Covariate-adjusted Spearman's rank correlation with probability-scale residuals.
Liu, Qi; Li, Chun; Wanga, Valentine; Shepherd, Bryan E
2018-06-01
It is desirable to adjust Spearman's rank correlation for covariates, yet existing approaches have limitations. For example, the traditionally defined partial Spearman's correlation does not have a sensible population parameter, and the conditional Spearman's correlation defined with copulas cannot be easily generalized to discrete variables. We define population parameters for both partial and conditional Spearman's correlation through concordance-discordance probabilities. The definitions are natural extensions of Spearman's rank correlation in the presence of covariates and are general for any orderable random variables. We show that they can be neatly expressed using probability-scale residuals (PSRs). This connection allows us to derive simple estimators. Our partial estimator for Spearman's correlation between X and Y adjusted for Z is the correlation of PSRs from models of X on Z and of Y on Z, which is analogous to the partial Pearson's correlation derived as the correlation of observed-minus-expected residuals. Our conditional estimator is the conditional correlation of PSRs. We describe estimation and inference, and highlight the use of semiparametric cumulative probability models, which allow preservation of the rank-based nature of Spearman's correlation. We conduct simulations to evaluate the performance of our estimators and compare them with other popular measures of association, demonstrating their robustness and efficiency. We illustrate our method in two applications, a biomarker study and a large survey. © 2017, The International Biometric Society.
Neutron spectrum adjustment. The role of covariances
International Nuclear Information System (INIS)
Remec, I.
1992-01-01
Neutron spectrum adjustment method is shortly reviewed. Practical example dealing with power reactor pressure vessel exposure rates determination is analysed. Adjusted exposure rates are found only slightly affected by the covariances of measured reaction rates and activation cross sections, while the multigroup spectra covariances were found important. Approximate spectra covariance matrices, as suggested in Astm E944-89, were found useful but care is advised if they are applied in adjustments of spectra at locations without dosimetry. (author) [sl
Smooth individual level covariates adjustment in disease mapping.
Huque, Md Hamidul; Anderson, Craig; Walton, Richard; Woolford, Samuel; Ryan, Louise
2018-05-01
Spatial models for disease mapping should ideally account for covariates measured both at individual and area levels. The newly available "indiCAR" model fits the popular conditional autoregresssive (CAR) model by accommodating both individual and group level covariates while adjusting for spatial correlation in the disease rates. This algorithm has been shown to be effective but assumes log-linear associations between individual level covariates and outcome. In many studies, the relationship between individual level covariates and the outcome may be non-log-linear, and methods to track such nonlinearity between individual level covariate and outcome in spatial regression modeling are not well developed. In this paper, we propose a new algorithm, smooth-indiCAR, to fit an extension to the popular conditional autoregresssive model that can accommodate both linear and nonlinear individual level covariate effects while adjusting for group level covariates and spatial correlation in the disease rates. In this formulation, the effect of a continuous individual level covariate is accommodated via penalized splines. We describe a two-step estimation procedure to obtain reliable estimates of individual and group level covariate effects where both individual and group level covariate effects are estimated separately. This distributed computing framework enhances its application in the Big Data domain with a large number of individual/group level covariates. We evaluate the performance of smooth-indiCAR through simulation. Our results indicate that the smooth-indiCAR method provides reliable estimates of all regression and random effect parameters. We illustrate our proposed methodology with an analysis of data on neutropenia admissions in New South Wales (NSW), Australia. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Structural Analysis of Covariance and Correlation Matrices.
Joreskog, Karl G.
1978-01-01
A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…
Covariate-adjusted measures of discrimination for survival data
DEFF Research Database (Denmark)
White, Ian R; Rapsomaniki, Eleni; Frikke-Schmidt, Ruth
2015-01-01
by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination...... statistics in censored survival data. OBJECTIVE: To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s). METHOD: We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators......, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration. RESULTS: The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were...
ACORNS, Covariance and Correlation Matrix Diagonalization
International Nuclear Information System (INIS)
Szondi, E.J.
1990-01-01
1 - Description of program or function: The program allows the user to verify the different types of covariance/correlation matrices used in the activation neutron spectrometry. 2 - Method of solution: The program performs the diagonalization of the input covariance/relative covariance/correlation matrices. The Eigen values are then analyzed to determine the rank of the matrices. If the Eigen vectors of the pertinent correlation matrix have also been calculated, the program can perform a complete factor analysis (generation of the factor matrix and its rotation in Kaiser's 'varimax' sense to select the origin of the correlations). 3 - Restrictions on the complexity of the problem: Matrix size is limited to 60 on PDP and to 100 on IBM PC/AT
Spatial implications of covariate adjustment on patterns of risk
DEFF Research Database (Denmark)
Sabel, Clive Eric; Wilson, Jeff Gaines; Kingham, Simon
2007-01-01
Epidemiological studies that examine the relationship between environmental exposures and health often address other determinants of health that may influence the relationship being studied by adjusting for these factors as covariates. While disease surveillance methods routinely control...... for covariates such as deprivation, there has been limited investigative work on the spatial movement of risk at the intraurban scale due to the adjustment. It is important that the nature of any spatial relocation be well understood as a relocation to areas of increased risk may also introduce additional...... localised factors that influence the exposure-response relationship. This paper examines the spatial patterns of relative risk and clusters of hospitalisations based on an illustrative small-area example from Christchurch, New Zealand. A four-stage test of the spatial relocation effects of covariate...
Directory of Open Access Journals (Sweden)
Tania Dehesh
2015-01-01
Full Text Available Background. Univariate meta-analysis (UM procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS method as a multivariate meta-analysis approach. Methods. We evaluated the efficiency of four new approaches including zero correlation (ZC, common correlation (CC, estimated correlation (EC, and multivariate multilevel correlation (MMC on the estimation bias, mean square error (MSE, and 95% probability coverage of the confidence interval (CI in the synthesis of Cox proportional hazard models coefficients in a simulation study. Result. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. Conclusion. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.
Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi
2015-01-01
Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.
Flexible Bayesian Dynamic Modeling of Covariance and Correlation Matrices
Lan, Shiwei; Holbrook, Andrew; Fortin, Norbert J.; Ombao, Hernando; Shahbaba, Babak
2017-01-01
Modeling covariance (and correlation) matrices is a challenging problem due to the large dimensionality and positive-definiteness constraint. In this paper, we propose a novel Bayesian framework based on decomposing the covariance matrix
Inverse probability weighting for covariate adjustment in randomized studies.
Shen, Changyu; Li, Xiaochun; Li, Lingling
2014-02-20
Covariate adjustment in randomized clinical trials has the potential benefit of precision gain. It also has the potential pitfall of reduced objectivity as it opens the possibility of selecting a 'favorable' model that yields strong treatment benefit estimate. Although there is a large volume of statistical literature targeting on the first aspect, realistic solutions to enforce objective inference and improve precision are rare. As a typical randomized trial needs to accommodate many implementation issues beyond statistical considerations, maintaining the objectivity is at least as important as precision gain if not more, particularly from the perspective of the regulatory agencies. In this article, we propose a two-stage estimation procedure based on inverse probability weighting to achieve better precision without compromising objectivity. The procedure is designed in a way such that the covariate adjustment is performed before seeing the outcome, effectively reducing the possibility of selecting a 'favorable' model that yields a strong intervention effect. Both theoretical and numerical properties of the estimation procedure are presented. Application of the proposed method to a real data example is presented. Copyright © 2013 John Wiley & Sons, Ltd.
Ole E. Barndorff-Nielsen; Neil Shephard
2002-01-01
This paper analyses multivariate high frequency financial data using realised covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis and covariance. It will be based on a fixed interval of time (e.g. a day or week), allowing the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions and covariances change through time. In particular w...
Multisample adjusted U-statistics that account for confounding covariates.
Satten, Glen A; Kong, Maiying; Datta, Somnath
2018-06-19
Multisample U-statistics encompass a wide class of test statistics that allow the comparison of 2 or more distributions. U-statistics are especially powerful because they can be applied to both numeric and nonnumeric data, eg, ordinal and categorical data where a pairwise similarity or distance-like measure between categories is available. However, when comparing the distribution of a variable across 2 or more groups, observed differences may be due to confounding covariates. For example, in a case-control study, the distribution of exposure in cases may differ from that in controls entirely because of variables that are related to both exposure and case status and are distributed differently among case and control participants. We propose to use individually reweighted data (ie, using the stratification score for retrospective data or the propensity score for prospective data) to construct adjusted U-statistics that can test the equality of distributions across 2 (or more) groups in the presence of confounding covariates. Asymptotic normality of our adjusted U-statistics is established and a closed form expression of their asymptotic variance is presented. The utility of our approach is demonstrated through simulation studies, as well as in an analysis of data from a case-control study conducted among African-Americans, comparing whether the similarity in haplotypes (ie, sets of adjacent genetic loci inherited from the same parent) occurring in a case and a control participant differs from the similarity in haplotypes occurring in 2 control participants. Copyright © 2018 John Wiley & Sons, Ltd.
Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data
Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.
2014-01-01
In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Shephard, N.
2004-01-01
This paper analyses multivariate high frequency financial data using realized covariation. We provide a new asymptotic distribution theory for standard methods such as regression, correlation analysis, and covariance. It will be based on a fixed interval of time (e.g., a day or week), allowing...... the number of high frequency returns during this period to go to infinity. Our analysis allows us to study how high frequency correlations, regressions, and covariances change through time. In particular we provide confidence intervals for each of these quantities....
Asset allocation with different covariance/correlation estimators
Μανταφούνη, Σοφία
2007-01-01
The subject of the study is to test whether the use of different covariance – correlation estimators than the historical covariance matrix that is widely used, would help in portfolio optimization through the mean-variance analysis. In other words, if an investor would like to use the mean-variance analysis in order to invest in assets like stocks or indices, would it be of some help to use more sophisticated estimators for the covariance matrix of the returns of his portfolio? The procedure ...
Nimon, Kim; Henson, Robin K.
2015-01-01
The authors empirically examined whether the validity of a residualized dependent variable after covariance adjustment is comparable to that of the original variable of interest. When variance of a dependent variable is removed as a result of one or more covariates, the residual variance may not reflect the same meaning. Using the pretest-posttest…
Flexible Bayesian Dynamic Modeling of Covariance and Correlation Matrices
Lan, Shiwei
2017-11-08
Modeling covariance (and correlation) matrices is a challenging problem due to the large dimensionality and positive-definiteness constraint. In this paper, we propose a novel Bayesian framework based on decomposing the covariance matrix into variance and correlation matrices. The highlight is that the correlations are represented as products of vectors on unit spheres. We propose a variety of distributions on spheres (e.g. the squared-Dirichlet distribution) to induce flexible prior distributions for covariance matrices that go beyond the commonly used inverse-Wishart prior. To handle the intractability of the resulting posterior, we introduce the adaptive $\\\\Delta$-Spherical Hamiltonian Monte Carlo. We also extend our structured framework to dynamic cases and introduce unit-vector Gaussian process priors for modeling the evolution of correlation among multiple time series. Using an example of Normal-Inverse-Wishart problem, a simulated periodic process, and an analysis of local field potential data (collected from the hippocampus of rats performing a complex sequence memory task), we demonstrated the validity and effectiveness of our proposed framework for (dynamic) modeling covariance and correlation matrices.
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.
A comparison of methods to adjust for continuous covariates in the analysis of randomised trials
Directory of Open Access Journals (Sweden)
Brennan C. Kahan
2016-04-01
Full Text Available Abstract Background Although covariate adjustment in the analysis of randomised trials can be beneficial, adjustment for continuous covariates is complicated by the fact that the association between covariate and outcome must be specified. Misspecification of this association can lead to reduced power, and potentially incorrect conclusions regarding treatment efficacy. Methods We compared several methods of adjustment to determine which is best when the association between covariate and outcome is unknown. We assessed (a dichotomisation or categorisation; (b assuming a linear association with outcome; (c using fractional polynomials with one (FP1 or two (FP2 polynomial terms; and (d using restricted cubic splines with 3 or 5 knots. We evaluated each method using simulation and through a re-analysis of trial datasets. Results Methods which kept covariates as continuous typically had higher power than methods which used categorisation. Dichotomisation, categorisation, and assuming a linear association all led to large reductions in power when the true association was non-linear. FP2 models and restricted cubic splines with 3 or 5 knots performed best overall. Conclusions For the analysis of randomised trials we recommend (1 adjusting for continuous covariates even if their association with outcome is unknown; (2 keeping covariates as continuous; and (3 using fractional polynomials with two polynomial terms or restricted cubic splines with 3 to 5 knots when a linear association is in doubt.
Testing power-law cross-correlations: Rescaled covariance test
Czech Academy of Sciences Publication Activity Database
Krištoufek, Ladislav
2013-01-01
Roč. 86, č. 10 (2013), 418-1-418-15 ISSN 1434-6028 R&D Projects: GA ČR GA402/09/0965 Institutional support: RVO:67985556 Keywords : power-law cross-correlations * testing * long-term memory Subject RIV: AH - Economics Impact factor: 1.463, year: 2013 http://library.utia.cas.cz/separaty/2013/E/kristoufek-testing power-law cross-correlations rescaled covariance test.pdf
Estimating correlation and covariance matrices by weighting of market similarity
Michael C. M\\"unnix; Rudi Sch\\"afer; Oliver Grothe
2010-01-01
We discuss a weighted estimation of correlation and covariance matrices from historical financial data. To this end, we introduce a weighting scheme that accounts for similarity of previous market conditions to the present one. The resulting estimators are less biased and show lower variance than either unweighted or exponentially weighted estimators. The weighting scheme is based on a similarity measure which compares the current correlation structure of the market to the structures at past ...
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.
DEFF Research Database (Denmark)
Vansteelandt, S.; Martinussen, Torben; Tchetgen, E. J Tchetgen
2014-01-01
We consider additive hazard models (Aalen, 1989) for the effect of a randomized treatment on a survival outcome, adjusting for auxiliary baseline covariates. We demonstrate that the Aalen least-squares estimator of the treatment effect parameter is asymptotically unbiased, even when the hazard...... that, in view of its robustness against model misspecification, Aalen least-squares estimation is attractive for evaluating treatment effects on a survival outcome in randomized experiments, and the primary reasons to consider baseline covariate adjustment in such settings could be interest in subgroup......'s dependence on time or on the auxiliary covariates is misspecified, and even away from the null hypothesis of no treatment effect. We furthermore show that adjustment for auxiliary baseline covariates does not change the asymptotic variance of the estimator of the effect of a randomized treatment. We conclude...
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.
Lee, Paul H
2016-08-01
This study aims to show that under several assumptions, in randomized controlled trials (RCTs), unadjusted, crude analysis will underestimate the Cohen's d effect size of the treatment, and an unbiased estimate of effect size can be obtained only by adjusting for all predictors of the outcome. Four simulations were performed to examine the effects of adjustment on the estimated effect size of the treatment and power of the analysis. In addition, we analyzed data from the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) study (older adults aged 65-94), an RCT with three treatment arms and one control arm. We showed that (1) the number of unadjusted covariates was associated with the effect size of the treatment; (2) the biasedness of effect size estimation was minimized if all covariates were adjusted for; (3) the power of the statistical analysis slightly decreased with the number of adjusted noise variables; and (4) exhaustively searching the covariates and noise variables adjusted for can lead to exaggeration of the true effect size. Analysis of the ACTIVE study data showed that the effect sizes adjusting for covariates of all three treatments were 7.39-24.70% larger than their unadjusted counterparts, whereas the effect size would be elevated by at most 57.92% by exhaustively searching the variables adjusted for. All covariates of the outcome in RCTs should be adjusted for, and if the effect of a particular variable on the outcome is unknown, adjustment will do more good than harm. Copyright © 2016 Elsevier Inc. All rights reserved.
ORACLE: an adjusted cross-section and covariance library for fast-reactor analysis
International Nuclear Information System (INIS)
Yeivin, Y.; Marable, J.H.; Weisbin, C.R.; Wagschal, J.J.
1980-01-01
Benchmark integral-experiment values from six fast critical-reactor assemblies and two standard neutron fields are combined with corresponding calculations using group cross sections based on ENDF/B-V in a least-squares data adjustment using evaluated covariances from ENDF/B-V and supporting covariance evaluations. Purpose is to produce an adjusted cross-section and covariance library which is based on well-documented data and methods and which is suitable for fast-reactor design. By use of such a library, data- and methods-related biases of calculated performance parameters should be reduced and uncertainties of the calculated values minimized. Consistency of the extensive data base is analyzed using the chi-square test. This adjusted library ORACLE will be available shortly
Extreme eigenvalues of sample covariance and correlation matrices
DEFF Research Database (Denmark)
Heiny, Johannes
This thesis is concerned with asymptotic properties of the eigenvalues of high-dimensional sample covariance and correlation matrices under an infinite fourth moment of the entries. In the first part, we study the joint distributional convergence of the largest eigenvalues of the sample covariance...... matrix of a p-dimensional heavy-tailed time series when p converges to infinity together with the sample size n. We generalize the growth rates of p existing in the literature. Assuming a regular variation condition with tail index ... eigenvalues are essentially determined by the extreme order statistics from an array of iid random variables. The asymptotic behavior of the extreme eigenvalues is then derived routinely from classical extreme value theory. The resulting approximations are strikingly simple considering the high dimension...
DEFF Research Database (Denmark)
He, Peng; Eriksson, Frank; Scheike, Thomas H.
2016-01-01
function by fitting the Cox model for the censoring distribution and using the predictive probability for each individual. Our simulation study shows that the covariate-adjusted weight estimator is basically unbiased when the censoring time depends on the covariates, and the covariate-adjusted weight......With competing risks data, one often needs to assess the treatment and covariate effects on the cumulative incidence function. Fine and Gray proposed a proportional hazards regression model for the subdistribution of a competing risk with the assumption that the censoring distribution...... and the covariates are independent. Covariate-dependent censoring sometimes occurs in medical studies. In this paper, we study the proportional hazards regression model for the subdistribution of a competing risk with proper adjustments for covariate-dependent censoring. We consider a covariate-adjusted weight...
Solid-state NMR covariance of homonuclear correlation spectra.
Hu, Bingwen; Amoureux, Jean-Paul; Trebosc, Julien; Deschamps, Michael; Tricot, Gregory
2008-04-07
Direct covariance NMR spectroscopy, which does not involve a Fourier transformation along the indirect dimension, is demonstrated to obtain homonuclear correlation two-dimensional (2D) spectra in the solid state. In contrast to the usual 2D Fourier transform (2D-FT) NMR, in a 2D covariance (2D-Cov) spectrum the spectral resolution in the indirect dimension is determined by the resolution along the detection dimension, thereby largely reducing the time-consuming indirect sampling requirement. The covariance method does not need any separate phase correction or apodization along the indirect dimension because it uses those applied in the detection dimension. We compare in detail the specifications obtained with 2D-FT and 2D-Cov, for narrow and broad resonances. The efficiency of the covariance data treatment is demonstrated in organic and inorganic samples that are both well crystallized and amorphous, for spin -1/2 nuclei with 13C, 29Si, and 31P through-space or through-bond homonuclear 2D correlation spectra. In all cases, the experimental time has been reduced by at least a factor of 10, without any loss of resolution and signal to noise ratio, with respect to what is necessary with the 2D-FT NMR. According to this method, we have been able to study the silicate network of glasses by 2D NMR within reasonable experimental time despite the very long relaxation time of the 29Si nucleus. The main limitation of the 2D-Cov data treatment is related to the introduction of autocorrelated peaks onto the diagonal, which does not represent any actual connectivity.
Steiner, Peter M.; Cook, Thomas D.; Shadish, William R.
2011-01-01
The effect of unreliability of measurement on propensity score (PS) adjusted treatment effects has not been previously studied. The authors report on a study simulating different degrees of unreliability in the multiple covariates that were used to estimate the PS. The simulation uses the same data as two prior studies. Shadish, Clark, and Steiner…
Some remarks on estimating a covariance structure model from a sample correlation matrix
Maydeu Olivares, Alberto; Hernández Estrada, Adolfo
2000-01-01
A popular model in structural equation modeling involves a multivariate normal density with a structured covariance matrix that has been categorized according to a set of thresholds. In this setup one may estimate the covariance structure parameters from the sample tetrachoricl polychoric correlations but only if the covariance structure is scale invariant. Doing so when the covariance structure is not scale invariant results in estimating a more restricted covariance structure than the one i...
Effortless assignment with 4D covariance sequential correlation maps.
Harden, Bradley J; Mishra, Subrata H; Frueh, Dominique P
2015-11-01
Traditional Nuclear Magnetic Resonance (NMR) assignment procedures for proteins rely on preliminary peak-picking to identify and label NMR signals. However, such an approach has severe limitations when signals are erroneously labeled or completely neglected. The consequences are especially grave for proteins with substantial peak overlap, and mistakes can often thwart entire projects. To overcome these limitations, we previously introduced an assignment technique that bypasses traditional pick peaking altogether. Covariance Sequential Correlation Maps (COSCOMs) transform the indirect connectivity information provided by multiple 3D backbone spectra into direct (H, N) to (H, N) correlations. Here, we present an updated method that utilizes a single four-dimensional spectrum rather than a suite of three-dimensional spectra. We demonstrate the advantages of 4D-COSCOMs relative to their 3D counterparts. We introduce improvements accelerating their calculation. We discuss practical considerations affecting their quality. And finally we showcase their utility in the context of a 52 kDa cyclization domain from a non-ribosomal peptide synthetase. Copyright © 2015 Elsevier Inc. All rights reserved.
