 199- and 238-group structures, using the latest ORNL evaluation of the {sup 235}U resonance parameters.
Eddy covariance based methane flux in Sundarbans mangroves, India
Chandra Shekhar Jha; Suraj Reddy Rodda; Kiran Chand Thumaty; A K Raha; V K Dadhwal
2014-07-01
We report the initial results of the methane flux measured using eddy covariance method during summer months from the world’s largest mangrove ecosystem, Sundarbans of India. Mangrove ecosystems are known sources for methane (CH4) having very high global warming potential. In order to quantify the methane flux in mangroves, an eddy covariance flux tower was recently erected in the largest unpolluted and undisturbed mangrove ecosystem in Sundarbans (India). The tower is equipped with eddy covariance flux tower instruments to continuously measure methane fluxes besides the mass and energy fluxes. This paper presents the preliminary results of methane flux variations during summer months (i.e., April and May 2012) in Sundarbans mangrove ecosystem. The mean concentrations of CH4 emission over the study period was 1682 ± 956 ppb. The measured CH4 fluxes computed from eddy covariance technique showed that the study area acts as a net source for CH4 with daily mean flux of 150.22 ± 248.87 mg m−2 day−1. The methane emission as well as its flux showed very high variability diurnally. Though the environmental conditions controlling methane emission is not yet fully understood, an attempt has been made in the present study to analyse the relationships of methane efflux with tidal activity. This present study is part of Indian Space Research Organisation–Geosphere Biosphere Program (ISRO–GBP) initiative under ‘National Carbon Project’.
A New Test for a Normal Covariance Matrix
禹建奇
2015-01-01
The problem of testing the normal covariance matrix equal to a specified matrix is considered.A new Chi-Square test statistic is derived for multivariate normal population.Unlike the likelihood ratio test,the new test is an exact one.
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…
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.
Yeager, Lauren A; Marchand, Philippe; Gill, David A; Baum, Julia K; McPherson, Jana M
2017-07-01
Biophysical conditions, including climate, environmental stress, and habitat availability, are key drivers of many ecological processes (e.g., community assembly and productivity) and associated ecosystem services (e.g., carbon sequestration and fishery production). Furthermore, anthropogenic impacts such as coastal development and fishing can have drastic effects on the structure and function of marine ecosystems. Scientists need to account for environmental variation and human impacts to accurately model, manage, and conserve marine ecosystems. Although there are many types of environmental data available from global remote sensing and open-source data products, some are inaccessible to potential end-users because they exist as global layers in high temporal and spatial resolutions which require considerable computational power to process. Additionally, coastal locations often suffer from missing data or data quality issues which limit the utility of some global marine products for coastal sites. Herein we present the Marine Socio-Environmental Covariates dataset for the global oceans, which consists of environmental and anthropogenic variables summarized in ecologically relevant ways. The dataset includes four sets of environmental variables related to biophysical conditions (net primary productivity models corrected for shallow-water reflectance, wave energy including sheltered-coastline corrections) and landscape context (coral reef and land cover within varying radii). We also present two sets of anthropogenic variables, human population density (within varying radii) and distance to large population center, which can serve as indicators of local human impacts. We have paired global, summarized layers available for download with an online data querying platform that allows users to extract data for specific point locations with finer control of summary statistics. In creating these global layers and online platform, we hope to make the data accessible to a
Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates
Han, Heejoon; Kristensen, Dennis
This paper investigates the asymptotic properties of the Gaussian quasi-maximum-likelihood estimators (QMLE’s) of the GARCH model augmented by including an additional explanatory variable - the so-called GARCH-X model. The additional covariate is allowed to exhibit any degree of persistence as ca...
Covariation between human pelvis shape, stature, and head size alleviates the obstetric dilemma.
Fischer, Barbara; Mitteroecker, Philipp
2015-05-05
Compared with other primates, childbirth is remarkably difficult in humans because the head of a human neonate is large relative to the birth-relevant dimensions of the maternal pelvis. It seems puzzling that females have not evolved wider pelvises despite the high maternal mortality and morbidity risk connected to childbirth. Despite this seeming lack of change in average pelvic morphology, we show that humans have evolved a complex link between pelvis shape, stature, and head circumference that was not recognized before. The identified covariance patterns contribute to ameliorate the "obstetric dilemma." Females with a large head, who are likely to give birth to neonates with a large head, possess birth canals that are shaped to better accommodate large-headed neonates. Short females with an increased risk of cephalopelvic mismatch possess a rounder inlet, which is beneficial for obstetrics. We suggest that these covariances have evolved by the strong correlational selection resulting from childbirth. Although males are not subject to obstetric selection, they also show part of these association patterns, indicating a genetic-developmental origin of integration.
Individual covariation in life-history traits: seeing the trees despite the forest
Cam, E.; Link, W.A.; Cooch, E.G.; Monnat, J.-Y.; Danchin, E.
2002-01-01
We investigated the influence of age on survival and breeding rates in a long-lived species Rissa tridactyla using models with individual random effects permitting variation and covariation in fitness components among individuals. Differences in survival or breeding probabilities among individuals are substantial, and there was positive covariation between survival and breeding probability; birds that were more likely to survive were also more likely to breed, given that they survived. The pattern of age-related variation in these rates detected at the individual level differed from that observed at the population level. Our results provided confirmation of what has been suggested by other investigators: within-cohort phenotypic selection can mask senescence. Although this phenomenon has been extensively studied in humans and captive animals, conclusive evidence of the discrepancy between population-level and individual-level patterns of age-related variation in life-history traits is extremely rare in wild animal populations. Evolutionary studies of the influence of age on life-history traits should use approaches differentiating population level from the genuine influence of age: only the latter is relevant to theories of life-history evolution. The development of models permitting access to individual variation in fitness is a promising advance for the study of senescence and evolutionary processes.
Trust and team performance: A meta-analysis of main effects, moderators, and covariates.
De Jong, Bart A; Dirks, Kurt T; Gillespie, Nicole
2016-08-01
Cumulating evidence from 112 independent studies (N = 7,763 teams), we meta-analytically examine the fundamental questions of whether intrateam trust is positively related to team performance, and the conditions under which it is particularly important. We address these questions by analyzing the overall trust-performance relationship, assessing the robustness of this relationship by controlling for other relevant predictors and covariates, and examining how the strength of this relationship varies as a function of several moderating factors. Our findings confirm that intrateam trust is positively related to team performance, and has an above-average impact (ρ = .30). The covariate analyses show that this relationship holds after controlling for team trust in leader and past team performance, and across dimensions of trust (i.e., cognitive and affective). The moderator analyses indicate that the trust-performance relationship is contingent upon the level of task interdependence, authority differentiation, and skill differentiation in teams. Finally, we conducted preliminary analyses on several emerging issues in the literature regarding the conceptualization and measurement of trust and team performance (i.e., referent of intrateam trust, dimension of performance, performance objectivity). Together, our findings contribute to the literature by helping to (a) integrate the field of intrateam trust research, (b) resolve mixed findings regarding the trust-performance relationship, (c) overcome scholarly skepticism regarding the main effect of trust on team performance, and (d) identify the conditions under which trust is most important for team performance. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Residual noise covariance for Planck low-resolution data analysis
Keskitalo, R.; Ashdown, M. A. J.; Cabella, P.; Kisner, T.; Poutanen, T.; Stompor, R.; Bartlett, J. G.; Borrill, J.; Cantalupo, C.; de Gasperis, G.; de Rosa, A.; de Troia, G.; Eriksen, H. K.; Finelli, F.; Górski, K. M.; Gruppuso, A.; Hivon, E.; Jaffe, A.; Keihänen, E.; Kurki-Suonio, H.; Lawrence, C. R.; Natoli, P.; Paci, F.; Polenta, G.; Rocha, G.
2010-11-01
Aims: We develop and validate tools for estimating residual noise covariance in Planck frequency maps, we also quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derived analytical estimates of covariance of the residual noise contained in low-resolution maps produced using a number of mapmaking approaches. We tested these analytical predictions using both Monte Carlo simulations and by applying them to angular power spectrum estimation. We used simulations to quantify the level of signal errors incurred in the different resolution downgrading schemes considered in this work. Results: We find excellent agreement between the optimal residual noise covariance matrices and Monte Carlo noise maps. For destriping mapmakers, the extent of agreement is dictated by the knee frequency of the correlated noise component and the chosen baseline offset length. Signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the subpercent level at multipoles, ℓ > 2Nside, where Nside is the HEALPix resolution parameter. We show that, for a polarization measurement, reliable characterization of the residual noise is required to draw reliable constraints on large-scale anisotropy. Conclusions: Methods presented and tested in this paper allow for production of low-resolution maps with both controlled sky signal error level and a reliable estimate of covariance of the residual noise. We have also presented a method for smoothing the residual noise covariance matrices to describe the noise correlations in smoothed, bandwidth-limited maps.