Estimation of group means when adjusting for covariates in generalized linear models.
Qu, Yongming; Luo, Junxiang
2015-01-01
Generalized linear models are commonly used to analyze categorical data such as binary, count, and ordinal outcomes. Adjusting for important prognostic factors or baseline covariates in generalized linear models may improve the estimation efficiency. The model-based mean for a treatment group produced by most software packages estimates the response at the mean covariate, not the mean response for this treatment group for the studied population. Although this is not an issue for linear models, the model-based group mean estimates in generalized linear models could be seriously biased for the true group means. We propose a new method to estimate the group mean consistently with the corresponding variance estimation. Simulation showed the proposed method produces an unbiased estimator for the group means and provided the correct coverage probability. The proposed method was applied to analyze hypoglycemia data from clinical trials in diabetes. Copyright © 2014 John Wiley & Sons, Ltd.
International Nuclear Information System (INIS)
Boehmer, Bertram
2000-01-01
Results of estimation of the covariance matrix of the neutron spectrum in the WWER-1000 reactor cavity and pressure vessel positions are presented. Two-dimensional calculations with the discrete ordinates transport code DORT in r-theta and r-z-geometry used to determine the neutron group spectrum covariances including gross-correlations between interesting positions. The new Russian ABBN-93 data set and CONSYST code used to supply all transport calculations with group neutron data. All possible sources of uncertainties namely caused by the neutron gross sections, fission sources, geometrical dimensions and material densities considered, whereas the uncertainty of the calculation method was considered negligible in view of the available precision of Monte Carlo simulation used for more precise evaluation of the neutron fluence. (Authors)
International Nuclear Information System (INIS)
Mannhart, W.
1986-01-01
Based on the responses of 25 different neutron activation detectors, the neutron spectrum of Cf-252 hs been adjusted with least-squares methods. For a fixed input neutron spectrum, the covariance matrix of this spectrum has been systematically varied to investigate the influence of this matrix on the final result. The investigation showed that the adjusted neutron spectrum is rather sensitive to the structure of the covariance matrix for the input spectrum. (author)
Effect of correlation on covariate selection in linear and nonlinear mixed effect models.
Bonate, Peter L
2017-01-01
The effect of correlation among covariates on covariate selection was examined with linear and nonlinear mixed effect models. Demographic covariates were extracted from the National Health and Nutrition Examination Survey III database. Concentration-time profiles were Monte Carlo simulated where only one covariate affected apparent oral clearance (CL/F). A series of univariate covariate population pharmacokinetic models was fit to the data and compared with the reduced model without covariate. The "best" covariate was identified using either the likelihood ratio test statistic or AIC. Weight and body surface area (calculated using Gehan and George equation, 1970) were highly correlated (r = 0.98). Body surface area was often selected as a better covariate than weight, sometimes as high as 1 in 5 times, when weight was the covariate used in the data generating mechanism. In a second simulation, parent drug concentration and three metabolites were simulated from a thorough QT study and used as covariates in a series of univariate linear mixed effects models of ddQTc interval prolongation. The covariate with the largest significant LRT statistic was deemed the "best" predictor. When the metabolite was formation-rate limited and only parent concentrations affected ddQTc intervals the metabolite was chosen as a better predictor as often as 1 in 5 times depending on the slope of the relationship between parent concentrations and ddQTc intervals. A correlated covariate can be chosen as being a better predictor than another covariate in a linear or nonlinear population analysis by sheer correlation These results explain why for the same drug different covariates may be identified in different analyses. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Directory of Open Access Journals (Sweden)
Daniel Bartz
Full Text Available Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.
Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W; Müller, Klaus-Robert; Lemm, Steven
2013-01-01
Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.
Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W.; Müller, Klaus-Robert; Lemm, Steven
2013-01-01
Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016
DEFF Research Database (Denmark)
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...... process can be relaxed and how our method can be applied to non-synchronous observations. We also present an empirical study of how high-frequency correlations, regressions and covariances change through time....
Correlational indicators of psychosocial adjustment among senior ...
African Journals Online (AJOL)
There was a significant joint contribution of the independent variables (sense of coherence, optimism and self-efficacy) to the prediction of psychosocial adjustment. This suggested that the three independent variables combined accounted for 30.4% (Adj.R2= .304) variation in the prediction of psychosocial adjustment.
Utilization of cross-section covariance data in FBR core nuclear design and cross-section adjustment
International Nuclear Information System (INIS)
Ishikawa, Makoto
1994-01-01
In the core design of large fast breeder reactors (FBRs), it is essentially important to improve the prediction accuracy of nuclear characteristics from the viewpoint of both reducing cost and insuring reliability of the plant. The cross-section errors, that is, covariance data are one of the most dominant sources for the prediction uncertainty of the core parameters, therefore, quantitative evaluation of covariance data is indispensable for FBR core design. The first objective of the present paper is to introduce how the cross-section covariance data are utilized in the FBR core nuclear design works. The second is to delineate the cross-section adjustment study and its application to an FBR design, because this improved design method markedly enhances the needs and importance of the cross-section covariance data. (author)
Petscher, Yaacov; Schatschneider, Christopher
2011-01-01
Research by Huck and McLean (1975) demonstrated that the covariance-adjusted score is more powerful than the simple difference score, yet recent reviews indicate researchers are equally likely to use either score type in two-wave randomized experimental designs. A Monte Carlo simulation was conducted to examine the conditions under which the…
International Nuclear Information System (INIS)
Cabellos, Oscar; ); PELLONI, Sandro; Ivanov, Evgeny; Sobes, Vladimir; Fukushima, M.; Yokoyama, Kenji; Palmiotti, Giuseppe; Kodeli, Ivo
2016-12-01
The aim of WPEC subgroup 39 'Methods and approaches to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data files' is to provide criteria and practical approaches to use effectively the results of sensitivity analyses and cross section adjustments for feedback to evaluators and differential measurement experimentalists in order to improve the knowledge of neutron cross sections, uncertainties, and correlations to be used in a wide range of applications. This document is the proceedings of the eighth Subgroup 39 meeting, held at the OECD NEA, Boulogne-Billancourt, France, on 1-2 December 2016. It comprises all the available presentations (slides) given by the participants: A - Presentations: Welcome and actions review (Oscar CABELLOS); B - Methods: - Detailed comparison of Progressive Incremental Adjustment (PIA) sequence results involving adjustments of spectral indices and coolant density effects on the basis of the SG33 benchmark (Sandro PELLONI); - ND assessment alternatives: Validation matrix vs XS adjustment (Evgeny IVANOV); - Implementation of Resonance Parameter Sensitivity Coefficients Calculation in CE TSUNAMI-3D (Vladimir SOBES); C - Experiment analysis, sensitivity calculations and benchmarks: - Benchmark tests of ENDF/B-VIII.0 beta 1 using sodium void reactivity worth of FCA-XXVII-1 assembly (M. FUKUSHIMA, Kenji YOKOYAMA); D - Adjustments: - Cross-section adjustment based on JENDL-4.0 using new experiments on the basis of the SG33 benchmark (Kenji YOKOYAMA); - Comparison of adjustment trends with the Cielo evaluation (Sandro PELLONI); - Expanded adjustment in support of CIELO initiative (Giuseppe PALMIOTTI); - First preliminary results of the adjustment exercise using ASPIS Fe88 and SNEAK-7A/7B k_e_f_f and b_e_f_f benchmarks (Ivo KODELI); E - Future actions, deliverables: - Discussion on future of SG39 and possible new subgroup (Giuseppe PALMIOTTI); - WPEC sub-group proposal: Investigation of Covariance Data in
A joint logistic regression and covariate-adjusted continuous-time Markov chain model.
Rubin, Maria Laura; Chan, Wenyaw; Yamal, Jose-Miguel; Robertson, Claudia Sue
2017-12-10
The use of longitudinal measurements to predict a categorical outcome is an increasingly common goal in research studies. Joint models are commonly used to describe two or more models simultaneously by considering the correlated nature of their outcomes and the random error present in the longitudinal measurements. However, there is limited research on joint models with longitudinal predictors and categorical cross-sectional outcomes. Perhaps the most challenging task is how to model the longitudinal predictor process such that it represents the true biological mechanism that dictates the association with the categorical response. We propose a joint logistic regression and Markov chain model to describe a binary cross-sectional response, where the unobserved transition rates of a two-state continuous-time Markov chain are included as covariates. We use the method of maximum likelihood to estimate the parameters of our model. In a simulation study, coverage probabilities of about 95%, standard deviations close to standard errors, and low biases for the parameter values show that our estimation method is adequate. We apply the proposed joint model to a dataset of patients with traumatic brain injury to describe and predict a 6-month outcome based on physiological data collected post-injury and admission characteristics. Our analysis indicates that the information provided by physiological changes over time may help improve prediction of long-term functional status of these severely ill subjects. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Li, Siying; Koch, Gary G; Preisser, John S; Lam, Diana; Sanchez-Kam, Matilde
2017-01-01
Dichotomous endpoints in clinical trials have only two possible outcomes, either directly or via categorization of an ordinal or continuous observation. It is common to have missing data for one or more visits during a multi-visit study. This paper presents a closed form method for sensitivity analysis of a randomized multi-visit clinical trial that possibly has missing not at random (MNAR) dichotomous data. Counts of missing data are redistributed to the favorable and unfavorable outcomes mathematically to address possibly informative missing data. Adjusted proportion estimates and their closed form covariance matrix estimates are provided. Treatment comparisons over time are addressed with Mantel-Haenszel adjustment for a stratification factor and/or randomization-based adjustment for baseline covariables. The application of such sensitivity analyses is illustrated with an example. An appendix outlines an extension of the methodology to ordinal endpoints.
(13)C-(15)N correlation via unsymmetrical indirect covariance NMR: application to vinblastine.
Martin, Gary E; Hilton, Bruce D; Blinov, Kirill A; Williams, Antony J
2007-12-01
Unsymmetrical indirect covariance processing methods allow the derivation of hyphenated 2D NMR data from the component 2D spectra, potentially circumventing the acquisition of the much lower sensitivity hyphenated 2D NMR experimental data. Calculation of HSQC-COSY and HSQC-NOESY spectra from GHSQC, COSY, and NOESY spectra, respectively, has been reported. The use of unsymmetrical indirect covariance processing has also been applied to the combination of (1)H- (13)C GHSQC and (1)H- (15)N long-range correlation data (GHMBC, IMPEACH, or CIGAR-HMBC). The application of unsymmetrical indirect covariance processing to spectra of vinblastine is now reported, specifically the algorithmic extraction of (13)C- (15)N correlations via the unsymmetrical indirect covariance processing of the combination of (1)H- (13)C GHSQC and long-range (1)H- (15)N GHMBC to produce the equivalent of a (13)C- (15)N HSQC-HMBC correlation spectrum. The elimination of artifact responses with aromatic solvent-induced shifts (ASIS) is shown in addition to a method of forecasting potential artifact responses through the indirect covariance processing of the GHSQC spectrum used in the unsymmetrical indirect covariance processing.
Kistner, Emily O.; Muller, Keith E.
2004-01-01
Intraclass correlation and Cronbach's alpha are widely used to describe reliability of tests and measurements. Even with Gaussian data, exact distributions are known only for compound symmetric covariance (equal variances and equal correlations). Recently, large sample Gaussian approximations were derived for the distribution functions. New exact…
International Nuclear Information System (INIS)
Aliberti, G.; Archier, P.; Dunn, M.; Dupont, E.; Hill, I.; ); Garcia, A.; Hursin, M.; Pelloni, S.; Ivanova, T.; Kodeli, I.; Palmiotti, G.; Salvatores, M.; Touran, N.; Wenming, Wang; Yokoyama, K.
2014-05-01
The aim of WPEC subgroup 39 'Methods and approaches to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data files' is to provide criteria and practical approaches to use effectively the results of sensitivity analyses and cross section adjustments for feedback to evaluators and differential measurement experimentalists in order to improve the knowledge of neutron cross sections, uncertainties, and correlations to be used in a wide range of applications. This document is the proceedings of the second Subgroup meeting, held at the NEA, Issy-les-Moulineaux, France, on 13 May 2014. It comprises a Summary Record of the meeting and all the available presentations (slides) given by the participants: A - Welcome: Review of actions (M. Salvatores); B - Inter-comparison of sensitivity coefficients: 1 - Sensitivity Computation with Monte Carlo Methods (T. Ivanova); 2 - Sensitivity analysis of FLATTOP-Pu (I. Kodeli); 3 - Sensitivity coefficients by means of SERPENT-2 (S. Pelloni); 4 - Demonstration - Database for ICSBEP (DICE) and Database and Analysis Tool for IRPhE (IDAT) (I. Hill); C - Specific new experiments: 1 - PROTEUS FDWR-II (HCLWR) program summary (M. Hursin); 2 - STEK and SEG Experiments, M. Salvatores 3 - Experiments related to "2"3"5U, "2"3"8U, "5"6Fe and "2"3Na, G. Palmiotti); 4 - Validation of Iron Cross Sections against ASPIS Experiments (JEF/DOC-420) (I. Kodeli); 5 - Benchmark analysis of Iron Cross-sections (EFFDOC-1221) (I. Kodeli 6 - Integral Beta-effective Measurements (K. Yokoyama on behalf of M. Ishikawa); D - Adjustment results: 1 - Impacts of Covariance Data and Interpretation of Adjustment Trends of ADJ2010, (K. Yokoyama); 2 - Revised Recommendations from ADJ2010 Adjustment (K. Yokoyama); 3 - Comparisons and Discussions on Adjustment trends from JEFF (CEA) (P. Archier); 4 - Feedback on CIELO Isotopes from ENDF/B-VII.0 Adjustment (G. Palmiotti); 5 - Demonstration - Plot comparisons of participants' results (E
Correlations-Adjusted Export Market Diversification
Jung Joo La
2011-01-01
This paper introduces new export market diversification indices incorporated with correlations of business cycles among export partners to identify the actual effects of export market diversification on export instability. Three existing export market diversification indices reflect the dispersion level in terms of the number of export partners and their export shares, without a clear control for correlations among export earnings from export partners. In addition, they are underestimated or ...
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.
Homonuclear long-range correlation spectra from HMBC experiments by covariance processing.
Schoefberger, Wolfgang; Smrecki, Vilko; Vikić-Topić, Drazen; Müller, Norbert
2007-07-01
We present a new application of covariance nuclear magnetic resonance processing based on 1H--13C-HMBC experiments which provides an effective way for establishing indirect 1H--1H and 13C--13C nuclear spin connectivity at natural isotope abundance. The method, which identifies correlated spin networks in terms of covariance between one-dimensional traces from a single decoupled HMBC experiment, derives 13C--13C as well as 1H--1H spin connectivity maps from the two-dimensional frequency domain heteronuclear long-range correlation data matrix. The potential and limitations of this novel covariance NMR application are demonstrated on two compounds: eugenyl-beta-D-glucopyranoside and an emodin-derivative. Copyright (c) 2007 John Wiley & Sons, Ltd.
Fish mercury levels in lakes - adjusting for Hg and fish-size covariation
International Nuclear Information System (INIS)
Sonesten, Lars
2003-01-01
Fish-size covariation can be circumvented by regression intercepts of Hg vs. fish length as lake-specific Hg levels. - Accurate estimates of lake-specific mercury levels are vital in assessing the environmental impact on the mercury content in fish. The intercepts of lake-specific regressions of Hg concentration in fish vs. fish length provide accurate estimates when there is a prominent Hg and fish-size covariation. Commonly used regression methods, such as analysis of covariance (ANCOVA) and various standardization techniques are less suitable, since they do not completely remove the fish-size covariation when regression slopes are not parallel. Partial least squares (PLS) regression analysis reveals that catchment area and water chemistry have the strongest influence on the Hg level in fish in circumneutral lakes. PLS is a multivariate projection method that allows biased linear regression analysis of multicollinear data. The method is applicable to statistical and visual exploration of large data sets, even if there are more variables than observations. Environmental descriptors have no significant impact on the slopes of linear regressions of the Hg concentration in perch (Perca fluviatilis L.) vs. fish length, suggesting that the slopes mainly reflect ontogenetic dietary shifts during the perch life span
Fouladi, Rachel T.
2000-01-01
Provides an overview of standard and modified normal theory and asymptotically distribution-free covariance and correlation structure analysis techniques and details Monte Carlo simulation results on Type I and Type II error control. Demonstrates through the simulation that robustness and nonrobustness of structure analysis techniques vary as a…
International Nuclear Information System (INIS)
De Saint Jean, C.; Dupont, E.; ); Dyrda, J.; Hursin, M.; Pelloni, S.; Ishikawa, M.; Ivanov, E.; Ivanova, T.; Kim, D.H.; Ee, Y.O.; Kodeli, I.; Leal, L.; Leichtle, D.; Palmiotti, G.; Salvatores, M.; Pronyaev, V.; Simakov, S.; )
2013-11-01
The aim of WPEC subgroup 39 'Methods and approaches to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data files' is to provide criteria and practical approaches to use effectively the results of sensitivity analyses and cross section adjustments for feedback to evaluators and differential measurement experimentalists in order to improve the knowledge of neutron cross sections, uncertainties, and correlations to be used in a wide range of applications. This document is the proceedings of the first formal Subgroup 39 meeting held at the NEA, Issy-les-Moulineaux, France, on 28-29 November 2013. It comprises a Summary Record of the meeting and all the available presentations (slides) given by the participants: A - Recent data adjustments performances and trends: 1 - Recommendations from ADJ2010 adjustment (M. Ishikawa); 2 - Feedback on CIELO isotopes from ENDF/B-VII.0 adjustment (G. Palmiotti); 3 - Sensitivity and uncertainty results on FLATTOP-Pu (I. Kodeli); 4 - SG33 benchmark: Comparative adjustment results (S. Pelloni) 5 - Integral benchmarks for data assimilation: selection of a consistent set and establishment of integral correlations (E. Ivanov); 6 - PROTEUS experimental data (M. Hursin); 7 - Additional information on High Conversion Light Water Reactor (HCLWR aka FDWR-II) experiments (14 January 2014); 8 - Data assimilation of benchmark experiments for homogenous thermal/epithermal uranium systems (J. Dyrda); B - Methodology issues: 1 - Adjustment methodology issues (G. Palmiotti); 2 - Marginalisation, methodology issues and nuclear data parameter adjustment (C. De Saint Jean); 3 - Nuclear data parameter adjustment (G. Palmiotti). A list of issues and actions conclude the document
Schur Complement Inequalities for Covariance Matrices and Monogamy of Quantum Correlations.
Lami, Ludovico; Hirche, Christoph; Adesso, Gerardo; Winter, Andreas
2016-11-25
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.
Madrigal, Pedro
2017-03-01
Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomic science, as it allows both to evaluate reproducibility of biological or technical replicates, and to compare different datasets to identify their potential correlations. Here we present fCCAC, an application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). We show how this method differs from other measures of correlation, and exemplify how it can reveal shared covariance between histone modifications and DNA binding proteins, such as the relationship between the H3K4me3 chromatin mark and its epigenetic writers and readers. An R/Bioconductor package is available at http://bioconductor.org/packages/fCCAC/ . pmb59@cam.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
International Nuclear Information System (INIS)
Sato, Masanori; Matsubara, Takahiko; Takada, Masahiro; Hamana, Takashi
2011-01-01
Using 1000 ray-tracing simulations for a Λ-dominated cold dark model in Sato et al., we study the covariance matrix of cosmic shear correlation functions, which is the standard statistics used in previous measurements. The shear correlation function of a particular separation angle is affected by Fourier modes over a wide range of multipoles, even beyond a survey area, which complicates the analysis of the covariance matrix. To overcome such obstacles we first construct Gaussian shear simulations from the 1000 realizations and then use the Gaussian simulations to disentangle the Gaussian covariance contribution to the covariance matrix we measured from the original simulations. We found that an analytical formula of Gaussian covariance overestimates the covariance amplitudes due to an effect of the finite survey area. Furthermore, the clean separation of the Gaussian covariance allows us to examine the non-Gaussian covariance contributions as a function of separation angles and source redshifts. For upcoming surveys with typical source redshifts of z s = 0.6 and 1.0, the non-Gaussian contribution to the diagonal covariance components at 1 arcmin scales is greater than the Gaussian contribution by a factor of 20 and 10, respectively. Predictions based on the halo model qualitatively well reproduce the simulation results, however show a sizable disagreement in the covariance amplitudes. By combining these simulation results we develop a fitting formula to the covariance matrix for a survey with arbitrary area coverage, taking into account effects of the finiteness of survey area on the Gaussian covariance.
International Nuclear Information System (INIS)
Weisbin, C.R.; Marable, J.H.; Collins, P.J.; Cowan, C.L.; Peelle, R.W.; Salvatores, M.
1979-06-01
The present work proposes a specific plan of cross section library adjustment for fast reactor core physics analysis using information from fast reactor and dosimetry integral experiments and from differential data evaluations. This detailed exposition of the proposed approach is intended mainly to elicit review and criticism from scientists and engineers in the research, development, and design fields. This major attempt to develop useful adjusted libraries is based on the established benchmark integral data, accurate and well documented analysis techniques, sensitivities, and quantified uncertainties for nuclear data, integral experiment measurements, and calculational methodology. The adjustments to be obtained using these specifications are intended to produce an overall improvement in the least-squares sense in the quality of the data libraries, so that calculations of other similar systems using the adjusted data base with any credible method will produce results without much data-related bias. The adjustments obtained should provide specific recommendations to the data evaluation program to be weighed in the light of newer measurements, and also a vehicle for observing how the evaluation process is converging. This report specifies the calculational methodology to be used, the integral experiments to be employed initially, and the methods and integral experiment biases and uncertainties to be used. The sources of sensitivity coefficients, as well as the cross sections to be adjusted, are detailed. The formulae for sensitivity coefficients for fission spectral parameters are developed. A mathematical formulation of the least-square adjustment problem is given including biases and uncertainties in methods
Gaussian covariance graph models accounting for correlated marker effects in genome-wide prediction.
Martínez, C A; Khare, K; Rahman, S; Elzo, M A
2017-10-01
Several statistical models used in genome-wide prediction assume uncorrelated marker allele substitution effects, but it is known that these effects may be correlated. In statistics, graphical models have been identified as a useful tool for covariance estimation in high-dimensional problems and it is an area that has recently experienced a great expansion. In Gaussian covariance graph models (GCovGM), the joint distribution of a set of random variables is assumed to be Gaussian and the pattern of zeros of the covariance matrix is encoded in terms of an undirected graph G. In this study, methods adapting the theory of GCovGM to genome-wide prediction were developed (Bayes GCov, Bayes GCov-KR and Bayes GCov-H). In simulated data sets, improvements in correlation between phenotypes and predicted breeding values and accuracies of predicted breeding values were found. Our models account for correlation of marker effects and permit to accommodate general structures as opposed to models proposed in previous studies, which consider spatial correlation only. In addition, they allow incorporation of biological information in the prediction process through its use when constructing graph G, and their extension to the multi-allelic loci case is straightforward. © 2017 Blackwell Verlag GmbH.
Uncertainty estimation of core safety parameters using cross-correlations of covariance matrix
International Nuclear Information System (INIS)
Yamamoto, A.; Yasue, Y.; Endo, T.; Kodama, Y.; Ohoka, Y.; Tatsumi, M.
2012-01-01
An uncertainty estimation method for core safety parameters, for which measurement values are not obtained, is proposed. We empirically recognize the correlations among the prediction errors among core safety parameters, e.g., a correlation between the control rod worth and assembly relative power of corresponding position. Correlations of uncertainties among core safety parameters are theoretically estimated using the covariance of cross sections and sensitivity coefficients for core parameters. The estimated correlations among core safety parameters are verified through the direct Monte-Carlo sampling method. Once the correlation of uncertainties among core safety parameters is known, we can estimate the uncertainty of a safety parameter for which measurement value is not obtained. Furthermore, the correlations can be also used for the reduction of uncertainties of core safety parameters. (authors)
International Nuclear Information System (INIS)
Wang, Wenming; Yokoyama, Kenji; Kim, Do Heon; Kodeli, Ivan-Alexander; Hursin, Mathieu; Pelloni, Sandro; Palmiotti, Giuseppe; Salvatores, Massimo; Touran, Nicholas; Cabellos De Francisco, Oscar; )
2015-05-01
The aim of WPEC subgroup 39 'Methods and approaches to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data files' is to provide criteria and practical approaches to use effectively the results of sensitivity analyses and cross section adjustments for feedback to evaluators and differential measurement experimentalists in order to improve the knowledge of neutron cross sections, uncertainties, and correlations to be used in a wide range of applications. This document is the proceedings of the fourth Subgroup meeting, held at the NEA, Issy-les-Moulineaux, France, on 19-20 May 2015. It comprises a Summary Record of the meeting, two papers on deliverables and all the available presentations (slides) given by the participants: 1 - Status of Deliverables: '1. Methodology' (K. Yokoyama); 2 - Status of Deliverables: '2. Comments on covariance data' (K. Yokoyama); 3 - PROTEUS HCLWR Experiments (M. Hursin); 4 - Preliminary UQ Efforts for TWR Design (N. Touran); 5 - Potential use of beta-eff and other benchmark for adjustment (I. Kodeli); 6 - k_e_f_f uncertainties for a simple case of Am"2"4"1 using different codes and evaluated files (I. Kodeli); 7 - k_e_f_f uncertainties for a simple case of Am"2"4"1 using TSUNAMI (O. Cabellos); 8 - REWIND: Ranking Experiments by Weighting to Improve Nuclear Data (G. Palmiotti); 9 - Recent analysis on NUDUNA/MOCABA applications to reactor physics parameters (E. Castro); 10 - INL exploratory study for SEG (A. Hummel); 11 - The Development of Nuclear Data Adjustment Code at CNDC (H. Wu); 12 - SG39 Perspectives (M. Salvatores). A list of issues and actions conclude the document
Uncertainty estimation of core safety parameters using cross-correlations of covariance matrix
International Nuclear Information System (INIS)
Yamamoto, Akio; Yasue, Yoshihiro; Endo, Tomohiro; Kodama, Yasuhiro; Ohoka, Yasunori; Tatsumi, Masahiro
2013-01-01
An uncertainty reduction method for core safety parameters, for which measurement values are not obtained, is proposed. We empirically recognize that there exist some correlations among the prediction errors of core safety parameters, e.g., a correlation between the control rod worth and the assembly relative power at corresponding position. Correlations of errors among core safety parameters are theoretically estimated using the covariance of cross sections and sensitivity coefficients of core parameters. The estimated correlations of errors among core safety parameters are verified through the direct Monte Carlo sampling method. Once the correlation of errors among core safety parameters is known, we can estimate the uncertainty of a safety parameter for which measurement value is not obtained. (author)
International Nuclear Information System (INIS)
Aufiero, Manuele; Ivanov, Evgeny; Hoefer, Axel; Yokoyama, Kenji; Da Cruz, Dirceu Ferreira; KODELI, Ivan-Alexander; Hursin, Mathieu; Pelloni, Sandro; Palmiotti, Giuseppe; Salvatores, Massimo; Barnes, Andrew; Cabellos De Francisco, Oscar; ); Ivanova, Tatiana; )
2014-11-01
The aim of WPEC subgroup 39 'Methods and approaches to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data files' is to provide criteria and practical approaches to use effectively the results of sensitivity analyses and cross section adjustments for feedback to evaluators and differential measurement experimentalists in order to improve the knowledge of neutron cross sections, uncertainties, and correlations to be used in a wide range of applications. This document is the proceedings of the third formal Subgroup meeting held at the NEA, Issy-les-Moulineaux, France, on 27-28 November 2014. It comprises a Summary Record of the meeting and all the available presentations (slides) given by the participants: A - Sensitivity methods: 1 - Perturbation/sensitivity calculations with Serpent (M. Aufiero); 2 - Comparison of deterministic and Monte Carlo sensitivity analysis of SNEAK-7A and FLATTOP-Pu Benchmarks (I. Kodeli); B - Integral experiments: 1 - PROTEUS experiments: selected experiments sensitivity profiles and availability, (M. Hursin, M. Salvatores - PROTEUS Experiments, HCLWR configurations); 2 - SINBAD Benchmark Database and FNS/JAEA Liquid Oxygen TOF Experiment Analysis (I. Kodeli); 3 - STEK experiment Opportunity for Validation of Fission Products Nuclear Data (D. Da Cruz); 4 - SEG (tailored adjoint flux shapes) (M. Savatores - comments) 5 - IPPE transmission experiments (Fe, 238 U) (T. Ivanova); 6 - RPI semi-integral (Fe, 238 U) (G. Palmiotti - comments); 7 - New experiments, e.g. in connection with the new NSC Expert Group on 'Improvement of Integral Experiments Data for Minor Actinide Management' (G. Palmiotti - Some comments from the Expert Group) 8 - Additional PSI adjustment studies accounting for nonlinearity (S. Pelloni); 9 - Adjustment methodology issues (G. Palmiotti); C - Am-241 and fission product issues: 1 - Am-241 validation for criticality-safety calculations (A. Barnes - Visio
Yang, Yang; DeGruttola, Victor
2012-06-22
Traditional resampling-based tests for homogeneity in covariance matrices across multiple groups resample residuals, that is, data centered by group means. These residuals do not share the same second moments when the null hypothesis is false, which makes them difficult to use in the setting of multiple testing. An alternative approach is to resample standardized residuals, data centered by group sample means and standardized by group sample covariance matrices. This approach, however, has been observed to inflate type I error when sample size is small or data are generated from heavy-tailed distributions. We propose to improve this approach by using robust estimation for the first and second moments. We discuss two statistics: the Bartlett statistic and a statistic based on eigen-decomposition of sample covariance matrices. Both statistics can be expressed in terms of standardized errors under the null hypothesis. These methods are extended to test homogeneity in correlation matrices. Using simulation studies, we demonstrate that the robust resampling approach provides comparable or superior performance, relative to traditional approaches, for single testing and reasonable performance for multiple testing. The proposed methods are applied to data collected in an HIV vaccine trial to investigate possible determinants, including vaccine status, vaccine-induced immune response level and viral genotype, of unusual correlation pattern between HIV viral load and CD4 count in newly infected patients.
Directory of Open Access Journals (Sweden)
R. Caballero-Águila
2014-01-01
Full Text Available The optimal least-squares linear estimation problem is addressed for a class of discrete-time multisensor linear stochastic systems subject to randomly delayed measurements with different delay rates. For each sensor, a different binary sequence is used to model the delay process. The measured outputs are perturbed by both random parameter matrices and one-step autocorrelated and cross correlated noises. Using an innovation approach, computationally simple recursive algorithms are obtained for the prediction, filtering, and smoothing problems, without requiring full knowledge of the state-space model generating the signal process, but only the information provided by the delay probabilities and the mean and covariance functions of the processes (signal, random parameter matrices, and noises involved in the observation model. The accuracy of the estimators is measured by their error covariance matrices, which allow us to analyze the estimator performance in a numerical simulation example that illustrates the feasibility of the proposed algorithms.
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.
Automated vessel segmentation using cross-correlation and pooled covariance matrix analysis.
Du, Jiang; Karimi, Afshin; Wu, Yijing; Korosec, Frank R; Grist, Thomas M; Mistretta, Charles A
2011-04-01
Time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA) provides contrast dynamics in the vasculature and allows vessel segmentation based on temporal correlation analysis. Here we present an automated vessel segmentation algorithm including automated generation of regions of interest (ROIs), cross-correlation and pooled sample covariance matrix analysis. The dynamic images are divided into multiple equal-sized regions. In each region, ROIs for artery, vein and background are generated using an iterative thresholding algorithm based on the contrast arrival time map and contrast enhancement map. Region-specific multi-feature cross-correlation analysis and pooled covariance matrix analysis are performed to calculate the Mahalanobis distances (MDs), which are used to automatically separate arteries from veins. This segmentation algorithm is applied to a dual-phase dynamic imaging acquisition scheme where low-resolution time-resolved images are acquired during the dynamic phase followed by high-frequency data acquisition at the steady-state phase. The segmented low-resolution arterial and venous images are then combined with the high-frequency data in k-space and inverse Fourier transformed to form the final segmented arterial and venous images. Results from volunteer and patient studies demonstrate the advantages of this automated vessel segmentation and dual phase data acquisition technique. Copyright © 2011 Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Akemann, Gernot; Checinski, Tomasz; Kieburg, Mario
2016-01-01
We compute the spectral statistics of the sum H of two independent complex Wishart matrices, each of which is correlated with a different covariance matrix. Random matrix theory enjoys many applications including sums and products of random matrices. Typically ensembles with correlations among the matrix elements are much more difficult to solve. Using a combination of supersymmetry, superbosonisation and bi-orthogonal functions we are able to determine all spectral k -point density correlation functions of H for arbitrary matrix size N . In the half-degenerate case, when one of the covariance matrices is proportional to the identity, the recent results by Kumar for the joint eigenvalue distribution of H serve as our starting point. In this case the ensemble has a bi-orthogonal structure and we explicitly determine its kernel, providing its exact solution for finite N . The kernel follows from computing the expectation value of a single characteristic polynomial. In the general non-degenerate case the generating function for the k -point resolvent is determined from a supersymmetric evaluation of the expectation value of k ratios of characteristic polynomials. Numerical simulations illustrate our findings for the spectral density at finite N and we also give indications how to do the asymptotic large- N analysis. (paper)
International Nuclear Information System (INIS)
Herman, Michal Wladyslaw; Cabellos De Francisco, Oscar; Beck, Bret; Ignatyuk, Anatoly V.; Palmiotti, Giuseppe; Grudzevich, Oleg T.; Salvatores, Massimo; Chadwick, Mark; Pelloni, Sandro; Diez De La Obra, Carlos Javier; Wu, Haicheng; Sobes, Vladimir; Rearden, Bradley T.; Yokoyama, Kenji; Hursin, Mathieu; Penttila, Heikki; Kodeli, Ivan-Alexander; Plevnik, Lucijan; Plompen, Arjan; Gabrielli, Fabrizio; Leal, Luiz Carlos; Aufiero, Manuele; Fiorito, Luca; Hummel, Andrew; Siefman, Daniel; Leconte, Pierre
2016-05-01
The aim of WPEC subgroup 39 'Methods and approaches to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data files' is to provide criteria and practical approaches to use effectively the results of sensitivity analyses and cross section adjustments for feedback to evaluators and differential measurement experimentalists in order to improve the knowledge of neutron cross sections, uncertainties, and correlations to be used in a wide range of applications. WPEC subgroup 40-CIELO (Collaborative International Evaluated Library Organization) provides a new working paradigm to facilitate evaluated nuclear reaction data advances. It brings together experts from across the international nuclear reaction data community to identify and document discrepancies among existing evaluated data libraries, measured data, and model calculation interpretations, and aims to make progress in reconciling these discrepancies to create more accurate ENDF-formatted files. SG40-CIELO focusses on 6 important isotopes: "1H, "1"6O, "5"6Fe, "2"3"5","2"3"8U, "2"3"9Pu. This document is the proceedings of the seventh formal Subgroup 39 meeting and of the Joint SG39+SG40 Session held at the NEA, OECD Conference Center, Paris, France on 10-11 May 2016. It comprises a Summary Record of the meeting, and all the available presentations (slides) given by the participants: A - Welcome and actions review (Oscar CABELLOS); B - Methods: - XGPT: uncertainty propagation and data assimilation from continuous energy covariance matrix and resonance parameters covariances (Manuele AUFIERO); - Optimal experiment utilization (REWINDing PIA), (G. Palmiotti); C - Experiment analysis, sensitivity calculations and benchmarks: - Tripoli-4 analysis of SEG experiments (Andrew HUMMEL); - Tripoli-4 analysis of BERENICE experiments (P. DUFAY, Cyrille DE SAINT JEAN); - Preparation of sensitivities of k-eff, beta-eff and shielding benchmarks for adjustment exercise (Ivo KODELI); - SA and
Directory of Open Access Journals (Sweden)
Zhang S
2014-07-01
Full Text Available Shiyuan Zhang,1 James Paul,2 Manyat Nantha-Aree,2 Norman Buckley,2 Uswa Shahzad,2 Ji Cheng,2 Justin DeBeer,5 Mitchell Winemaker,5 David Wismer,5 Dinshaw Punthakee,5 Victoria Avram,5 Lehana Thabane1–41Department of Clinical Epidemiology and Biostatistics, 2Department of Anesthesia, McMaster University, Hamilton, ON, Canada; 3Biostatistics Unit/Centre for Evaluation of Medicines, St Joseph's Healthcare - Hamilton, Hamilton, ON, Canada; 4Population Health Research Institute, Hamilton Health Science/McMaster University, 5Department of Surgery, Division of Orthopaedics, McMaster University, Hamilton, ON, CanadaBackground: Although seemingly straightforward, the statistical comparison of a continuous variable in a randomized controlled trial that has both a pre- and posttreatment score presents an interesting challenge for trialists. We present here empirical application of four statistical methods (posttreatment scores with analysis of variance, analysis of covariance, change in scores, and percent change in scores, using data from a randomized controlled trial of postoperative pain in patients following total joint arthroplasty (the Morphine COnsumption in Joint Replacement Patients, With and Without GaBapentin Treatment, a RandomIzed ControlLEd Study [MOBILE] trials.Methods: Analysis of covariance (ANCOVA was used to adjust for baseline measures and to provide an unbiased estimate of the mean group difference of the 1-year postoperative knee flexion scores in knee arthroplasty patients. Robustness tests were done by comparing ANCOVA with three comparative methods: the posttreatment scores, change in scores, and percentage change from baseline.Results: All four methods showed similar direction of effect; however, ANCOVA (-3.9; 95% confidence interval [CI]: -9.5, 1.6; P=0.15 and the posttreatment score (-4.3; 95% CI: -9.8, 1.2; P=0.12 method provided the highest precision of estimate compared with the change score (-3.0; 95% CI: -9.9, 3.8; P=0
Akdenur, B; Okkesum, S; Kara, S; Günes, S
2009-11-01
In this study, electromyography signals sampled from children undergoing orthodontic treatment were used to estimate the effect of an orthodontic trainer on the anterior temporal muscle. A novel data normalization method, called the correlation- and covariance-supported normalization method (CCSNM), based on correlation and covariance between features in a data set, is proposed to provide predictive guidance to the orthodontic technique. The method was tested in two stages: first, data normalization using the CCSNM; second, prediction of normalized values of anterior temporal muscles using an artificial neural network (ANN) with a Levenberg-Marquardt learning algorithm. The data set consists of electromyography signals from right anterior temporal muscles, recorded from 20 children aged 8-13 years with class II malocclusion. The signals were recorded at the start and end of a 6-month treatment. In order to train and test the ANN, two-fold cross-validation was used. The CCSNM was compared with four normalization methods: minimum-maximum normalization, z score, decimal scaling, and line base normalization. In order to demonstrate the performance of the proposed method, prevalent performance-measuring methods, and the mean square error and mean absolute error as mathematical methods, the statistical relation factor R2 and the average deviation have been examined. The results show that the CCSNM was the best normalization method among other normalization methods for estimating the effect of the trainer.
Phase-Covariant Cloning and EPR Correlations in Entangled Macroscopic Quantum Systems
de Martini, Francesco; Sciarrino, Fabio
2007-03-01
Theoretical and experimental results on the Quantum Injected Optical Parametric Amplification (QI-OPA) of optical qubits in the high gain regime are reported. The large size of the gain parameter in the collinear configuration, g = 4.5, allows the generation of EPR nonlocally correlated bunches containing about 4000 photons. The entanglement of the related Schroedinger Cat-State (SCS) is demonstrated as well as the establishment of Phase-Covariant quantum cloning. The cloning ``fidelity'' has been found to match the theoretical results. According to the original 1935 definition of the SCS, the overall apparatus establishes for the first time the nonlocal correlations between a microcopic spin (qubit) and a high J angular momentum i.e. a mesoscopic multiparticle system close to the classical limit. The results of the first experimental realization of the Herbert proposal for superluminal communication via nonlocality will be presented.
Separation of Correlated Astrophysical Sources Using Multiple-Lag Data Covariance Matrices
Directory of Open Access Journals (Sweden)
Baccigalupi C
2005-01-01
Full Text Available This paper proposes a new strategy to separate astrophysical sources that are mutually correlated. This strategy is based on second-order statistics and exploits prior information about the possible structure of the mixing matrix. Unlike ICA blind separation approaches, where the sources are assumed mutually independent and no prior knowledge is assumed about the mixing matrix, our strategy allows the independence assumption to be relaxed and performs the separation of even significantly correlated sources. Besides the mixing matrix, our strategy is also capable to evaluate the source covariance functions at several lags. Moreover, once the mixing parameters have been identified, a simple deconvolution can be used to estimate the probability density functions of the source processes. To benchmark our algorithm, we used a database that simulates the one expected from the instruments that will operate onboard ESA's Planck Surveyor Satellite to measure the CMB anisotropies all over the celestial sphere.
Directory of Open Access Journals (Sweden)
Meyer Karin
2001-11-01
Full Text Available Abstract A random regression model for the analysis of "repeated" records in animal breeding is described which combines a random regression approach for additive genetic and other random effects with the assumption of a parametric correlation structure for within animal covariances. Both stationary and non-stationary correlation models involving a small number of parameters are considered. Heterogeneity in within animal variances is modelled through polynomial variance functions. Estimation of parameters describing the dispersion structure of such model by restricted maximum likelihood via an "average information" algorithm is outlined. An application to mature weight records of beef cow is given, and results are contrasted to those from analyses fitting sets of random regression coefficients for permanent environmental effects.
HSQC-1,n-ADEQUATE: a new approach to long-range 13C-13C correlation by covariance processing.
Martin, Gary E; Hilton, Bruce D; Willcott, M Robert; Blinov, Kirill A
2011-10-01
Long-range, two-dimensional heteronuclear shift correlation NMR methods play a pivotal role in the assembly of novel molecular structures. The well-established GHMBC method is a high-sensitivity mainstay technique, affording connectivity information via (n)J(CH) coupling pathways. Unfortunately, there is no simple way of determining the value of n and hence no way of differentiating two-bond from three- and occasionally four-bond correlations. Three-bond correlations, however, generally predominate. Recent work has shown that the unsymmetrical indirect covariance or generalized indirect covariance processing of multiplicity edited GHSQC and 1,1-ADEQUATE spectra provides high-sensitivity access to a (13)C-(13) C connectivity map in the form of an HSQC-1,1-ADEQUATE spectrum. Covariance processing of these data allows the 1,1-ADEQUATE connectivity information to be exploited with the inherent sensitivity of the GHSQC spectrum rather than the intrinsically lower sensitivity of the 1,1-ADEQUATE spectrum itself. Data acquisition times and/or sample size can be substantially reduced when covariance processing is to be employed. In an extension of that work, 1,n-ADEQUATE spectra can likewise be subjected to covariance processing to afford high-sensitivity access to the equivalent of (4)J(CH) GHMBC connectivity information. The method is illustrated using strychnine as a model compound. Copyright © 2011 John Wiley & Sons, Ltd.