Optical modulator including grapene
Liu, Ming; Yin, Xiaobo; Zhang, Xiang
2016-06-07
The present invention provides for a one or more layer graphene optical modulator. In a first exemplary embodiment the optical modulator includes an optical waveguide, a nanoscale oxide spacer adjacent to a working region of the waveguide, and a monolayer graphene sheet adjacent to the spacer. In a second exemplary embodiment, the optical modulator includes at least one pair of active media, where the pair includes an oxide spacer, a first monolayer graphene sheet adjacent to a first side of the spacer, and a second monolayer graphene sheet adjacent to a second side of the spacer, and at least one optical waveguide adjacent to the pair.
Clinical Relevance of Adipokines
Matthias Blüher
2012-10-01
Full Text Available The incidence of obesity has increased dramatically during recent decades. Obesity increases the risk for metabolic and cardiovascular diseases and may therefore contribute to premature death. With increasing fat mass, secretion of adipose tissue derived bioactive molecules (adipokines changes towards a pro-inflammatory, diabetogenic and atherogenic pattern. Adipokines are involved in the regulation of appetite and satiety, energy expenditure, activity, endothelial function, hemostasis, blood pressure, insulin sensitivity, energy metabolism in insulin sensitive tissues, adipogenesis, fat distribution and insulin secretion in pancreatic β-cells. Therefore, adipokines are clinically relevant as biomarkers for fat distribution, adipose tissue function, liver fat content, insulin sensitivity, chronic inflammation and have the potential for future pharmacological treatment strategies for obesity and its related diseases. This review focuses on the clinical relevance of selected adipokines as markers or predictors of obesity related diseases and as potential therapeutic tools or targets in metabolic and cardiovascular diseases.
Bergenholtz, Henning; Gouws, Rufus
2007-01-01
as detrimental to the status of a dictionary as a container of linguistic knowledge. This paper shows that, from a lexicographic perspective, such a distinction is not relevant. What is important is that definitions should contain information that is relevant to and needed by the target users of that specific......In explanatory dictionaries, both general language dictionaries and dictionaries dealing with languages for special purposes, the lexicographic definition is an important item to present the meaning of a given lemma. Due to a strong linguistic bias, resulting from an approach prevalent in the early...... phases of the development of theoretical lexicography, a distinction is often made between encyclopaedic information and semantic information in dictionary definitions, and dictionaries had often been criticized when their definitions were dominated by an encyclopaedic approach. This used to be seen...
Visual Impairment, Including Blindness
... Who Knows What? Survey Item Bank Search for: Visual Impairment, Including Blindness Links updated, April 2017 En ... doesn’t wear his glasses. Back to top Visual Impairments in Children Vision is one of our ...
Wildemuth, Barbara M.
2009-01-01
A user's interaction with a DL is often initiated as the result of the user experiencing an information need of some kind. Aspects of that experience and how it might affect the user's interactions with the DL are discussed in this module. In addition, users continuously make decisions about and evaluations of the materials retrieved from a DL, relative to their information needs. Relevance judgments, and their relationship to the user's information needs, are discussed in this module. Draft
Some asymptotic properties of kriging when the covariance function is misspecified
Stein, M.L.; Handcock, M.S.
1989-02-01
The impact of using an incorrect covariance function of kriging predictors is investigated. Results of Stein (1988) show that the impact on the kriging predictor from not using the correct covariance function is asymptotically negligible as the number of observations increases if the covariance function used is compatible with the actual covariance function on the region of interest R. The definition and some properties of compatibility of covariance functions are given. The compatibility of generalized covariances also is defined. Compatibility supports the intuitively sensible concept that usually only the behavior near the origin of the covariance function is critical for purposes of kriging. However, the commonly used spherical covariance function is an exception: observations at a distance near the range of a spherical covariance function can have a nonnegligible effect on kriging predictors for three-dimensional processes. Finally, a comparison is made with the perturbation approach of Diamond and Armstrong (1984) and some observations of Warnes (1986) are clarified.
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.