Geerligs, Linda; Cam-Can; Henson, Richard N
2016-07-15
Studies of brain-wide functional connectivity or structural covariance typically use measures like the Pearson correlation coefficient, applied to data that have been averaged across voxels within regions of interest (ROIs). However, averaging across voxels may result in biased connectivity estimates when there is inhomogeneity within those ROIs, e.g., sub-regions that exhibit different patterns of functional connectivity or structural covariance. Here, we propose a new measure based on "distance correlation"; a test of multivariate dependence of high dimensional vectors, which allows for both linear and non-linear dependencies. We used simulations to show how distance correlation out-performs Pearson correlation in the face of inhomogeneous ROIs. To evaluate this new measure on real data, we use resting-state fMRI scans and T1 structural scans from 2 sessions on each of 214 participants from the Cambridge Centre for Ageing & Neuroscience (Cam-CAN) project. Pearson correlation and distance correlation showed similar average connectivity patterns, for both functional connectivity and structural covariance. Nevertheless, distance correlation was shown to be 1) more reliable across sessions, 2) more similar across participants, and 3) more robust to different sets of ROIs. Moreover, we found that the similarity between functional connectivity and structural covariance estimates was higher for distance correlation compared to Pearson correlation. We also explored the relative effects of different preprocessing options and motion artefacts on functional connectivity. Because distance correlation is easy to implement and fast to compute, it is a promising alternative to Pearson correlations for investigating ROI-based brain-wide connectivity patterns, for functional as well as structural data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Eisuke Chikayama
2016-10-01
Full Text Available Foods from agriculture and fishery products are processed using various technologies. Molecular mixture analysis during food processing has the potential to help us understand the molecular mechanisms involved, thus enabling better cooking of the analyzed foods. To date, there has been no web-based tool focusing on accumulating Nuclear Magnetic Resonance (NMR spectra from various types of food processing. Therefore, we have developed a novel web-based tool, FoodPro, that includes a food NMR spectrum database and computes covariance and correlation spectra to tasting and hardness. As a result, FoodPro has accumulated 236 aqueous (extracted in D2O and 131 hydrophobic (extracted in CDCl3 experimental bench-top 60-MHz NMR spectra, 1753 tastings scored by volunteers, and 139 hardness measurements recorded by a penetrometer, all placed into a core database. The database content was roughly classified into fish and vegetable groups from the viewpoint of different spectrum patterns. FoodPro can query a user food NMR spectrum, search similar NMR spectra with a specified similarity threshold, and then compute estimated tasting and hardness, covariance, and correlation spectra to tasting and hardness. Querying fish spectra exemplified specific covariance spectra to tasting and hardness, giving positive covariance for tasting at 1.31 ppm for lactate and 3.47 ppm for glucose and a positive covariance for hardness at 3.26 ppm for trimethylamine N-oxide.
Chikayama, Eisuke; Yamashina, Ryo; Komatsu, Keiko; Tsuboi, Yuuri; Sakata, Kenji; Kikuchi, Jun; Sekiyama, Yasuyo
2016-10-19
Foods from agriculture and fishery products are processed using various technologies. Molecular mixture analysis during food processing has the potential to help us understand the molecular mechanisms involved, thus enabling better cooking of the analyzed foods. To date, there has been no web-based tool focusing on accumulating Nuclear Magnetic Resonance (NMR) spectra from various types of food processing. Therefore, we have developed a novel web-based tool, FoodPro, that includes a food NMR spectrum database and computes covariance and correlation spectra to tasting and hardness. As a result, FoodPro has accumulated 236 aqueous (extracted in D₂O) and 131 hydrophobic (extracted in CDCl₃) experimental bench-top 60-MHz NMR spectra, 1753 tastings scored by volunteers, and 139 hardness measurements recorded by a penetrometer, all placed into a core database. The database content was roughly classified into fish and vegetable groups from the viewpoint of different spectrum patterns. FoodPro can query a user food NMR spectrum, search similar NMR spectra with a specified similarity threshold, and then compute estimated tasting and hardness, covariance, and correlation spectra to tasting and hardness. Querying fish spectra exemplified specific covariance spectra to tasting and hardness, giving positive covariance for tasting at 1.31 ppm for lactate and 3.47 ppm for glucose and a positive covariance for hardness at 3.26 ppm for trimethylamine N -oxide.
International Nuclear Information System (INIS)
Cabellos, Oscar; De Saint Jean, Cyrille; Hursin, Mathieu; Pelloni, Sandro; Ivanov, Evgeny; Kodeli, Ivan; Leconte, Pierre; Palmiotti, Giuseppe; Salvatores, Massimo; Sobes, Vladimir; Yokoyama, Kenji
2015-12-01
The aim of WPEC subgroup 39 'Methods and approaches to provide feedback from nuclear and covariance data adjustment for improvement of nuclear data files' is to provide criteria and practical approaches to use effectively the results of sensitivity analyses and cross section adjustments for feedback to evaluators and differential measurement experimentalists in order to improve the knowledge of neutron cross sections, uncertainties, and correlations to be used in a wide range of applications. This document is the proceedings of the fifth formal Subgroup 39 meeting held at the Institute Curie, Paris, France, on 4 December 2015. It comprises a Summary Record of the meeting, and all the available presentations (slides) given by the participants: A - Sensitivity methods: - 1: Short update on deliverables (K. Yokoyama); - 2: Does one shot Bayesian is equivalent to successive update? Bayesian inference: some matrix linear algebra (C. De Saint Jean); - 3: Progress in Methodology (G. Palmiotti); - SG39-3: Use of PIA approach. Possible application to neutron propagation experiments (S. Pelloni); - 4: Update on sensitivity coefficient methods (E. Ivanov); - 5: Stress test for U-235 fission (H. Wu); - 6: Methods and approaches development at ORNL for providing feedback from integral benchmark experiments for improvement of nuclear data files (V. Sobes); B - Integral experiments: - 7a: Update on SEG analysis (G. Palmiotti); - 7b:Status of MANTRA (G. Palmiotti); - 7c: Possible new experiments at NRAD (G. Palmiotti); - 8: B-eff experiments (I. Kodeli); - 9: On going CEA activities related to dedicated integral experiments for nuclear date validation in the Fast energy range (P. Leconte); - 10: PROTEUS Experiments: an update (M. Hursin); - 11: Short updates on neutron propagation experiments, STEK, CIELO status (O. Cabellos)
Westgate, Philip M
2016-01-01
When generalized estimating equations (GEE) incorporate an unstructured working correlation matrix, the variances of regression parameter estimates can inflate due to the estimation of the correlation parameters. In previous work, an approximation for this inflation that results in a corrected version of the sandwich formula for the covariance matrix of regression parameter estimates was derived. Use of this correction for correlation structure selection also reduces the over-selection of the unstructured working correlation matrix. In this manuscript, we conduct a simulation study to demonstrate that an increase in variances of regression parameter estimates can occur when GEE incorporates structured working correlation matrices as well. Correspondingly, we show the ability of the corrected version of the sandwich formula to improve the validity of inference and correlation structure selection. We also study the relative influences of two popular corrections to a different source of bias in the empirical sandwich covariance estimator.
International Nuclear Information System (INIS)
Pelloni, Sandro
2014-01-01
Highlights: • Our data adjustment is based on a Generalized Linear Least-Squares approach. • The computed sensitivity coefficients are converged within an iterative procedure. • The corresponding multistep adjustment thus accounts for non-linearity. • It provides a more accurate simulation of fast-spectrum experiments. - Abstract: The data assimilation benchmark launched by the “Subgroup 33” on “Methods and issues for the combined use of integral experiments and covariance data” of the Working Party on Evaluation Cooperation (WPEC) of the OECD Nuclear Energy Agency Nuclear Science Committee is recalculated by means of a multistep adjustment procedure using the deterministic code system ERANOS in conjunction with a dedicated Generalized Linear Least-Squares approach based on the Bayesian parameter estimation method. Nuclear data in terms of multi-group cross-sections as well as their variances and covariances, are adjusted for 11 nuclides, namely 10 B, 16 O, 23 Na, 56 Fe, 52 Cr, 58 Ni, 235 U, 238 U, 239 Pu, 240 Pu and 241 Pu and 6 nuclear reactions which are elastic and inelastic scattering, lumped (n,2n) and (n,3n), capture, fission and ν ¯ . The adjustment is carried out by making use of experimental data for 19 integral parameters obtained in 7 different fast spectrum systems. In the determination of a posteriori values for these integral parameters including effective multiplication factors, spectral indices and void effects, along with their nuclear data uncertainty, the required adjusted data for these nuclides and reactions are generated in conjunction with pre-computed sensitivity coefficients of the analytical integral parameters to the nuclear data to adjust. The suggested multistep scheme aims at accounting for non-linear effects. Correspondingly, the sensitivity coefficients are recalculated within an iterative procedure on the basis of the a posteriori analytical values and adjusted cross-sections. The adjustment is thus repeated
On the use of the covariance matrix to fit correlated data
D'Agostini, G.
1994-07-01
Best fits to data which are affected by systematic uncertainties on the normalization factor have the tendency to produce curves lower than expected if the covariance matrix of the data points is used in the definition of the χ2. This paper shows that the effect is a direct consequence of the hypothesis used to estimate the empirical covariance matrix, namely the linearization on which the usual error propagation relies. The bias can become unacceptable if the normalization error is large, or a large number of data points are fitted.
Anderson, Ray; Skaggs, Todd; Alfieri, Joseph; Kustas, William; Wang, Dong; Ayars, James
2016-04-01
Partitioned land surfaces fluxes (e.g. evaporation, transpiration, photosynthesis, and ecosystem respiration) are needed as input, calibration, and validation data for numerous hydrological and land surface models. However, one of the most commonly used techniques for measuring land surface fluxes, Eddy Covariance (EC), can directly measure net, combined water and carbon fluxes (evapotranspiration and net ecosystem exchange/productivity). Analysis of the correlation structure of high frequency EC time series (hereafter flux partitioning or FP) has been proposed to directly partition net EC fluxes into their constituent components using leaf-level water use efficiency (WUE) data to separate stomatal and non-stomatal transport processes. FP has significant logistical and spatial representativeness advantages over other partitioning approaches (e.g. isotopic fluxes, sap flow, microlysimeters), but the performance of the FP algorithm is reliant on the accuracy of the intercellular CO2 (ci) concentration used to parameterize WUE for each flux averaging interval. In this study, we tested several parameterizations for ci as a function of atmospheric CO2 (ca), including (1) a constant ci/ca ratio for C3 and C4 photosynthetic pathway plants, (2) species-specific ci/ca-Vapor Pressure Deficit (VPD) relationships (quadratic and linear), and (3) generalized C3 and C4 photosynthetic pathway ci/ca-VPD relationships. We tested these ci parameterizations at three agricultural EC towers from 2011-present in C4 and C3 crops (sugarcane - Saccharum officinarum L. and peach - Prunus persica), and validated again sap-flow sensors installed at the peach site. The peach results show that the species-specific parameterizations driven FP algorithm came to convergence significantly more frequently (~20% more frequently) than the constant ci/ca ratio or generic C3-VPD relationship. The FP algorithm parameterizations with a generic VPD relationship also had slightly higher transpiration (5 Wm-2
Richter, C.G.; Thompson, W.H.; Bosman, C.A.; Fries, P.
2015-01-01
The quantification of covariance between neuronal activities (functional connectivity) requires the observation of correlated changes and therefore multiple observations. The strength of such neuronal correlations may itself undergo moment-by-moment fluctuations, which might e.g. lead to
Westgate, Philip M
2013-07-20
Generalized estimating equations (GEEs) are routinely used for the marginal analysis of correlated data. The efficiency of GEE depends on how closely the working covariance structure resembles the true structure, and therefore accurate modeling of the working correlation of the data is important. A popular approach is the use of an unstructured working correlation matrix, as it is not as restrictive as simpler structures such as exchangeable and AR-1 and thus can theoretically improve efficiency. However, because of the potential for having to estimate a large number of correlation parameters, variances of regression parameter estimates can be larger than theoretically expected when utilizing the unstructured working correlation matrix. Therefore, standard error estimates can be negatively biased. To account for this additional finite-sample variability, we derive a bias correction that can be applied to typical estimators of the covariance matrix of parameter estimates. Via simulation and in application to a longitudinal study, we show that our proposed correction improves standard error estimation and statistical inference. Copyright © 2012 John Wiley & Sons, Ltd.
Psycho-social correlates of adjustment in adult amputees | Ajala ...
African Journals Online (AJOL)
Data collection was done by using structured questionnaire which contained the locus of control, self-concept, social support and coping scales. Multiple Regressions was used to test the independent and joint influence of these factors on adjustment. The result revealed significant influence of self-concept (t = 0.07, â = 0.03 ...
Schiefer, Jonathan; Niederbühl, Alexander; Pernice, Volker; Lennartz, Carolin; Hennig, Jürgen; LeVan, Pierre; Rotter, Stefan
2018-03-01
Knowing brain connectivity is of great importance both in basic research and for clinical applications. We are proposing a method to infer directed connectivity from zero-lag covariances of neuronal activity recorded at multiple sites. This allows us to identify causal relations that are reflected in neuronal population activity. To derive our strategy, we assume a generic linear model of interacting continuous variables, the components of which represent the activity of local neuronal populations. The suggested method for inferring connectivity from recorded signals exploits the fact that the covariance matrix derived from the observed activity contains information about the existence, the direction and the sign of connections. Assuming a sparsely coupled network, we disambiguate the underlying causal structure via L1-minimization, which is known to prefer sparse solutions. In general, this method is suited to infer effective connectivity from resting state data of various types. We show that our method is applicable over a broad range of structural parameters regarding network size and connection probability of the network. We also explored parameters affecting its activity dynamics, like the eigenvalue spectrum. Also, based on the simulation of suitable Ornstein-Uhlenbeck processes to model BOLD dynamics, we show that with our method it is possible to estimate directed connectivity from zero-lag covariances derived from such signals. In this study, we consider measurement noise and unobserved nodes as additional confounding factors. Furthermore, we investigate the amount of data required for a reliable estimate. Additionally, we apply the proposed method on full-brain resting-state fast fMRI datasets. The resulting network exhibits a tendency for close-by areas being connected as well as inter-hemispheric connections between corresponding areas. In addition, we found that a surprisingly large fraction of more than one third of all identified connections were of
Wu, Kai; Shu, Hong; Nie, Lei; Jiao, Zhenhang
2018-01-01
Spatially correlated errors are typically ignored in data assimilation, thus degenerating the observation error covariance R to a diagonal matrix. We argue that a nondiagonal R carries more observation information making assimilation results more accurate. A method, denoted TC_Cov, was proposed for soil moisture data assimilation to estimate spatially correlated observation error covariance based on triple collocation (TC). Assimilation experiments were carried out to test the performance of TC_Cov. AMSR-E soil moisture was assimilated with a diagonal R matrix computed using the TC and assimilated using a nondiagonal R matrix, as estimated by proposed TC_Cov. The ensemble Kalman filter was considered as the assimilation method. Our assimilation results were validated against climate change initiative data and ground-based soil moisture measurements using the Pearson correlation coefficient and unbiased root mean square difference metrics. These experiments confirmed that deterioration of diagonal R assimilation results occurred when model simulation is more accurate than observation data. Furthermore, nondiagonal R achieved higher correlation coefficient and lower ubRMSD values over diagonal R in experiments and demonstrated the effectiveness of TC_Cov to estimate richly structuralized R in data assimilation. In sum, compared with diagonal R, nondiagonal R may relieve the detrimental effects of assimilation when simulated model results outperform observation data.
Székely, Gábor J.; Rizzo, Maria L.
2010-01-01
Distance correlation is a new class of multivariate dependence coefficients applicable to random vectors of arbitrary and not necessarily equal dimension. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but generalize and extend these classical bivariate measures of dependence. Distance correlation characterizes independence: it is zero if and only if the random vectors are independent. The notion of covariance with...
Energy Technology Data Exchange (ETDEWEB)
Lim, Ki Chun; Kim, J. S.; Kim, C. Y.; Lee, H. K.; Moon, D. H. [Ulsan University, Seoul (Korea, Republic of)
2002-07-01
We investigated the relations between rCBF and psychopathology in schizophrenic patients using a SPM99. Thirty-two patients(M/F:22/10, 25{+-}5,6yr) with active symptoms of schizophrenia and 15 age matched normal controls underwent Tc-99m ECD brain perfusion SPECT. Psychopathology of all patients were also assessed according to PANSS (positive and negative syndrome scale in schizophrenia). By covariate SPM analysis, specific areas where rCBF correlated with sum scores of positive/negative synptoms were identified. Regional CBF of schizophrenics was different in several cortical regions from normal controls. Sum scores of positive symptoms were positively correlated with rCBF of both rectal and inferior frontal gyri and right transverse temporal gyrus, and negatively correlated with rCBF of left lingual and right middle temporal gyri (p<0.01). Sum scores of negative symptoms were positively correlated with rCBF of both middle temporal gyri and negatively correlated with rCBF of right superior parietal lobule and medial frontal gyrus (p<0.01). Positive and negative symptoms of schizophrenia were correlated with rCBF change in different regions of cerebral association cortex.
International Nuclear Information System (INIS)
Lim, Ki Chun; Kim, J. S.; Kim, C. Y.; Lee, H. K.; Moon, D. H.
2002-01-01
We investigated the relations between rCBF and psychopathology in schizophrenic patients using a SPM99. Thirty-two patients(M/F:22/10, 25±5,6yr) with active symptoms of schizophrenia and 15 age matched normal controls underwent Tc-99m ECD brain perfusion SPECT. Psychopathology of all patients were also assessed according to PANSS (positive and negative syndrome scale in schizophrenia). By covariate SPM analysis, specific areas where rCBF correlated with sum scores of positive/negative synptoms were identified. Regional CBF of schizophrenics was different in several cortical regions from normal controls. Sum scores of positive symptoms were positively correlated with rCBF of both rectal and inferior frontal gyri and right transverse temporal gyrus, and negatively correlated with rCBF of left lingual and right middle temporal gyri (p<0.01). Sum scores of negative symptoms were positively correlated with rCBF of both middle temporal gyri and negatively correlated with rCBF of right superior parietal lobule and medial frontal gyrus (p<0.01). Positive and negative symptoms of schizophrenia were correlated with rCBF change in different regions of cerebral association cortex
application of covariance analysis to feed/ ration experimental data
African Journals Online (AJOL)
Prince Acheampong
ABSTRACT. The use Analysis of Covariance (ANOCOVA) to feed/ration experimental data for birds was examined. Correlation and Regression analyses were used to adjust for the covariate – initial weight of the experimental birds. The Fisher's F statistic for the straight forward Analysis of Variance (ANOVA) showed ...
Are your covariates under control? How normalization can re-introduce covariate effects.
Pain, Oliver; Dudbridge, Frank; Ronald, Angelica
2018-04-30
Many statistical tests rely on the assumption that the residuals of a model are normally distributed. Rank-based inverse normal transformation (INT) of the dependent variable is one of the most popular approaches to satisfy the normality assumption. When covariates are included in the analysis, a common approach is to first adjust for the covariates and then normalize the residuals. This study investigated the effect of regressing covariates against the dependent variable and then applying rank-based INT to the residuals. The correlation between the dependent variable and covariates at each stage of processing was assessed. An alternative approach was tested in which rank-based INT was applied to the dependent variable before regressing covariates. Analyses based on both simulated and real data examples demonstrated that applying rank-based INT to the dependent variable residuals after regressing out covariates re-introduces a linear correlation between the dependent variable and covariates, increasing type-I errors and reducing power. On the other hand, when rank-based INT was applied prior to controlling for covariate effects, residuals were normally distributed and linearly uncorrelated with covariates. This latter approach is therefore recommended in situations were normality of the dependent variable is required.
Lam, Chun Bun; McHale, Susan M.; Crouter, Ann C.
2012-01-01
The development and adjustment correlates of parent-child social (parent, child, and others present) and dyadic time (only parent and child present) from age 8 to 18 were examined. Mothers, fathers, and firstborns and secondborns from 188 White families participated in both home and nightly phone interviews. Social time declined across…
Peer- and Self-Rated Correlates of a Teacher-Rated Typology of Child Adjustment
Lindstrom, William A., Jr.; Lease, A. Michele; Kamphaus, Randy W.
2007-01-01
External correlates of a teacher-rated typology of child adjustment developed using the Behavior Assessment System for Children were examined. Participants included 377 elementary school children recruited from 26 classrooms in the southeastern United States. Multivariate analyses of variance and planned comparisons were used to determine whether…
Directory of Open Access Journals (Sweden)
Josef Mordechai Haik
2015-03-01
Full Text Available Background: Burn victims experience immense physical and mental hardship during their process of rehabilitation and regaining functionality. We examined different objective burn related factors as well as psychological ones, in the form of personality traits, that may affect the rehabilitation process and its outcome. Objective: To assess the influence and correlation of specific personality traits and objective injury related parameters on the adjustment of burn victims post-injury. Methods: 62 male patients admitted to our burn unit due to burn injuries were compared with 36 healthy male individuals by use of questionnaires to assess each group's psychological adjustment parameters. Multivariate and hierarchical regression analysis was conducted to identify differences between the groups. Results: A significant negative correlation was found between the objective burn injury severity (e.g. TBSA and burn depth and the adjustment of burn victims (p<0.05, p<0.001, table 3. Moreover, patients more severely injured tend to be more neurotic (p<0.001, and less extroverted and agreeable (p<0.01, table 4. Conclusions: Extroverted burn victims tend to adjust better to their post-injury life while the neurotic patients tend to have difficulties adjusting. This finding may suggest new tools for early identification of maladjustment-prone patients and therefore provide them with better psychological support in a more dedicated manner.