Xu, Weijia; Ozer, Stuart; Gutell, Robin R
2009-01-01
With an increasingly large amount of sequences properly aligned, comparative sequence analysis can accurately identify not only common structures formed by standard base pairing but also new types of structural elements and constraints. However, traditional methods are too computationally expensive to perform well on large scale alignment and less effective with the sequences from diversified phylogenetic classifications. We propose a new approach that utilizes coevolutional rates among pairs of nucleotide positions using phylogenetic and evolutionary relationships of the organisms of aligned sequences. With a novel data schema to manage relevant information within a relational database, our method, implemented with a Microsoft SQL Server 2005, showed 90% sensitivity in identifying base pair interactions among 16S ribosomal RNA sequences from Bacteria, at a scale 40 times bigger and 50% better sensitivity than a previous study. The results also indicated covariation signals for a few sets of cross-strand base stacking pairs in secondary structure helices, and other subtle constraints in the RNA structure.
The Entropy of a Vacuum: What Does the Covariant Entropy Count?
Nomura, Yasunori
2013-01-01
We argue that a unitary description of the formation and evaporation of a black hole implies that the Bekenstein-Hawking entropy is the "entropy of a vacuum": the logarithm of the number of possible independent ways in which quantum field theory on a fixed classical spacetime background can emerge in a full quantum theory of gravity. In many cases, the covariant entropy counts this entropy--the degeneracy of emergent quantum field theories in full quantum gravity--with the entropy of particle excitations in each quantum field theory giving only a tiny perturbation. In the Rindler description of a (black hole) horizon, the relevant vacuum degrees of freedom manifest themselves as an extra hidden quantum number carried by the states representing the second exterior region; this quantum number is invisible in the emergent quantum field theory. In a distant picture, these states arise as exponentially degenerate ground and excited states of the intrinsically quantum gravitational degrees of freedom on the stretch...
Construction and use of gene expression covariation matrix
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
Analytic device including nanostructures
Di Fabrizio, Enzo M.
2015-07-02
A device for detecting an analyte in a sample comprising: an array including a plurality of pixels, each pixel including a nanochain comprising: a first nanostructure, a second nanostructure, and a third nanostructure, wherein size of the first nanostructure is larger than that of the second nanostructure, and size of the second nanostructure is larger than that of the third nanostructure, and wherein the first nanostructure, the second nanostructure, and the third nanostructure are positioned on a substrate such that when the nanochain is excited by an energy, an optical field between the second nanostructure and the third nanostructure is stronger than an optical field between the first nanostructure and the second nanostructure, wherein the array is configured to receive a sample; and a detector arranged to collect spectral data from a plurality of pixels of the array.
Greco, Johnny P.; Brandt, Timothy D.
2016-12-01
The recovery of an exoplanet’s atmospheric parameters from its spectrum requires accurate knowledge of the spectral errors and covariances. Unfortunately, the complex image processing used in high-contrast integral-field spectrograph (IFS) observations generally produces spectral covariances that are poorly understood and often ignored. In this work, we show how to measure the spectral errors and covariances and include them self-consistently in parameter retrievals. By combining model exoplanet spectra with a realistic noise model generated from the Gemini Planet Imager (GPI) early science data, we show that ignoring spectral covariance in high-contrast IFS data can both bias inferred parameters and lead to unreliable confidence regions on those parameters. This problem is made worse by the common practice of scaling the χ 2 per degree of freedom to unity; the input parameters then fall outside the 95% confidence regions in as many as ∼80% of noise realizations. The biases we observe can approach the typical levels of precision achieved in high-contrast spectroscopy. Accounting for realistic priors in fully Bayesian retrievals can also have a significant impact on the inferred parameters. Plausible priors on effective temperature and surface gravity can vary by an order of magnitude across the confidence regions appropriate for objects with weak age constraints; priors for objects with good age constraints are dominated by modeling uncertainties. Our methods are directly applicable to existing high-contrast IFSs including GPI and SPHERE, as well as upcoming instruments like CHARIS and, ultimately, WFIRST-AFTA.