Kisil, Vladimir V.
2010-01-01
The paper develops theory of covariant transform, which is inspired by the wavelet construction. It was observed that many interesting types of wavelets (or coherent states) arise from group representations which are not square integrable or vacuum vectors which are not admissible. Covariant transform extends an applicability of the popular wavelets construction to classic examples like the Hardy space H_2, Banach spaces, covariant functional calculus and many others. Keywords: Wavelets, cohe...
Distance covariance for stochastic processes
DEFF Research Database (Denmark)
Matsui, Muneya; Mikosch, Thomas Valentin; Samorodnitsky, Gennady
2017-01-01
The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analog of the distance covariance for two stochastic processes...
Fast Computing for Distance Covariance
Huo, Xiaoming; Szekely, Gabor J.
2014-01-01
Distance covariance and distance correlation have been widely adopted in measuring dependence of a pair of random variables or random vectors. If the computation of distance covariance and distance correlation is implemented directly accordingly to its definition then its computational complexity is O($n^2$) which is a disadvantage compared to other faster methods. In this paper we show that the computation of distance covariance and distance correlation of real valued random variables can be...
International Nuclear Information System (INIS)
Smith, D.L.
1987-03-01
Attention is called to the considerable sensitivity of many uncertainty calculations to the magnitude of the long-ranged correlations which appear in covariance matrices. If such correlations do exist, they must be included in order to properly assess the impact of the uncertainties in the data. If, however, certain assumed long-range correlations are unrealistic, then analyses involving such correlation information are almost certain to produce misleading results. The issue is discussed in general terms, and its importance is illustrated by examples based in part on recent work from this laboratory. Some practical suggestions are offered for dealing with the matter of correlations in instances where the available information is incomplete. 23 refs., 2 figs., 1 tab
Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina
2018-04-01
Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC-vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder.
Scheinost, Dustin; Holmes, Sophie E; DellaGioia, Nicole; Schleifer, Charlie; Matuskey, David; Abdallah, Chadi G; Hampson, Michelle; Krystal, John H; Anticevic, Alan; Esterlis, Irina
2018-01-01
Converging evidence suggests that major depressive disorder (MDD) affects multiple large-scale brain networks. Analyses of the correlation or covariance of regional brain structure and function applied to structural and functional MRI data may provide insights into systems-level organization and structure-to-function correlations in the brain in MDD. This study applied tensor-based morphometry and intrinsic connectivity distribution to identify regions of altered volume and intrinsic functional connectivity in data from unmedicated individuals with MDD (n=17) and healthy comparison participants (HC, n=20). These regions were then used as seeds for exploratory anatomical covariance and connectivity analyses. Reduction in volume in the anterior cingulate cortex (ACC) and lower structural covariance between the ACC and the cerebellum were observed in the MDD group. Additionally, individuals with MDD had significantly lower whole-brain intrinsic functional connectivity in the medial prefrontal cortex (mPFC). This mPFC region showed altered connectivity to the ventral lateral PFC (vlPFC) and local circuitry in MDD. Global connectivity in the ACC was negatively correlated with reported depressive symptomatology. The mPFC–vlPFC connectivity was positively correlated with depressive symptoms. Finally, we observed increased structure-to-function correlation in the PFC/ACC in the MDD group. Although across all analysis methods and modalities alterations in the PFC/ACC were a common finding, each modality and method detected alterations in subregions belonging to distinct large-scale brain networks. These exploratory results support the hypothesis that MDD is a systems level disorder affecting multiple brain networks located in the PFC and provide new insights into the pathophysiology of this disorder. PMID:28944772
Tracking of multiple objects with time-adjustable composite correlation filters
Ruchay, Alexey; Kober, Vitaly; Chernoskulov, Ilya
2017-09-01
An algorithm for tracking of multiple objects in video based on time-adjustable adaptive composite correlation filtering is proposed. For each frame a bank of composite correlation filters are designed in such a manner to provide invariance to pose, occlusion, clutter, and illumination changes. The filters are synthesized with the help of an iterative algorithm, which optimizes the discrimination capability for each object. The filters are adapted to the objects changes online using information from the current and past scene frames. Results obtained with the proposed algorithm using real-life scenes are presented and compared with those obtained with state-of-the-art tracking methods in terms of detection efficiency, tracking accuracy, and speed of processing.
Richter, Craig G; Thompson, William H; Bosman, Conrado A; Fries, Pascal
2015-07-01
The quantification of covariance between neuronal activities (functional connectivity) requires the observation of correlated changes and therefore multiple observations. The strength of such neuronal correlations may itself undergo moment-by-moment fluctuations, which might e.g. lead to fluctuations in single-trial metrics such as reaction time (RT), or may co-fluctuate with the correlation between activity in other brain areas. Yet, quantifying the relation between moment-by-moment co-fluctuations in neuronal correlations is precluded by the fact that neuronal correlations are not defined per single observation. The proposed solution quantifies this relation by first calculating neuronal correlations for all leave-one-out subsamples (i.e. the jackknife replications of all observations) and then correlating these values. Because the correlation is calculated between jackknife replications, we address this approach as jackknife correlation (JC). First, we demonstrate the equivalence of JC to conventional correlation for simulated paired data that are defined per observation and therefore allow the calculation of conventional correlation. While the JC recovers the conventional correlation precisely, alternative approaches, like sorting-and-binning, result in detrimental effects of the analysis parameters. We then explore the case of relating two spectral correlation metrics, like coherence, that require multiple observation epochs, where the only viable alternative analysis approaches are based on some form of epoch subdivision, which results in reduced spectral resolution and poor spectral estimators. We show that JC outperforms these approaches, particularly for short epoch lengths, without sacrificing any spectral resolution. Finally, we note that the JC can be applied to relate fluctuations in any smooth metric that is not defined on single observations. Copyright © 2015. Published by Elsevier Inc.
Pozsgay, Victor; Hirsch, Flavien; Branciard, Cyril; Brunner, Nicolas
2017-12-01
We introduce Bell inequalities based on covariance, one of the most common measures of correlation. Explicit examples are discussed, and violations in quantum theory are demonstrated. A crucial feature of these covariance Bell inequalities is their nonlinearity; this has nontrivial consequences for the derivation of their local bound, which is not reached by deterministic local correlations. For our simplest inequality, we derive analytically tight bounds for both local and quantum correlations. An interesting application of covariance Bell inequalities is that they can act as "shared randomness witnesses": specifically, the value of the Bell expression gives device-independent lower bounds on both the dimension and the entropy of the shared random variable in a local model.
Lam, Chun Bun; McHale, Susan M.; Crouter, Ann C.
2012-01-01
The development and adjustment correlates of parent-child social (parent, child, and others present) and dyadic time (only parent and child present) from age 8 to 18 were examined. Mothers, fathers, and firstborns and secondborns from 188 White families participated in both home and nightly phone interviews. Social time declined across adolescence, but dyadic time with mothers and fathers peaked in early and middle adolescence, respectively. Additionally, secondborns’ social time declined more slowly than firstborns’, and gendered time use patterns were more pronounced in boys and in opposite-sex sibling dyads. Finally, youths who spent more dyadic time with their fathers, on average, had higher general self-worth, and changes in social time with fathers were positively linked to changes in social competence. PMID:22925042
Lam, Chun Bun; McHale, Susan M; Crouter, Ann C
2012-11-01
The development and adjustment correlates of parent-child social (parent, child, and others present) and dyadic time (only parent and child present) from age 8 to 18 were examined. Mothers, fathers, and firstborns and secondborns from 188 White families participated in both home and nightly phone interviews. Social time declined across adolescence, but dyadic time with mothers and fathers peaked in early and middle adolescence, respectively. In addition, secondborns' social time declined more slowly than firstborns', and gendered time use patterns were more pronounced in boys and in opposite-sex sibling dyads. Finally, youths who spent more dyadic time with their fathers, on average, had higher general self-worth, and changes in social time with fathers were positively linked to changes in social competence. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.
Di, Xin; Gohel, Suril; Thielcke, Andre; Wehrl, Hans F; Biswal, Bharat B
2017-11-01
Relationships between spatially remote brain regions in human have typically been estimated by moment-to-moment correlations of blood-oxygen-level dependent signals in resting-state using functional MRI (fMRI). Recently, studies using subject-to-subject covariance of anatomical volumes, cortical thickness, and metabolic activity are becoming increasingly popular. However, question remains on whether these measures reflect the same inter-region connectivity and brain network organizations. In the current study, we systematically analyzed inter-subject volumetric covariance from anatomical MRI images, metabolic covariance from fluorodeoxyglucose positron emission tomography images from 193 healthy subjects, and resting-state moment-to-moment correlations from fMRI images of a subset of 44 subjects. The correlation matrices calculated from the three methods were found to be minimally correlated, with higher correlation in the range of 0.31, as well as limited proportion of overlapping connections. The volumetric network showed the highest global efficiency and lowest mean clustering coefficient, leaning toward random-like network, while the metabolic and resting-state networks conveyed properties more resembling small-world networks. Community structures of the volumetric and metabolic networks did not reflect known functional organizations, which could be observed in resting-state network. The current results suggested that inter-subject volumetric and metabolic covariance do not necessarily reflect the inter-regional relationships and network organizations as resting-state correlations, thus calling for cautions on interpreting results of inter-subject covariance networks.
Dynamic adjustments of cognitive control: oscillatory correlates of the conflict adaptation effect.
Pastötter, Bernhard; Dreisbach, Gesine; Bäuml, Karl-Heinz T
2013-12-01
It is a prominent idea that cognitive control mediates conflict adaptation, in that response conflict in a previous trial triggers control adjustments that reduce conflict in a current trial. In the present EEG study, we investigated the dynamics of cognitive control in a response-priming task by examining the effects of previous trial conflict on intertrial and current trial oscillatory brain activities, both on the electrode and the source level. Behavioral results showed conflict adaptation effects for RTs and response accuracy. Physiological results showed sustained intertrial effects in left parietal theta power, originating in the left inferior parietal cortex, and midcentral beta power, originating in the left and right (pre)motor cortex. Moreover, physiological analysis revealed a current trial conflict adaptation effect in midfrontal theta power, originating in the ACC. Correlational analyses showed that intertrial effects predicted conflict-induced midfrontal theta power in currently incongruent trials. In addition, conflict adaptation effects in midfrontal theta power and RTs were positively related. Together, these findings point to a dynamic cognitive control system that, as a function of previous trial type, up- and down-regulates attention and preparatory motor activities in anticipation of the next trial.
Sysko, Robyn; Hildebrandt, Tom B.; Kaplan, Simona; Brewer, Stephanie K.; Zitsman, Jeffrey L.; Devlin, Michael J.
2014-01-01
Background Adherence behaviors have not been examined among adolescents undergoing laparoscopic adjustable gastric banding (LAGB). In addition, studies of youth receiving bariatric surgery have not considered the influence of psychopathology on postoperative adherence. Objective The purpose of this study was to evaluate predictors and correlates of adherence to post-surgery visits among a sample of adolescents undergoing LAGB. Setting Psychiatry Department, University Medical Center, United States. Methods Postoperative visits with surgical staff were analyzed over the two years following surgery (n= 101 adolescents). Growth mixture modeling examined trends in adherence. Results A three-class solution provided the best fit to the data. The classes from the final model were characterized by class 1 (61.6%) demonstrating high levels of adherence over the 24 months following LAGB, class 2 (28.5%) showing a more gradual decline in adherence, and class 3 (9.9%) with an accelerated decline in adherence. Higher levels of preoperative depressive symptoms and more preoperative episodes of loss of control over eating decreased the likelihood of adherence. Class 3 adolescents had significantly higher estimated 24-month body mass indices than Classes 1 or 2. Conclusions Variable patterns of follow-up visit adherence were identified among adolescents receiving LAGB, which were predicted by depressive symptoms and loss of control over eating. The trajectory characterized by a rapid decline in adherence to follow-up visits was also associated with less weight loss. PMID:25066443
International Nuclear Information System (INIS)
Akhtar, K.; Ahmed, W.
2008-01-01
To determine the pattern and profile of Congenital Heart Diseases (CHD) in paediatric patients (age 1 day to 18 years) presenting to a paediatric tertiary referral centre and its correlation to risk adjustment for surgery for congenital heart disease. Over a period of 6 months, 1149 cases underwent 2-D echocardiography. It was a non-probability purposive sampling. This study showed 25% of all referrals had normal hearts. A male preponderance (38%) was observed from 1 year to 5 years age group. Nineteen percent of the cases were categorized as cyanotic CHD with the remaining as acyanotic variety. Tetralogy of Fallot (TOF) represented 10%, Ventricular Septal Defects (VSD) 24%, followed by Patent Ductus Arteriosus (PDA) and Atrial Septal Defect (ASD), which comprised 6.6% and 6.5% respectively. VSD was the most common association in patients with more complex CHD (10%) followed by PDA in 3% and ASD in 1.2% of the cases. Most of the cases were category 2 in the RACHS-1 scoring system. VSD and TOF formed the major groups of cases profiled. Most of the cases recommended for surgery for congenital heart disease belonged to the risk category 2 (28.1%) followed by the risk category 1 (12.7%) of the RACHS-1 scoring system. (author)
Directory of Open Access Journals (Sweden)
Agustín Ruiz
Full Text Available Plasma amyloid beta (Aβ levels are being investigated as potential biomarkers for Alzheimer's disease. In AB128 cross-sectional study, a number of medical relevant correlates of blood Aβ40 or Aβ42 were analyzed in 140 subjects (51 Alzheimer's disease patients, 53 healthy controls and 36 individuals diagnosed with mild cognitive impairment. We determined the association between multiple variables with Aβ40 and Aβ42 levels measured in three different blood compartments called i Aβ directly accessible (DA in the plasma, ii Aβ recovered from the plasma matrix (RP after diluting the plasma sample in a formulated buffer, and iii associated with the remaining cellular pellet (CP. We confirmed that diastolic blood pressure (DBP is consistently correlated with blood DA Aβ40 levels (r=-0.19, P=0.032. These results were consistent in the three phenotypic groups studied. Importantly, the observation resisted covariation with age, gender or creatinine levels. Observed effect size and direction of Aβ40 levels/DBP correlation are in accordance with previous reports. Of note, DA Aβ40 and the RP Aβ40 were also strongly associated with creatinine levels (r=0.599, P<<0.001 and to a lesser extent to urea, age, hematocrit, uric acid and homocysteine (p<0.001. DBP and the rest of statistical significant correlates identified should be considered as potential confounder factors in studies investigating blood Aβ levels as potential AD biomarker. Remarkably, the factors affecting Aβ levels in plasma (DA, RP and blood cell compartments (CP seem completely different.
Hurdebise, Quentin; Heinesch, Bernard; De Ligne, Anne; Vincke, Caroline; Aubinet, Marc
2017-04-01
Long-term data series of carbon dioxide and other gas exchanges between terrestrial ecosystems and atmosphere become more and more numerous. Long-term analyses of such exchanges require a good understanding of measurement conditions during the investigated period. Independently of climate drivers, measurements may indeed be influenced by measurement conditions themselves subjected to long-term variability due to vegetation growth or set-up changes. The present research refers to the Vielsalm Terrestrial Observatory (VTO) an ICOS candidate site located in a mixed forest (beech, silver fir, Douglas fir, Norway spruce) in the Belgian Ardenne. Fluxes of momentum, carbon dioxide and sensible heat have been continuously measured there by eddy covariance for more than 20 years. During this period, changes in canopy height and measurement height occurred. The correlation coefficients (for momemtum, sensible heat and CO2) and the normalized standard deviations measured for the past 20 years at the Vielsalm Terrestrial Observatory (VTO) were analysed in order to define how the fluxes, independently of climate conditions, were affected by the surrounding environment evolution, including tree growth, forest thinning and tower height change. A relationship between canopy aerodynamic distance and the momentum correlation coefficient was found which is characteristic of the roughness sublayer, and suggests that momentum transport processes were affected by z-d. In contrast, no relationship was found for sensible heat and CO2 correlation coefficients, suggesting that the z-d variability observed did not affect their turbulent transport. There were strong differences in these coefficients, however, between two wind sectors, characterized by contrasted stands (height differences, homogeneity) and different hypotheses were raised to explain it. This study highlighted the importance of taking the surrounding environment variability into account in order to ensure the spatio
Extendable linearised adjustment model for deformation analysis
Velsink, H.
2015-01-01
This paper gives a linearised adjustment model for the affine, similarity and congruence transformations in 3D that is easily extendable with other parameters to describe deformations. The model considers all coordinates stochastic. Full positive semi-definite covariance matrices and correlation
Moerbeek, Mirjam; van Schie, Sander
2016-07-11
The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.
Dong, Nianbo; Reinke, Wendy M; Herman, Keith C; Bradshaw, Catherine P; Murray, Desiree W
2016-09-30
There is a need for greater guidance regarding design parameters and empirical benchmarks for social and behavioral outcomes to inform assumptions in the design and interpretation of cluster randomized trials (CRTs). We calculated the empirical reference values on critical research design parameters associated with statistical power for children's social and behavioral outcomes, including effect sizes, intraclass correlations (ICCs), and proportions of variance explained by a covariate at different levels (R 2 ). Children from kindergarten to Grade 5 in the samples from four large CRTs evaluating the effectiveness of two classroom- and two school-level preventive interventions. Teacher ratings of students' social and behavioral outcomes using the Teacher Observation of Classroom Adaptation-Checklist and the Social Competence Scale-Teacher. Two types of effect size benchmarks were calculated: (1) normative expectations for change and (2) policy-relevant demographic performance gaps. The ICCs and R 2 were calculated using two-level hierarchical linear modeling (HLM), where students are nested within schools, and three-level HLM, where students were nested within classrooms, and classrooms were nested within schools. Comprehensive tables of benchmarks and ICC values are provided to inform prevention researchers in interpreting the effect size of interventions and conduct power analyses for designing CRTs of children's social and behavioral outcomes. The discussion also provides a demonstration for how to use the parameter reference values provided in this article to calculate the sample size for two- and three-level CRTs designs. © The Author(s) 2016.
Armbruster, W S; Di Stilio, V S; Tuxill, J D; Flores, T C; Velásquez Runk, J L
1999-01-01
Nearly forty years ago R. L. Berg proposed that plants with specialized pollination ecology evolve genetic and developmental systems that decouple floral morphology from phenotypic variation in vegetative traits. These species evolve separate floral and vegetative trait clusters, or as she termed them, "correlation pleiades." The predictions of this hypothesis have been generally supported, but only a small sample of temperate-zone herb and grass species has been tested. To further evaluate this hypothesis, especially its applicability to plants of other growth forms, we examined the patterns of phenotypic variation and covariation of floral and vegetative traits in nine species of Neotropical plants. We recognized seven specific predictions of Berg's hypothesis. Our results supported some predictions but not others. Species with specialized pollination systems usually had floral traits decoupled (weak correlation; Canna and Eichornia) or buffered (relationship with shallow proportional slope; Calathea and Canna) from variation in vegetative traits. However, the same trend was also observed in three species with unspecialized pollination systems (Echinodorus, Muntingia, and Wedelia). One species with unspecialized pollination (Croton) and one wind-pollinated species (Cyperus) showed no decoupling or buffering, as predicted. While species with specialized pollination usually showed lower coefficients of variation for floral traits than vegetative traits (as predicted), the same was also true of species with unspecialized or wind pollination (unlike our prediction). Species with specialized pollination showed less variation in floral traits than did species with unspecialized or wind pollination, as predicted. However, the same was true of the corresponding vegetative traits, which was unexpected. Also in contrast to our prediction, plants with specialized pollination systems did not exhibit tighter phenotypic integration of floral characters than did species with
Peiris, T. S. G.; Nanayakkara, K. A. D. S. A.
2017-09-01
Mathematics plays a key role in engineering sciences as it assists to develop the intellectual maturity and analytical thinking of engineering students and exploring the student academic performance has received great attention recently. The lack of control over covariates motivates the need for their adjustment when measuring the degree of association between two sets of variables in Canonical Correlation Analysis (CCA). Thus to examine the individual effects of mathematics in Level 1 and Level 2 on engineering performance in Level 2, two adjusted analyses in CCA: Part CCA and Partial CCA were applied for the raw marks of engineering undergraduates for three different disciplines, at the Faculty of Engineering, University of Moratuwa, Sri Lanka. The joint influence of mathematics in Level 1 and Level 2 is significant on engineering performance in Level 2 irrespective of the engineering disciplines. The individual effect of mathematics in Level 2 is significantly higher compared to the individual effect of mathematics in Level 1 on engineering performance in Level 2. Furthermore, the individual effect of mathematics in Level 1 can be negligible. But, there would be a notable indirect effect of mathematics in Level 1 on engineering performance in Level 2. It can be concluded that the joint effect of mathematics in both Level 1 and Level 2 is immensely beneficial to improve the overall academic performance at the end of Level 2 of the engineering students. Furthermore, it was found that the impact mathematics varies among engineering disciplines. As partial CCA and partial CCA are not widely explored in applied work, it is recommended to use these techniques for various applications.
Chao, Shiau-Fang
2017-06-01
The present study examines the associations among social support, coping strategies and relocation adjustment outcomes, including community cohesion, residential satisfaction and depressive symptoms, for older persons in Taiwan displaced by Typhoon Morakot. This study enrolled 372 adults aged 60 years or older who were relocated to permanent houses after Typhoon Morakot destroyed their homes on 8 August 2009. A path analysis simultaneously examined the hypothesized links among social support, coping strategies and relocation adjustment outcomes. The relationships between coping strategies and relocation outcomes varied. Problem-focused and support-seeking coping were positively related to perceived community cohesion, whereas emotion-focused coping was associated with a high number of depressive symptoms. Social support was positively related to residential satisfaction. Additionally, social support was also indirectly related to increased community cohesion and residential satisfaction through its positive relationship with support-seeking and problem-focused coping. More interventions should be implemented to enhance support within informal networks and a sense of belonging to the new resident community, thereby promoting more active coping strategies, enhancing the effectiveness of coping efforts and maximizing positive adjustment outcomes. Geriatr Gerontol Int 2017; 17: 1006-1014. © 2016 Japan Geriatrics Society.
Energy Technology Data Exchange (ETDEWEB)
Sikora, Andrzej, E-mail: sikora@iel.wroc.pl [Electrotechnical Institute, Division of Electrotechnology and Materials Science, M. Skłodowskiej-Curie 55/61, 50-369 Wrocław (Poland); Rodak, Aleksander [Faculty of Electronics, Wrocław University of Technology, Janiszewskiego 11/17, 50-372 Wrocław (Poland); Unold, Olgierd [Institute of Computer Engineering, Control and Robotics, Faculty of Electronics, Wrocław University of Technology, Janiszewskiego 11/17, 50-372 Wrocław (Poland); Klapetek, Petr [Czech Metrology Institute, Okružní 31, 638 00 Brno (Czech Republic)
2016-12-15
In this paper a novel approach for the practical utilization of the 2D wavelet filter in terms of the artifacts removal from atomic force microscopy measurements results is presented. The utilization of additional data such as summary photodiode signal map is implemented in terms of the identification of the areas requiring the data processing, filtering settings optimization and the verification of the process performance. Such an approach allows to perform the filtering parameters adjustment by average user, while the straightforward method requires an expertise in this field. The procedure was developed as the function of the Gwyddion software. The examples of filtering the phase imaging and Electrostatic Force Microscopy measurement result are presented. As the wavelet filtering feature may remove a local artifacts, its superior efficiency over similar approach with 2D Fast Fourier Transformate based filter (2D FFT) can be noticed. - Highlights: • A novel approach to 2D wavelet-based filter for atomic force microscopy is shown. • The additional AFM measurement signal is used to adjust the filter. • Efficient removal of the local interference phenomena caused artifacts is presented.
International Nuclear Information System (INIS)
Sikora, Andrzej; Rodak, Aleksander; Unold, Olgierd; Klapetek, Petr
2016-01-01
In this paper a novel approach for the practical utilization of the 2D wavelet filter in terms of the artifacts removal from atomic force microscopy measurements results is presented. The utilization of additional data such as summary photodiode signal map is implemented in terms of the identification of the areas requiring the data processing, filtering settings optimization and the verification of the process performance. Such an approach allows to perform the filtering parameters adjustment by average user, while the straightforward method requires an expertise in this field. The procedure was developed as the function of the Gwyddion software. The examples of filtering the phase imaging and Electrostatic Force Microscopy measurement result are presented. As the wavelet filtering feature may remove a local artifacts, its superior efficiency over similar approach with 2D Fast Fourier Transformate based filter (2D FFT) can be noticed. - Highlights: • A novel approach to 2D wavelet-based filter for atomic force microscopy is shown. • The additional AFM measurement signal is used to adjust the filter. • Efficient removal of the local interference phenomena caused artifacts is presented.
Sikora, Andrzej; Rodak, Aleksander; Unold, Olgierd; Klapetek, Petr
2016-12-01
In this paper a novel approach for the practical utilization of the 2D wavelet filter in terms of the artifacts removal from atomic force microscopy measurements results is presented. The utilization of additional data such as summary photodiode signal map is implemented in terms of the identification of the areas requiring the data processing, filtering settings optimization and the verification of the process performance. Such an approach allows to perform the filtering parameters adjustment by average user, while the straightforward method requires an expertise in this field. The procedure was developed as the function of the Gwyddion software. The examples of filtering the phase imaging and Electrostatic Force Microscopy measurement result are presented. As the wavelet filtering feature may remove a local artifacts, its superior efficiency over similar approach with 2D Fast Fourier Transformate based filter (2D FFT) can be noticed. Copyright © 2016 Elsevier B.V. All rights reserved.
Ibrahim Fahmy; Yasser Elkhiat; Mohamed Saad; Hussein Ghanem
2013-01-01
Objective: To correlate late spermatid score and sperm count in men with normal semen analysis and oligozoospermia undergoing intracytoplasmic sperm injection (ICSI) to set the average threshold of spermatids/tubule of testicular tissue needed for normal sperm count/ml of semen. Material and methods: This study was conducted on 24 normozoospermic subjects and 18 oligozoospermic patients who underwent wide bore needle biopsy because of failed sperm collection at the day of ICSI. Clinical da...
Directory of Open Access Journals (Sweden)
Ibrahim Fahmy
2013-12-01
Conclusion: This work supports the hypothesis that late spermatid score is a simple and reliable method for quantitation of spermatogenesis and it correlates well with the sperm count. The value of late spermatids needed for normal sperm count in this report is different from some other reports. The better standardization of work in this study may help resetting a new late spermatid threshold for normal sperm count.
Martin, Gary E; Hilton, Bruce D; Irish, Patrick A; Blinov, Kirill A; Williams, Antony J
2007-10-01
Utilization of long-range (1)H--(15)N heteronuclear chemical shift correlation has continually grown in importance since the first applications were reported in 1995. More recently, indirect covariance NMR methods have been introduced followed by the development of unsymmetrical indirect covariance processing methods. The latter technique has been shown to allow the calculation of hyphenated 2D NMR data matrices from more readily acquired nonhyphenated 2D NMR spectra. We recently reported the use of unsymmetrical indirect covariance processing to combine (1)H--(13)C GHSQC and (1)H--(15)N GHMBC long-range spectra to yield a (13)C--(15)N HSQC-HMBC chemical shift correlation spectrum that could not be acquired in a reasonable period of time without resorting to (15)N-labeled molecules. We now report the unsymmetrical indirect covariance processing of (1)H--(13)C GHMBC and (1)H--(15)N IMPEACH spectra to afford a (13)C--(15)N HMBC-IMPEACH spectrum that has the potential to span as many as six to eight bonds. Correlations for carbon resonances long-range coupled to a protonated carbon in the (1)H--(13)C HMBC spectrum are transferred via the long-range (1)H--(15)N coupling pathway in the (1)H--(15)N IMPEACH spectrum to afford a much broader range of correlation possibilities in the (13)C--(15)N HMBC-IMPEACH correlation spectrum. The indole alkaloid vincamine is used as a model compound to illustrate the application of the method. (c) 2007 John Wiley & Sons, Ltd.
Li, Bang-Jian; Wang, Quan-Bao; Duan, Deng-Ping; Chen, Ji-An
2018-05-01
Intensity saturation can cause decorrelation phenomenon and decrease the measurement accuracy in digital image correlation (DIC). In the paper, the grey intensity adjustment strategy is proposed to improve the measurement accuracy of DIC considering the effect of intensity saturation. First, the grey intensity adjustment strategy is described in detail, which can recover the truncated grey intensities of the saturated pixels and reduce the decorrelation phenomenon. The simulated speckle patterns are then employed to demonstrate the efficacy of the proposed strategy, which indicates that the displacement accuracy can be improved by about 40% by the proposed strategy. Finally, the true experimental image is used to show the feasibility of the proposed strategy, which indicates that the displacement accuracy can be increased by about 10% by the proposed strategy.
Reissing, Elke D; Binik, Yitzchak M; Khalifé, Samir; Cohen, Deborah; Amsel, Rhonda
2003-01-01
This study investigated the role of sexual and physical abuse, sexual self-schema, sexual functioning, sexual knowledge, relationship adjustment, and psychological distress in 87 women matched on age, relationship status, and parity and assigned to 3 groups--vaginismus, dyspareunia/vulvar vestibulitis syndrome (VVS), and no pain. More women with vaginismus reported a history of childhood sexual interference, and women in both the vaginismus and VVS groups reported lower levels of sexual functioning and a less positive sexual self-schema. Lack of support for traditionally held hypotheses concerning etiological correlates of vaginismus and the relationship between vaginismus and dyspareunia are discussed.
Czech Academy of Sciences Publication Activity Database
Czernek, Jiří; Brus, Jiří
2014-01-01
Roč. 608, 21 July (2014), s. 334-339 ISSN 0009-2614 R&D Projects: GA ČR(CZ) GA14-03636S Institutional support: RVO:61389013 Keywords : NMR * DFT * covariance Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 1.897, year: 2014
Uncertainty covariances in robotics applications
International Nuclear Information System (INIS)
Smith, D.L.
1984-01-01
The application of uncertainty covariance matrices in the analysis of robot trajectory errors is explored. First, relevant statistical concepts are reviewed briefly. Then, a simple, hypothetical robot model is considered to illustrate methods for error propagation and performance test data evaluation. The importance of including error correlations is emphasized
AFCI-2.0 Neutron Cross Section Covariance Library
Energy Technology Data Exchange (ETDEWEB)
Herman, M.; Herman, M; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.
2011-03-01
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
International Nuclear Information System (INIS)
Herman, M.; Oblozinsky, P.; Mattoon, C.M.; Pigni, M.; Hoblit, S.; Mughabghab, S.F.; Sonzogni, A.; Talou, P.; Chadwick, M.B.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Yount, P.G.
2011-01-01
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 and 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
A class of covariate-dependent spatiotemporal covariance functions
Reich, Brian J; Eidsvik, Jo; Guindani, Michele; Nail, Amy J; Schmidt, Alexandra M.
2014-01-01
In geostatistics, it is common to model spatially distributed phenomena through an underlying stationary and isotropic spatial process. However, these assumptions are often untenable in practice because of the influence of local effects in the correlation structure. Therefore, it has been of prolonged interest in the literature to provide flexible and effective ways to model non-stationarity in the spatial effects. Arguably, due to the local nature of the problem, we might envision that the correlation structure would be highly dependent on local characteristics of the domain of study, namely the latitude, longitude and altitude of the observation sites, as well as other locally defined covariate information. In this work, we provide a flexible and computationally feasible way for allowing the correlation structure of the underlying processes to depend on local covariate information. We discuss the properties of the induced covariance functions and discuss methods to assess its dependence on local covariate information by means of a simulation study and the analysis of data observed at ozone-monitoring stations in the Southeast United States. PMID:24772199
International Nuclear Information System (INIS)
Kawano, Toshihiko; Shibata, Keiichi.
1997-09-01
A covariance evaluation system for the evaluated nuclear data library was established. The parameter estimation method and the least squares method with a spline function are used to generate the covariance data. Uncertainties of nuclear reaction model parameters are estimated from experimental data uncertainties, then the covariance of the evaluated cross sections is calculated by means of error propagation. Computer programs ELIESE-3, EGNASH4, ECIS, and CASTHY are used. Covariances of 238 U reaction cross sections were calculated with this system. (author)
Covariate Imbalance and Precision in Measuring Treatment Effects
Liu, Xiaofeng Steven
2011-01-01
Covariate adjustment can increase the precision of estimates by removing unexplained variance from the error in randomized experiments, although chance covariate imbalance tends to counteract the improvement in precision. The author develops an easy measure to examine chance covariate imbalance in randomization by standardizing the average…
Networks of myelin covariance.
Melie-Garcia, Lester; Slater, David; Ruef, Anne; Sanabria-Diaz, Gretel; Preisig, Martin; Kherif, Ferath; Draganski, Bogdan; Lutti, Antoine
2018-04-01
Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures (i.e., cortical thickness) between brain structures across subjects (Evans, ). However, the existence of networks of microstructural changes within brain tissue has been largely unexplored so far. In this article, we studied in vivo the concurrent myelination processes among brain anatomical structures that gathered together emerge to form nonrandom networks. We name these "networks of myelin covariance" (Myelin-Nets). The Myelin-Nets were built from quantitative Magnetization Transfer data-an in-vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin-Nets. We therefore selected two age groups: Young-Age (20-31 years old) and Old-Age (60-71 years old) and a pool of participants from 48 to 87 years old for a Myelin-Nets aging trajectory study. We found that the topological organization of the Myelin-Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin-Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.
Multivariate covariance generalized linear models
DEFF Research Database (Denmark)
Bonat, W. H.; Jørgensen, Bent
2016-01-01
are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions......We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...
A complete generalized adjustment criterion
Perković, Emilija; Textor, Johannes; Kalisch, Markus; Maathuis, Marloes H.
2015-01-01
Covariate adjustment is a widely used approach to estimate total causal effects from observational data. Several graphical criteria have been developed in recent years to identify valid covariates for adjustment from graphical causal models. These criteria can handle multiple causes, latent
Covariance Spectroscopy for Fissile Material Detection
International Nuclear Information System (INIS)
Trainham, Rusty; Tinsley, Jim; Hurley, Paul; Keegan, Ray
2009-01-01
Nuclear fission produces multiple prompt neutrons and gammas at each fission event. The resulting daughter nuclei continue to emit delayed radiation as neutrons boil off, beta decay occurs, etc. All of the radiations are causally connected, and therefore correlated. The correlations are generally positive, but when different decay channels compete, so that some radiations tend to exclude others, negative correlations could also be observed. A similar problem of reduced complexity is that of cascades radiation, whereby a simple radioactive decay produces two or more correlated gamma rays at each decay. Covariance is the usual means for measuring correlation, and techniques of covariance mapping may be useful to produce distinct signatures of special nuclear materials (SNM). A covariance measurement can also be used to filter data streams because uncorrelated signals are largely rejected. The technique is generally more effective than a coincidence measurement. In this poster, we concentrate on cascades and the covariance filtering problem
Nishiyama, N.
2001-12-01
Absolute return strategy provided from fund of funds (FOFs) investment schemes is the focus in Japanese Financial Community. FOFs investment mainly consists of hedge fund investment and it has two major characteristics which are low correlation against benchmark index and little impact from various external changes in the environment given maximizing return. According to the historical track record of survival hedge funds in this business world, they maintain a stable high return and low risk. However, one must keep in mind that low risk would not be equal to risk free. The failure of Long-term capital management (LTCM) that took place in the summer of 1998 was a symbolized phenomenon. The summer of 1998 exhibited a certain limitation of traditional value at risk (VaR) and some possibility that traditional VaR could be ineffectual to the nonlinear type of fluctuation in the market. In this paper, I try to bring self-organized criticality (SOC) into portfolio risk control. SOC would be well known as a model of decay in the natural world. I analyzed nonlinear type of fluctuation in the market as SOC and applied SOC to capture complicated market movement using threshold point of SOC and risk adjustments by scenario correlation as implicit signals. Threshold becomes the control parameter of risk exposure to set downside floor and forecast extreme nonlinear type of fluctuation under a certain probability. Simulation results would show synergy effect of portfolio risk control between SOC and absolute return strategy.
Directory of Open Access Journals (Sweden)
Carmassi C
2016-02-01
Full Text Available Claudia Carmassi,1 Camilla Gesi,1 Marly Simoncini,1 Luca Favilla,1 Gabriele Massimetti,1 Maria Cristina Olivieri,1 Ciro Conversano,2 Massimo Santini,2 Liliana Dell’Osso1 1Department of Clinical and Experimental Medicine, Section of Psychiatry, University of Pisa, Pisa, Italy; 2Emergency Medicine and Emergency Room Unit, Azienda Ospedaliero-Universitaria Pisana (AOUP, Pisa, Italy Abstract: The Diagnostic and Statistical Manual of Mental Disorders Fifth Edition (DSM-5 has recently recognized a particular risk for posttraumatic stress disorder (PTSD among first responders (criterion A4, acknowledging emergency units as stressful places of employment. Little data is yet available on DSM-5 among emergency health operators. The aim of this study was to assess DSM-5 symptomatological PTSD and posttraumatic stress spectrum, as well as their impact on work and social functioning, in the emergency staff of a major university hospital in Italy. One hundred and ten subjects (doctors, nurses, and health-care assistants were recruited at the Emergency Unit of the Azienda Ospedaliero-Universitaria Pisana (Italy and assessed by the Trauma and Loss Spectrum-Self Report (TALS-SR and Work and Social Adjustment Scale (WSAS. A 15.7% DSM-5 symptomatological PTSD prevalence rate was found. Nongraduated persons reported significantly higher TALS-SR Domain IV (reaction to loss or traumatic events scores and a significantly higher proportion of individuals presenting at least one maladaptive behavior (TALS-SR Domain VII, with respect to graduate ones. Women reported significantly higher WSAS scores. Significant correlations emerged between PTSD symptoms and WSAS total scores among health-care assistants, nongraduates and women. Our results showed emergency workers to be at risk for posttraumatic stress spectrum and related work and social impairment, particularly among women and nongraduated subjects. Keywords: posttraumatic stress disorder (PTSD, emergency, emergency
Forecasting Covariance Matrices: A Mixed Frequency Approach
DEFF Research Database (Denmark)
Halbleib, Roxana; Voev, Valeri
This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows for flexi......This paper proposes a new method for forecasting covariance matrices of financial returns. The model mixes volatility forecasts from a dynamic model of daily realized volatilities estimated with high-frequency data with correlation forecasts based on daily data. This new approach allows...... for flexible dependence patterns for volatilities and correlations, and can be applied to covariance matrices of large dimensions. The separate modeling of volatility and correlation forecasts considerably reduces the estimation and measurement error implied by the joint estimation and modeling of covariance...
Enhanced brainstem and cortical evoked response amplitudes: single-trial covariance analysis.
Galbraith, G C
2001-06-01
The purpose of the present study was to develop analytic procedures that improve the definition of sensory evoked response components. Such procedures could benefit all recordings but would especially benefit difficult recordings where many trials are contaminated by muscle and movement artifacts. First, cross-correlation and latency adjustment analyses were applied to the human brainstem frequency-following response and cortical auditory evoked response recorded on the same trials. Lagged cross-correlation functions were computed, for each of 17 subjects, between single-trial data and templates consisting of the sinusoid stimulus waveform for the brainstem response and the subject's own smoothed averaged evoked response P2 component for the cortical response. Trials were considered in the analysis only if the maximum correlation-squared (r2) exceeded .5 (negatively correlated trials were thus included). Identical correlation coefficients may be based on signals with quite different amplitudes, but it is possible to assess amplitude by the nonnormalized covariance function. Next, an algorithm is applied in which each trial with negative covariance is matched to a trial with similar, but positive, covariance and these matched-trial pairs are deleted. When an evoked response signal is present in the data, the majority of trials positively correlate with the template. Thus, a residual of positively correlated trials remains after matched covariance trials are deleted. When these residual trials are averaged, the resulting brainstem and cortical responses show greatly enhanced amplitudes. This result supports the utility of this analysis technique in clarifying and assessing evoked response signals.
International Nuclear Information System (INIS)
Uematsu, Takayoshi; Kasami, Masako; Watanabe, Junichiro
2012-01-01
Purpose: The purpose of this study was to assess the correlation between mammographic density, age, and background enhancement on breast MRI without adjusting for the phase in patients’ menstrual cycle. Material and methods: The background enhancement of bilateral breast MRI and the breast density of mammography in 146 consecutive women without adjusting for the phase in patients’ menstrual cycle were reviewed. The breast density was classified into four categories according to the American College of Radiology the Breast Imaging Reporting and Data System lexicon. The background enhancement was classified into four categories: minimal, mild, moderate, and marked. The correlations of mammographic breast density as well as age with background enhancement on breast MRI were examined. Results: There was a significant correlation between mammographic breast density and background enhancement (p = 0.011). All nine cases with almost completely fat mammographic breast density showed minimal (78%) or mild (12%) background enhancement on breast MRI. There was a significant inverse correlation between age and background enhancement (p < 0.0001). Younger patients with dense breasts were more likely to demonstrate moderate/marked background enhancement. Conclusion: When no adjusting for the phase in patients’ menstrual cycle, a significant correlation was observed between background enhancement and mammographic density. A significant inverse correlation was also observed between age and background enhancement.
HiCRep: assessing the reproducibility of Hi-C data using a stratum-adjusted correlation coefficient.
Yang, Tao; Zhang, Feipeng; Yardımcı, Galip Gürkan; Song, Fan; Hardison, Ross C; Noble, William Stafford; Yue, Feng; Li, Qunhua
2017-11-01
Hi-C is a powerful technology for studying genome-wide chromatin interactions. However, current methods for assessing Hi-C data reproducibility can produce misleading results because they ignore spatial features in Hi-C data, such as domain structure and distance dependence. We present HiCRep, a framework for assessing the reproducibility of Hi-C data that systematically accounts for these features. In particular, we introduce a novel similarity measure, the stratum adjusted correlation coefficient (SCC), for quantifying the similarity between Hi-C interaction matrices. Not only does it provide a statistically sound and reliable evaluation of reproducibility, SCC can also be used to quantify differences between Hi-C contact matrices and to determine the optimal sequencing depth for a desired resolution. The measure consistently shows higher accuracy than existing approaches in distinguishing subtle differences in reproducibility and depicting interrelationships of cell lineages. The proposed measure is straightforward to interpret and easy to compute, making it well-suited for providing standardized, interpretable, automatable, and scalable quality control. The freely available R package HiCRep implements our approach. © 2017 Yang et al.; Published by Cold Spring Harbor Laboratory Press.