Noise Covariance Properties in Dual-Tree Wavelet Decompositions
Chaux, Caroline; Duval, Laurent; 10.1109/TIT.2007.909104
2011-01-01
Dual-tree wavelet decompositions have recently gained much popularity, mainly due to their ability to provide an accurate directional analysis of images combined with a reduced redundancy. When the decomposition of a random process is performed -- which occurs in particular when an additive noise is corrupting the signal to be analyzed -- it is useful to characterize the statistical properties of the dual-tree wavelet coefficients of this process. As dual-tree decompositions constitute overcomplete frame expansions, correlation structures are introduced among the coefficients, even when a white noise is analyzed. In this paper, we show that it is possible to provide an accurate description of the covariance properties of the dual-tree coefficients of a wide-sense stationary process. The expressions of the (cross-)covariance sequences of the coefficients are derived in the one and two-dimensional cases. Asymptotic results are also provided, allowing to predict the behaviour of the second-order moments for larg...
Model Order Selection Rules for Covariance Structure Classification in Radar
Carotenuto, Vincenzo; De Maio, Antonio; Orlando, Danilo; Stoica, Petre
2017-10-01
The adaptive classification of the interference covariance matrix structure for radar signal processing applications is addressed in this paper. This represents a key issue because many detection architectures are synthesized assuming a specific covariance structure which may not necessarily coincide with the actual one due to the joint action of the system and environment uncertainties. The considered classification problem is cast in terms of a multiple hypotheses test with some nested alternatives and the theory of Model Order Selection (MOS) is exploited to devise suitable decision rules. Several MOS techniques, such as the Akaike, Takeuchi, and Bayesian information criteria are adopted and the corresponding merits and drawbacks are discussed. At the analysis stage, illustrating examples for the probability of correct model selection are presented showing the effectiveness of the proposed rules.
Global recoverable reserve estimation by covariance matching constrained kriging
Tercan, A.E. [Hacettepe University, Ankara (Turkey). Dept. of Mining Engineering
2004-10-01
A central problem in mining practice is estimation of global recoverable reserves, i.e., recovered tonnage and mean quality varying with cut-off value over the whole deposit. This article describes the application of covariance matching constrained kriging to the estimation of the global recoverable reserves in a lignite deposit in Turkey. Thickness and calorific value are the variables used in this study. The deposit is divided into 180 panels with 200 m x 200 m size and the mean calorific value of the panels is estimated by covariance matching constrained kriging. Quality tonnage curve is constructed based on the estimated mean values. For comparison, quality tonnage curve from ordinary kriging is also provided.
Sparse Inverse Covariance Selection via Alternating Linearization Methods
Scheinberg, Katya; Goldfarb, Donald
2010-01-01
Gaussian graphical models are of great interest in statistical learning. Because the conditional independencies between different nodes correspond to zero entries in the inverse covariance matrix of the Gaussian distribution, one can learn the structure of the graph by estimating a sparse inverse covariance matrix from sample data, by solving a convex maximum likelihood problem with an $\\ell_1$-regularization term. In this paper, we propose a first-order method based on an alternating linearization technique that exploits the problem's special structure; in particular, the subproblems solved in each iteration have closed-form solutions. Moreover, our algorithm obtains an $\\epsilon$-optimal solution in $O(1/\\epsilon)$ iterations. Numerical experiments on both synthetic and real data from gene association networks show that a practical version of this algorithm outperforms other competitive algorithms.
Covariance in models of loop quantum gravity: Spherical symmetry
Bojowald, Martin; Reyes, Juan D
2015-01-01
Spherically symmetric models of loop quantum gravity have been studied recently by different methods that aim to deal with structure functions in the usual constraint algebra of gravitational systems. As noticed by Gambini and Pullin, a linear redefinition of the constraints (with phase-space dependent coefficients) can be used to eliminate structure functions, even Abelianizing the more-difficult part of the constraint algebra. The Abelianized constraints can then easily be quantized or modified by putative quantum effects. As pointed out here, however, the method does not automatically provide a covariant quantization, defined as an anomaly-free quantum theory with a classical limit in which the usual (off-shell) gauge structure of hypersurface deformations in space-time appears. The holonomy-modified vacuum theory based on Abelianization is covariant in this sense, but matter theories with local degrees of freedom are not. Detailed demonstrations of these statements show complete agreement with results of ...
Estimating surface fluxes using eddy covariance and numerical ogive optimization
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......-frequency contributions interfere with our ability to isolate local biogeochemical processes of interest, as represented by turbulent fluxes. No method currently exists to disentangle low-frequency contributions on flux estimates. Here, we present a novel comprehensive numerical scheme to identify and separate out low...
Batalin-Vilkovisky formalism in locally covariant field theory
Rejzner, Katarzyna
2011-01-01
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 a...