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.
On the covariance matrices in the evaluated nuclear data
International Nuclear Information System (INIS)
Corcuera, R.P.
1983-05-01
The implications of the uncertainties of nuclear data on reactor calculations are shown. The concept of variance, covariance and correlation are expressed first by intuitive definitions and then through statistical theory. The format of the covariance data for ENDF/B is explained and the formulas to obtain the multigroup covariances are given. (Author) [pt
On estimating cosmology-dependent covariance matrices
International Nuclear Information System (INIS)
Morrison, Christopher B.; Schneider, Michael D.
2013-01-01
We describe a statistical model to estimate the covariance matrix of matter tracer two-point correlation functions with cosmological simulations. Assuming a fixed number of cosmological simulation runs, we describe how to build a 'statistical emulator' of the two-point function covariance over a specified range of input cosmological parameters. Because the simulation runs with different cosmological models help to constrain the form of the covariance, we predict that the cosmology-dependent covariance may be estimated with a comparable number of simulations as would be needed to estimate the covariance for fixed cosmology. Our framework is a necessary first step in planning a simulations campaign for analyzing the next generation of cosmological surveys
Covariance descriptor fusion for target detection
Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih
2016-05-01
Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.
Slater, David; Ruef, Anne; Sanabria‐Diaz, Gretel; Preisig, Martin; Kherif, Ferath; Draganski, Bogdan; Lutti, Antoine
2017-01-01
Abstract Networks of anatomical covariance have been widely used to study connectivity patterns in both normal and pathological brains based on the concurrent changes of morphometric measures (i.e., cortical thickness) between brain structures across subjects (Evans, 2013). However, the existence of networks of microstructural changes within brain tissue has been largely unexplored so far. In this article, we studied in vivo the concurrent myelination processes among brain anatomical structures that gathered together emerge to form nonrandom networks. We name these “networks of myelin covariance” (Myelin‐Nets). The Myelin‐Nets were built from quantitative Magnetization Transfer data—an in‐vivo magnetic resonance imaging (MRI) marker of myelin content. The synchronicity of the variations in myelin content between anatomical regions was measured by computing the Pearson's correlation coefficient. We were especially interested in elucidating the effect of age on the topological organization of the Myelin‐Nets. We therefore selected two age groups: Young‐Age (20–31 years old) and Old‐Age (60–71 years old) and a pool of participants from 48 to 87 years old for a Myelin‐Nets aging trajectory study. We found that the topological organization of the Myelin‐Nets is strongly shaped by aging processes. The global myelin correlation strength, between homologous regions and locally in different brain lobes, showed a significant dependence on age. Interestingly, we also showed that the aging process modulates the resilience of the Myelin‐Nets to damage of principal network structures. In summary, this work sheds light on the organizational principles driving myelination and myelin degeneration in brain gray matter and how such patterns are modulated by aging. PMID:29271053
Phenotypic covariance at species' borders.
Caley, M Julian; Cripps, Edward; Game, Edward T
2013-05-28
Understanding the evolution of species limits is important in ecology, evolution, and conservation biology. Despite its likely importance in the evolution of these limits, little is known about phenotypic covariance in geographically marginal populations, and the degree to which it constrains, or facilitates, responses to selection. We investigated phenotypic covariance in morphological traits at species' borders by comparing phenotypic covariance matrices (P), including the degree of shared structure, the distribution of strengths of pair-wise correlations between traits, the degree of morphological integration of traits, and the ranks of matricies, between central and marginal populations of three species-pairs of coral reef fishes. Greater structural differences in P were observed between populations close to range margins and conspecific populations toward range centres, than between pairs of conspecific populations that were both more centrally located within their ranges. Approximately 80% of all pair-wise trait correlations within populations were greater in the north, but these differences were unrelated to the position of the sampled population with respect to the geographic range of the species. Neither the degree of morphological integration, nor ranks of P, indicated greater evolutionary constraint at range edges. Characteristics of P observed here provide no support for constraint contributing to the formation of these species' borders, but may instead reflect structural change in P caused by selection or drift, and their potential to evolve in the future.
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
Covariant representations of nuclear *-algebras
International Nuclear Information System (INIS)
Moore, S.M.
1978-01-01
Extensions of the Csup(*)-algebra theory for covariant representations to nuclear *-algebra are considered. Irreducible covariant representations are essentially unique, an invariant state produces a covariant representation with stable vacuum, and the usual relation between ergodic states and covariant representations holds. There exist construction and decomposition theorems and a possible relation between derivations and covariant representations
Covariant Noncommutative Field Theory
Energy Technology Data Exchange (ETDEWEB)
Estrada-Jimenez, S [Licenciaturas en Fisica y en Matematicas, Facultad de Ingenieria, Universidad Autonoma de Chiapas Calle 4a Ote. Nte. 1428, Tuxtla Gutierrez, Chiapas (Mexico); Garcia-Compean, H [Departamento de Fisica, Centro de Investigacion y de Estudios Avanzados del IPN P.O. Box 14-740, 07000 Mexico D.F., Mexico and Centro de Investigacion y de Estudios Avanzados del IPN, Unidad Monterrey Via del Conocimiento 201, Parque de Investigacion e Innovacion Tecnologica (PIIT) Autopista nueva al Aeropuerto km 9.5, Lote 1, Manzana 29, cp. 66600 Apodaca Nuevo Leon (Mexico); Obregon, O [Instituto de Fisica de la Universidad de Guanajuato P.O. Box E-143, 37150 Leon Gto. (Mexico); Ramirez, C [Facultad de Ciencias Fisico Matematicas, Universidad Autonoma de Puebla, P.O. Box 1364, 72000 Puebla (Mexico)
2008-07-02
The covariant approach to noncommutative field and gauge theories is revisited. In the process the formalism is applied to field theories invariant under diffeomorphisms. Local differentiable forms are defined in this context. The lagrangian and hamiltonian formalism is consistently introduced.
Covariant Noncommutative Field Theory
International Nuclear Information System (INIS)
Estrada-Jimenez, S.; Garcia-Compean, H.; Obregon, O.; Ramirez, C.
2008-01-01
The covariant approach to noncommutative field and gauge theories is revisited. In the process the formalism is applied to field theories invariant under diffeomorphisms. Local differentiable forms are defined in this context. The lagrangian and hamiltonian formalism is consistently introduced
Covariance data processing code. ERRORJ
International Nuclear Information System (INIS)
Kosako, Kazuaki
2001-01-01
The covariance data processing code, ERRORJ, was developed to process the covariance data of JENDL-3.2. ERRORJ has the processing functions of covariance data for cross sections including resonance parameters, angular distribution and energy distribution. (author)
Impacts of data covariances on the calculated breeding ratio for CRBRP
International Nuclear Information System (INIS)
Liaw, J.R.; Collins, P.J.; Henryson, H. II; Shenter, R.E.
1983-01-01
In order to establish confidence on the data adjustment methodology as applied to LMFBR design, and to estimate the importance of data correlations in that respect, an investigation was initiated on the impacts of data covariances on the calculated reactor performance parameters. This paper summarizes the results and findings of such an effort specifically related to the calculation of breeding ratio for CRBRP as an illustration. Thirty-nine integral parameters and their covariances, including k/sub eff/ and various capture and fission reaction rate ratios, from the ZEBRA-8 series and four ZPR physics benchmark assemblies were used in the least-squares fitting processes. Multigroup differential data and the sensitivity coefficients of those 39 integral parameters were generated by standard 2-D diffusion theory neutronic calculational modules at ANL. Three differential data covariance libraries, all based on ENDF/B-V evaluations, were tested in this study
Parametric number covariance in quantum chaotic spectra.
Vinayak; Kumar, Sandeep; Pandey, Akhilesh
2016-03-01
We study spectral parametric correlations in quantum chaotic systems and introduce the number covariance as a measure of such correlations. We derive analytic results for the classical random matrix ensembles using the binary correlation method and obtain compact expressions for the covariance. We illustrate the universality of this measure by presenting the spectral analysis of the quantum kicked rotors for the time-reversal invariant and time-reversal noninvariant cases. A local version of the parametric number variance introduced earlier is also investigated.
New perspective in covariance evaluation for nuclear data
International Nuclear Information System (INIS)
Kanda, Y.
1992-01-01
Methods of nuclear data evaluation have been highly developed during the past decade, especially after introducing the concept of covariance. This makes it utmost important how to evaluate covariance matrices for nuclear data. It can be said that covariance evaluation is just the nuclear data evaluation, because the covariance matrix has quantitatively decisive function in current evaluation methods. The covariance primarily represents experimental uncertainties. However, correlation of individual uncertainties between different data must be taken into account and it can not be conducted without detailed physical considerations on experimental conditions. This procedure depends on the evaluator and the estimated covariance does also. The mathematical properties of the covariance have been intensively discussed. Their physical properties should be studied to apply it to the nuclear data evaluation, and then, in this report, are reviewed to give the base for further development of the covariance application. (orig.)
Ohuakanwa, Chijioke Ephraim; Omeje, Joachim Chinweike; Eskay, Michael
2012-01-01
The study sought to investigate the relationship between pornography addiction and psychosocial and academic adjustment of students in universities in Lagos State. In order to achieve this objective, five research questions were formulated and two hypotheses postulated. The subjects for the study consisted of 616 full-time third-year undergraduate…
Brier, Matthew R; Mitra, Anish; McCarthy, John E; Ances, Beau M; Snyder, Abraham Z
2015-11-01
Functional connectivity refers to shared signals among brain regions and is typically assessed in a task free state. Functional connectivity commonly is quantified between signal pairs using Pearson correlation. However, resting-state fMRI is a multivariate process exhibiting a complicated covariance structure. Partial covariance assesses the unique variance shared between two brain regions excluding any widely shared variance, hence is appropriate for the analysis of multivariate fMRI datasets. However, calculation of partial covariance requires inversion of the covariance matrix, which, in most functional connectivity studies, is not invertible owing to rank deficiency. Here we apply Ledoit-Wolf shrinkage (L2 regularization) to invert the high dimensional BOLD covariance matrix. We investigate the network organization and brain-state dependence of partial covariance-based functional connectivity. Although RSNs are conventionally defined in terms of shared variance, removal of widely shared variance, surprisingly, improved the separation of RSNs in a spring embedded graphical model. This result suggests that pair-wise unique shared variance plays a heretofore unrecognized role in RSN covariance organization. In addition, application of partial correlation to fMRI data acquired in the eyes open vs. eyes closed states revealed focal changes in uniquely shared variance between the thalamus and visual cortices. This result suggests that partial correlation of resting state BOLD time series reflect functional processes in addition to structural connectivity. Copyright © 2015 Elsevier Inc. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Bourget, Antoine; Troost, Jan [Laboratoire de Physique Théorique, École Normale Supérieure, 24 rue Lhomond, 75005 Paris (France)
2016-03-23
We construct a covariant generating function for the spectrum of chiral primaries of symmetric orbifold conformal field theories with N=(4,4) supersymmetry in two dimensions. For seed target spaces K3 and T{sup 4}, the generating functions capture the SO(21) and SO(5) representation theoretic content of the chiral ring respectively. Via string dualities, we relate the transformation properties of the chiral ring under these isometries of the moduli space to the Lorentz covariance of perturbative string partition functions in flat space.
Dimension from covariance matrices.
Carroll, T L; Byers, J M
2017-02-01
We describe a method to estimate embedding dimension from a time series. This method includes an estimate of the probability that the dimension estimate is valid. Such validity estimates are not common in algorithms for calculating the properties of dynamical systems. The algorithm described here compares the eigenvalues of covariance matrices created from an embedded signal to the eigenvalues for a covariance matrix of a Gaussian random process with the same dimension and number of points. A statistical test gives the probability that the eigenvalues for the embedded signal did not come from the Gaussian random process.
Cheng, Fang; Meng, Ai-feng; Yang, Li-Fang; Zhang, Yi-nan
2013-07-01
A colostomy can have a negative impact on patient quality of life. Research suggests that psychosocial adaptation is positively associated with quality of life, but few reports address this adaptation and its related factors in patients with a permanent colostomy. A 4-month, descriptive study was conducted to assess the impact of ostomy knowledge and ability to self-care on the psychosocial adjustment of 54 Chinese outpatients (47 men, 14 participants 40 to 50 years old, 40 participants 50 to 70 years old) with a permanent colostomy to investigate the correlation between stoma knowledge, self-care ability, and psychosocial adjustment. Assessment instruments included a sociodemographic data questionnaire and a Chinese translation of the Ostomy Adjustment Inventory-23 that comprises 20 items in three domains (positive emotions, negative emotions, and social life). Participants rated statements on a scale from 0 (totally disagree) to 4 (totally agree); a score of 40 indicates a low level of psychosocial adjustment. Participants also completed the Stoma-related Knowledge Scale, comprising 14 5-point Likert scale questions where low scores indicate low knowledge, and they answered one question regarding self-care ability. Data were analyzed using statistical software for social science. The average stoma-related knowledge score suggested moderate levels of knowledge (45.112 ± 13.358). Twenty (20) participants managed all stoma care aspects independently, 30 required some assistance, and four (4) required care by someone else. The three domains of psychosocial adjustment scores (positive emotions, negative emotions, and social life) were 17.60 ± 4.093,12.92 ± 3.440, and 19.15 ± 6.316, respectively. Knowledge and the three domains of psychosocial adjustment were positively correlated with positive emotion (r = .610, P = 0.001), negative emotion (r = .696, P = 0.000), and social life adjustment (r = .617, P = 0.001). A significant difference in psychosocial adjustment
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.
Progress on Nuclear Data Covariances: AFCI-1.2 Covariance Library
International Nuclear Information System (INIS)
Oblozinsky, P.; Oblozinsky, P.; Mattoon, C.M.; Herman, M.; Mughabghab, S.F.; Pigni, M.T.; Talou, P.; Hale, G.M.; Kahler, A.C.; Kawano, T.; Little, R.C.; Young, P.G
2009-01-01
Improved neutron cross section covariances were produced for 110 materials including 12 light nuclei (coolants and moderators), 78 structural materials and fission products, and 20 actinides. Improved covariances were organized into AFCI-1.2 covariance library in 33-energy groups, from 10 -5 eV to 19.6 MeV. BNL contributed improved covariance data for the following materials: 23 Na and 55 Mn where more detailed evaluation was done; improvements in major structural materials 52 Cr, 56 Fe and 58 Ni; improved estimates for remaining structural materials and fission products; improved covariances for 14 minor actinides, and estimates of mubar covariances for 23 Na and 56 Fe. LANL contributed improved covariance data for 235 U and 239 Pu including prompt neutron fission spectra and completely new evaluation for 240 Pu. New R-matrix evaluation for 16 O including mubar covariances is under completion. BNL assembled the library and performed basic testing using improved procedures including inspection of uncertainty and correlation plots for each material. The AFCI-1.2 library was released to ANL and INL in August 2009.
Continuous Covariate Imbalance and Conditional Power for Clinical Trial Interim Analyses
Ciolino, Jody D.; Martin, Renee' H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.
2014-01-01
Oftentimes valid statistical analyses for clinical trials involve adjustment for known influential covariates, regardless of imbalance observed in these covariates at baseline across treatment groups. Thus, it must be the case that valid interim analyses also properly adjust for these covariates. There are situations, however, in which covariate adjustment is not possible, not planned, or simply carries less merit as it makes inferences less generalizable and less intuitive. In this case, covariate imbalance between treatment groups can have a substantial effect on both interim and final primary outcome analyses. This paper illustrates the effect of influential continuous baseline covariate imbalance on unadjusted conditional power (CP), and thus, on trial decisions based on futility stopping bounds. The robustness of the relationship is illustrated for normal, skewed, and bimodal continuous baseline covariates that are related to a normally distributed primary outcome. Results suggest that unadjusted CP calculations in the presence of influential covariate imbalance require careful interpretation and evaluation. PMID:24607294
Pfeiffer, Christine M.; Sternberg, Maya R.; Schleicher, Rosemary L.; Rybak, Michael E.
2016-01-01
Biochemical indicators of water-soluble vitamin (WSV) status have been measured in a nationally representative sample of the US population in NHANES 2003–2006. To examine whether demographic differentials in nutritional status were related to and confounded by certain variables, we assessed the association of sociodemographic (age, sex, race-ethnicity, education, income) and lifestyle variables (dietary supplement use, smoking, alcohol consumption, BMI, physical activity) with biomarkers of WSV status in adults (≥20 y): serum and RBC folate, serum pyridoxal-5′-phosphate (PLP), serum 4-pyridoxic acid, serum total cobalamin (B-12), plasma total homocysteine (tHcy), plasma methylmalonic acid (MMA), and serum ascorbic acid. Age (except for PLP) and smoking (except for MMA) were generally the strongest significant correlates of these biomarkers (|r| ≤0.43) and together with supplement use explained more of the variability as compared to the other covariates in bivariate analysis. In multiple regression models, sociodemographic and lifestyle variables together explained from 7% (B-12) to 29% (tHcy) of the biomarker variability. We observed significant associations for most biomarkers (≥6 out of 8) with age, sex, race-ethnicity, supplement use, smoking, and BMI; and for some biomarkers with PIR (5/8), education (1/8), alcohol consumption (4/8), and physical activity (5/8). We noted large estimated percent changes in biomarker concentrations between race-ethnic groups (from −24% to 20%), between supplement users and nonusers (from −12% to 104%), and between smokers and nonsmokers (from −28% to 8%). In summary, age, sex, and race-ethnic differentials in biomarker concentrations remained significant after adjusting for sociodemographic and lifestyle variables. Supplement use and smoking were important correlates of biomarkers of WSV status. PMID:23576641
Pfeiffer, Christine M; Sternberg, Maya R; Schleicher, Rosemary L; Rybak, Michael E
2013-06-01
Biochemical indicators of water-soluble vitamin (WSV) status were measured in a nationally representative sample of the U.S. population in NHANES 2003-2006. To examine whether demographic differentials in nutritional status were related to and confounded by certain variables, we assessed the association of sociodemographic (age, sex, race-ethnicity, education, income) and lifestyle (dietary supplement use, smoking, alcohol consumption, BMI, physical activity) variables with biomarkers of WSV status in adults (aged ≥ 20 y): serum and RBC folate, serum pyridoxal-5'-phosphate (PLP), serum 4-pyridoxic acid, serum total cobalamin (vitamin B-12), plasma total homocysteine (tHcy), plasma methylmalonic acid (MMA), and serum ascorbic acid. Age (except for PLP) and smoking (except for MMA) were generally the strongest significant correlates of these biomarkers (|r| ≤ 0.43) and together with supplement use explained more of the variability compared with the other covariates in bivariate analysis. In multiple regression models, sociodemographic and lifestyle variables together explained from 7 (vitamin B-12) to 29% (tHcy) of the biomarker variability. We observed significant associations for most biomarkers (≥ 6 of 8) with age, sex, race-ethnicity, supplement use, smoking, and BMI and for some biomarkers with PIR (5 of 8), education (1 of 8), alcohol consumption (4 of 8), and physical activity (5 of 8). We noted large estimated percentage changes in biomarker concentrations between race-ethnic groups (from -24 to 20%), between supplement users and nonusers (from -12 to 104%), and between smokers and nonsmokers (from -28 to 8%). In summary, age, sex, and race-ethnic differentials in biomarker concentrations remained significant after adjusting for sociodemographic and lifestyle variables. Supplement use and smoking were important correlates of biomarkers of WSV status.
International Nuclear Information System (INIS)
Zaberi, B.F.; Riaz, M.F.; Sultan, B.A.; Gobindram, P.
2007-01-01
To determine the correlation of ABRI with treatment intervention and outcome as discharged or expired in patients of acute variceal bleed. Records of all the patients admitted in Medical Unit-IV, Civil Hospital Karachi with acute variceal bleeding during January 2004 to October 2006 were retrieved. Use of vasoactive agents (Terlipressin/Octreotide), endoscopic band ligation (EBL) and outcome (Discharged/Expired) were noted. ABRI was calculated by the following formula. ABRI= Blood Units Transfused/((Final Hematocrit-Initial Hematocrit)+0.01) Mean ABRI were compared by student's 't' test according to vasoactive therapy, EBL and outcome. Correlation of ABRI with the same variables was also studied by plotting Receiver Operative Curves (ROC). Seventy six patients fulfilling inclusion criteria were selected. No statistically significant difference was observed in the mean ABRI scores when compared according to vasoactive drug administration, EBL and outcome. Significant correlation with mortality was seen on ROC plot with significantly larger area under the curve. (author)
Covariant field equations in supergravity
Energy Technology Data Exchange (ETDEWEB)
Vanhecke, Bram [KU Leuven, Institute for Theoretical Physics, Leuven (Belgium); Ghent University, Faculty of Physics, Gent (Belgium); Proeyen, Antoine van [KU Leuven, Institute for Theoretical Physics, Leuven (Belgium)
2017-12-15
Covariance is a useful property for handling supergravity theories. In this paper, we prove a covariance property of supergravity field equations: under reasonable conditions, field equations of supergravity are covariant modulo other field equations. We prove that for any supergravity there exist such covariant equations of motion, other than the regular equations of motion, that are equivalent to the latter. The relations that we find between field equations and their covariant form can be used to obtain multiplets of field equations. In practice, the covariant field equations are easily found by simply covariantizing the ordinary field equations. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Covariant field equations in supergravity
International Nuclear Information System (INIS)
Vanhecke, Bram; Proeyen, Antoine van
2017-01-01
Covariance is a useful property for handling supergravity theories. In this paper, we prove a covariance property of supergravity field equations: under reasonable conditions, field equations of supergravity are covariant modulo other field equations. We prove that for any supergravity there exist such covariant equations of motion, other than the regular equations of motion, that are equivalent to the latter. The relations that we find between field equations and their covariant form can be used to obtain multiplets of field equations. In practice, the covariant field equations are easily found by simply covariantizing the ordinary field equations. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Generally covariant gauge theories
International Nuclear Information System (INIS)
Capovilla, R.
1992-01-01
A new class of generally covariant gauge theories in four space-time dimensions is investigated. The field variables are taken to be a Lie algebra valued connection 1-form and a scalar density. Modulo an important degeneracy, complex [euclidean] vacuum general relativity corresponds to a special case in this class. A canonical analysis of the generally covariant gauge theories with the same gauge group as general relativity shows that they describe two degrees of freedom per space point, qualifying therefore as a new set of neighbors of general relativity. The modification of the algebra of the constraints with respect to the general relativity case is computed; this is used in addressing the question of how general relativity stands out from its neighbors. (orig.)
The Bayesian Covariance Lasso.
Khondker, Zakaria S; Zhu, Hongtu; Chu, Haitao; Lin, Weili; Ibrahim, Joseph G
2013-04-01
Estimation of sparse covariance matrices and their inverse subject to positive definiteness constraints has drawn a lot of attention in recent years. The abundance of high-dimensional data, where the sample size ( n ) is less than the dimension ( d ), requires shrinkage estimation methods since the maximum likelihood estimator is not positive definite in this case. Furthermore, when n is larger than d but not sufficiently larger, shrinkage estimation is more stable than maximum likelihood as it reduces the condition number of the precision matrix. Frequentist methods have utilized penalized likelihood methods, whereas Bayesian approaches rely on matrix decompositions or Wishart priors for shrinkage. In this paper we propose a new method, called the Bayesian Covariance Lasso (BCLASSO), for the shrinkage estimation of a precision (covariance) matrix. We consider a class of priors for the precision matrix that leads to the popular frequentist penalties as special cases, develop a Bayes estimator for the precision matrix, and propose an efficient sampling scheme that does not precalculate boundaries for positive definiteness. The proposed method is permutation invariant and performs shrinkage and estimation simultaneously for non-full rank data. Simulations show that the proposed BCLASSO performs similarly as frequentist methods for non-full rank data.
Lorentz Covariance of Langevin Equation
International Nuclear Information System (INIS)
Koide, T.; Denicol, G.S.; Kodama, T.
2008-01-01
Relativistic covariance of a Langevin type equation is discussed. The requirement of Lorentz invariance generates an entanglement between the force and noise terms so that the noise itself should not be a covariant quantity. (author)
Markovic, Andrea; Bowker, Julie C
2015-01-01
A social surrogate is an individual who offers help and comfort in social situations or makes social events more exciting. In this study of 157 young adolescents (55% female; Mage = 13.84 years, SD = 0.75 years), the authors examined whether the linear and curvilinear associations between self-reported social surrogate use and adjustment outcomes (social problems, loneliness, anxiety symptoms, depressive symptoms) varied as a function of shyness and gender, after accounting for the effects of positive friendship quality. Regression analyses revealed that low and high levels of social surrogate use were related to greater social problems for all adolescents. In addition, shyness emerged as a moderator for several curvilinear effects. Specifically, results indicated that (a) high levels of social surrogate use were associated with greater anxiety for adolescents high in shyness; and (b) low levels of social surrogate use were associated with greater depressive symptoms for adolescents low in shyness. Findings highlight the developmental importance of specific types of relationship experiences during early adolescence and point to different implications of social surrogate use for shy and non-shy young adolescents.
A New Approach for Nuclear Data Covariance and Sensitivity Generation
International Nuclear Information System (INIS)
Leal, L.C.; Larson, N.M.; Derrien, H.; Kawano, T.; Chadwick, M.B.
2005-01-01
Covariance data are required to correctly assess uncertainties in design parameters in nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the U.S. Evaluated Nuclear Data File, ENDF/B. The uncertainty files in the ENDF/B library are obtained from the analysis of experimental data and are stored as variance and covariance data. The computer code SAMMY is used in the analysis of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on generalized least-squares formalism (Bayes' theory) together with the resonance formalism described by R-matrix theory. Two approaches are used in SAMMY for the generation of resonance-parameter covariance data. In the evaluation process SAMMY generates a set of resonance parameters that fit the data, and, in addition, it also provides the resonance-parameter covariances. For existing resonance-parameter evaluations where no resonance-parameter covariance data are available, the alternative is to use an approach called the 'retroactive' resonance-parameter covariance generation. In the high-energy region the methodology for generating covariance data consists of least-squares fitting and model parameter adjustment. The least-squares fitting method calculates covariances directly from experimental data. The parameter adjustment method employs a nuclear model calculation such as the optical model and the Hauser-Feshbach model, and estimates a covariance for the nuclear model parameters. In this paper we describe the application of the retroactive method and the parameter adjustment method to generate covariance data for the gadolinium isotopes
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.
Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data
International Nuclear Information System (INIS)
Jun, Sung C; Plis, Sergey M; Ranken, Doug M; Schmidt, David M
2006-01-01
The performance of parametric magnetoencephalography (MEG) and electroencephalography (EEG) source localization approaches can be degraded by the use of poor background noise covariance estimates. In general, estimation of the noise covariance for spatiotemporal analysis is difficult mainly due to the limited noise information available. Furthermore, its estimation requires a large amount of storage and a one-time but very large (and sometimes intractable) calculation or its inverse. To overcome these difficulties, noise covariance models consisting of one pair or a sum of multi-pairs of Kronecker products of spatial covariance and temporal covariance have been proposed. However, these approaches cannot be applied when the noise information is very limited, i.e., the amount of noise information is less than the degrees of freedom of the noise covariance models. A common example of this is when only averaged noise data are available for a limited prestimulus region (typically at most a few hundred milliseconds duration). For such cases, a diagonal spatiotemporal noise covariance model consisting of sensor variances with no spatial or temporal correlation has been the common choice for spatiotemporal analysis. In this work, we propose a different noise covariance model which consists of diagonal spatial noise covariance and Toeplitz temporal noise covariance. It can easily be estimated from limited noise information, and no time-consuming optimization and data-processing are required. Thus, it can be used as an alternative choice when one-pair or multi-pair noise covariance models cannot be estimated due to lack of noise information. To verify its capability we used Bayesian inference dipole analysis and a number of simulated and empirical datasets. We compared this covariance model with other existing covariance models such as conventional diagonal covariance, one-pair and multi-pair noise covariance models, when noise information is sufficient to estimate them. We
A Covariance Generation Methodology for Fission Product Yields
Directory of Open Access Journals (Sweden)
Terranova N.
2016-01-01
Full Text Available Recent safety and economical concerns for modern nuclear reactor applications have fed an outstanding interest in basic nuclear data evaluation improvement and completion. It has been immediately clear that the accuracy of our predictive simulation models was strongly affected by our knowledge on input data. Therefore strong efforts have been made to improve nuclear data and to generate complete and reliable uncertainty information able to yield proper uncertainty propagation on integral reactor parameters. Since in modern nuclear data banks (such as JEFF-3.1.1 and ENDF/BVII.1 no correlations for fission yields are given, in the present work we propose a covariance generation methodology for fission product yields. The main goal is to reproduce the existing European library and to add covariance information to allow proper uncertainty propagation in depletion and decay heat calculations. To do so, we adopted the Generalized Least Square Method (GLSM implemented in CONRAD (COde for Nuclear Reaction Analysis and Data assimilation, developed at CEA-Cadarache. Theoretical values employed in the Bayesian parameter adjustment are delivered thanks to a convolution of different models, representing several quantities in fission yield calculations: the Brosa fission modes for pre-neutron mass distribution, a simplified Gaussian model for prompt neutron emission probability, theWahl systematics for charge distribution and the Madland-England model for the isomeric ratio. Some results will be presented for the thermal fission of U-235, Pu-239 and Pu-241.
Contributions to Large Covariance and Inverse Covariance Matrices Estimation
Kang, Xiaoning
2016-01-01
Estimation of covariance matrix and its inverse is of great importance in multivariate statistics with broad applications such as dimension reduction, portfolio optimization, linear discriminant analysis and gene expression analysis. However, accurate estimation of covariance or inverse covariance matrices is challenging due to the positive definiteness constraint and large number of parameters, especially in the high-dimensional cases. In this thesis, I develop several approaches for estimat...
Nuclear data covariances in the Indian context
International Nuclear Information System (INIS)
Ganesan, S.
2014-01-01
The topic of covariances is recognized as an important part of several ongoing nuclear data science activities, since 2007, in the Nuclear Data Physics Centre of India (NDPCI). A Phase-1 project in collaboration with the Statistics department in Manipal University, Karnataka (Prof. K.M. Prasad and Prof. S. Nair) on nuclear data covariances was executed successfully during 2007-2011 period. In Phase-I, the NDPCI has conducted three national Theme meetings sponsored by the DAE-BRNS in 2008, 2010 and 2013 on nuclear data covariances. In Phase-1, the emphasis was on a thorough basic understanding of the concept of covariances including assigning uncertainties to experimental data in terms of partial errors and micro correlations, through a study and a detailed discussion of open literature. Towards the end of Phase-1, measurements and a first time covariance analysis of cross-sections for 58 Ni (n, p) 58 Co reaction measured in Mumbai Pelletron accelerator using 7 Li (p,n) reactions as neutron source in the MeV energy region were performed under a PhD programme on nuclear data covariances in which enrolled are two students, Shri B.S. Shivashankar and Ms. Shanti Sheela. India is also successfully evolving a team of young researchers to code nuclear data of uncertainties, with the perspectives on covariances, in the IAEA-EXFOR format. A Phase-II DAE-BRNS-NDPCI proposal of project at Manipal has been submitted and the proposal is undergoing a peer-review at this time. In Phase-2, modern nuclear data evaluation techniques that including covariances will be further studied as a research and development effort, as a first time effort. These efforts include the use of techniques such as that of the Kalman filter. Presently, a 48 hours lecture series on treatment of errors and their propagation is being formulated under auspices of the Homi Bhabha National Institute. The talk describes the progress achieved thus far in the learning curve of the above-mentioned and exciting
International Nuclear Information System (INIS)
Ginelli, Francesco; Politi, Antonio; Chaté, Hugues; Livi, Roberto
2013-01-01
Recent years have witnessed a growing interest in covariant Lyapunov vectors (CLVs) which span local intrinsic directions in the phase space of chaotic systems. Here, we review the basic results of ergodic theory, with a specific reference to the implications of Oseledets’ theorem for the properties of the CLVs. We then present a detailed description of a ‘dynamical’ algorithm to compute the CLVs and show that it generically converges exponentially in time. We also discuss its numerical performance and compare it with other algorithms presented in the literature. We finally illustrate how CLVs can be used to quantify deviations from hyperbolicity with reference to a dissipative system (a chain of Hénon maps) and a Hamiltonian model (a Fermi–Pasta–Ulam chain). This article is part of a special issue of Journal of Physics A: Mathematical and Theoretical devoted to ‘Lyapunov analysis: from dynamical systems theory to applications’. (paper)
Deriving covariant holographic entanglement
Energy Technology Data Exchange (ETDEWEB)
Dong, Xi [School of Natural Sciences, Institute for Advanced Study, Princeton, NJ 08540 (United States); Lewkowycz, Aitor [Jadwin Hall, Princeton University, Princeton, NJ 08544 (United States); Rangamani, Mukund [Center for Quantum Mathematics and Physics (QMAP), Department of Physics, University of California, Davis, CA 95616 (United States)
2016-11-07
We provide a gravitational argument in favour of the covariant holographic entanglement entropy proposal. In general time-dependent states, the proposal asserts that the entanglement entropy of a region in the boundary field theory is given by a quarter of the area of a bulk extremal surface in Planck units. The main element of our discussion is an implementation of an appropriate Schwinger-Keldysh contour to obtain the reduced density matrix (and its powers) of a given region, as is relevant for the replica construction. We map this contour into the bulk gravitational theory, and argue that the saddle point solutions of these replica geometries lead to a consistent prescription for computing the field theory Rényi entropies. In the limiting case where the replica index is taken to unity, a local analysis suffices to show that these saddles lead to the extremal surfaces of interest. We also comment on various properties of holographic entanglement that follow from this construction.
Nonparametric Bayesian models for a spatial covariance.
Reich, Brian J; Fuentes, Montserrat
2012-01-01
A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.
An Information-Theoretic Justification for Covariance Intersectionand Its Generalization
National Research Council Canada - National Science Library
Hurley, Michael
2001-01-01
.... that addresses the problems that arise from fusing correlated measurements. The researchers have named this technique 'covariance intersection' and have presented papers on it at several robotics and control theory conferences...
General Galilei Covariant Gaussian Maps
Gasbarri, Giulio; Toroš, Marko; Bassi, Angelo
2017-09-01
We characterize general non-Markovian Gaussian maps which are covariant under Galilean transformations. In particular, we consider translational and Galilean covariant maps and show that they reduce to the known Holevo result in the Markovian limit. We apply the results to discuss measures of macroscopicity based on classicalization maps, specifically addressing dissipation, Galilean covariance and non-Markovianity. We further suggest a possible generalization of the macroscopicity measure defined by Nimmrichter and Hornberger [Phys. Rev. Lett. 110, 16 (2013)].
A Generalized Autocovariance Least-Squares Method for Covariance Estimation
DEFF Research Database (Denmark)
Åkesson, Bernt Magnus; Jørgensen, John Bagterp; Poulsen, Niels Kjølstad
2007-01-01
A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter.......A generalization of the autocovariance least- squares method for estimating noise covariances is presented. The method can estimate mutually correlated system and sensor noise and can be used with both the predicting and the filtering form of the Kalman filter....
Adjustment of the 235U Fission Spectrum
International Nuclear Information System (INIS)
GRIFFIN, PATRICK J.; WILLIAMS, J.G.
1999-01-01
The latest nuclear data are used to examine the sensitivity of the least squares adjustment of the 235 U fission spectrum to the measured reaction rates, dosimetry cross sections, and prior spectrum covariance matrix. All of these parameters were found to be very important in the spectrum adjustment. The most significant deficiency in the nuclear data is the absence of a good prior covariance matrix. Covariance matrices generated from analytic models of the fission spectra have been used in the past. This analysis reveals some unusual features in the covariance matrix produced with this approach. Specific needs are identified for improved nuclear data to better determine the 235 U spectrum. An improved 235 U covariance matrix and adjusted spectrum are recommended for use in radiation transport sensitivity analyses
How much do genetic covariances alter the rate of adaptation?
Agrawal, Aneil F; Stinchcombe, John R
2009-03-22
Genetically correlated traits do not evolve independently, and the covariances between traits affect the rate at which a population adapts to a specified selection regime. To measure the impact of genetic covariances on the rate of adaptation, we compare the rate fitness increases given the observed G matrix to the expected rate if all the covariances in the G matrix are set to zero. Using data from the literature, we estimate the effect of genetic covariances in real populations. We find no net tendency for covariances to constrain the rate of adaptation, though the quality and heterogeneity of the data limit the certainty of this result. There are some examples in which covariances strongly constrain the rate of adaptation but these are balanced by counter examples in which covariances facilitate the rate of adaptation; in many cases, covariances have little or no effect. We also discuss how our metric can be used to identify traits or suites of traits whose genetic covariances to other traits have a particularly large impact on the rate of adaptation.
Cross-population myelination covariance of human cerebral cortex.
Ma, Zhiwei; Zhang, Nanyin
2017-09-01
Cross-population covariance of brain morphometric quantities provides a measure of interareal connectivity, as it is believed to be determined by the coordinated neurodevelopment of connected brain regions. Although useful, structural covariance analysis predominantly employed bulky morphological measures with mixed compartments, whereas studies of the structural covariance of any specific subdivisions such as myelin are rare. Characterizing myelination covariance is of interest, as it will reveal connectivity patterns determined by coordinated development of myeloarchitecture between brain regions. Using myelin content MRI maps from the Human Connectome Project, here we showed that the cortical myelination covariance was highly reproducible, and exhibited a brain organization similar to that previously revealed by other connectivity measures. Additionally, the myelination covariance network shared common topological features of human brain networks such as small-worldness. Furthermore, we found that the correlation between myelination covariance and resting-state functional connectivity (RSFC) was uniform within each resting-state network (RSN), but could considerably vary across RSNs. Interestingly, this myelination covariance-RSFC correlation was appreciably stronger in sensory and motor networks than cognitive and polymodal association networks, possibly due to their different circuitry structures. This study has established a new brain connectivity measure specifically related to axons, and this measure can be valuable to investigating coordinated myeloarchitecture development. Hum Brain Mapp 38:4730-4743, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Covariant electromagnetic field lines
Hadad, Y.; Cohen, E.; Kaminer, I.; Elitzur, A. C.
2017-08-01
Faraday introduced electric field lines as a powerful tool for understanding the electric force, and these field lines are still used today in classrooms and textbooks teaching the basics of electromagnetism within the electrostatic limit. However, despite attempts at generalizing this concept beyond the electrostatic limit, such a fully relativistic field line theory still appears to be missing. In this work, we propose such a theory and define covariant electromagnetic field lines that naturally extend electric field lines to relativistic systems and general electromagnetic fields. We derive a closed-form formula for the field lines curvature in the vicinity of a charge, and show that it is related to the world line of the charge. This demonstrates how the kinematics of a charge can be derived from the geometry of the electromagnetic field lines. Such a theory may also provide new tools in modeling and analyzing electromagnetic phenomena, and may entail new insights regarding long-standing problems such as radiation-reaction and self-force. In particular, the electromagnetic field lines curvature has the attractive property of being non-singular everywhere, thus eliminating all self-field singularities without using renormalization techniques.
Covariation in Natural Causal Induction.
Cheng, Patricia W.; Novick, Laura R.
1991-01-01
Biases and models usually offered by cognitive and social psychology and by philosophy to explain causal induction are evaluated with respect to focal sets (contextually determined sets of events over which covariation is computed). A probabilistic contrast model is proposed as underlying covariation computation in natural causal induction. (SLD)
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.
Covariance Manipulation for Conjunction Assessment
Hejduk, M. D.
2016-01-01
The manipulation of space object covariances to try to provide additional or improved information to conjunction risk assessment is not an uncommon practice. Types of manipulation include fabricating a covariance when it is missing or unreliable to force the probability of collision (Pc) to a maximum value ('PcMax'), scaling a covariance to try to improve its realism or see the effect of covariance volatility on the calculated Pc, and constructing the equivalent of an epoch covariance at a convenient future point in the event ('covariance forecasting'). In bringing these methods to bear for Conjunction Assessment (CA) operations, however, some do not remain fully consistent with best practices for conducting risk management, some seem to be of relatively low utility, and some require additional information before they can contribute fully to risk analysis. This study describes some basic principles of modern risk management (following the Kaplan construct) and then examines the PcMax and covariance forecasting paradigms for alignment with these principles; it then further examines the expected utility of these methods in the modern CA framework. Both paradigms are found to be not without utility, but only in situations that are somewhat carefully circumscribed.
Using machine learning to assess covariate balance in matching studies.
Linden, Ariel; Yarnold, Paul R
2016-12-01
In order to assess the effectiveness of matching approaches in observational studies, investigators typically present summary statistics for each observed pre-intervention covariate, with the objective of showing that matching reduces the difference in means (or proportions) between groups to as close to zero as possible. In this paper, we introduce a new approach to distinguish between study groups based on their distributions of the covariates using a machine-learning algorithm called optimal discriminant analysis (ODA). Assessing covariate balance using ODA as compared with the conventional method has several key advantages: the ability to ascertain how individuals self-select based on optimal (maximum-accuracy) cut-points on the covariates; the application to any variable metric and number of groups; its insensitivity to skewed data or outliers; and the use of accuracy measures that can be widely applied to all analyses. Moreover, ODA accepts analytic weights, thereby extending the assessment of covariate balance to any study design where weights are used for covariate adjustment. By comparing the two approaches using empirical data, we are able to demonstrate that using measures of classification accuracy as balance diagnostics produces highly consistent results to those obtained via the conventional approach (in our matched-pairs example, ODA revealed a weak statistically significant relationship not detected by the conventional approach). Thus, investigators should consider ODA as a robust complement, or perhaps alternative, to the conventional approach for assessing covariate balance in matching studies. © 2016 John Wiley & Sons, Ltd.
Covariance matrices of experimental data
International Nuclear Information System (INIS)
Perey, F.G.
1978-01-01
A complete statement of the uncertainties in data is given by its covariance matrix. It is shown how the covariance matrix of data can be generated using the information available to obtain their standard deviations. Determination of resonance energies by the time-of-flight method is used as an example. The procedure for combining data when the covariance matrix is non-diagonal is given. The method is illustrated by means of examples taken from the recent literature to obtain an estimate of the energy of the first resonance in carbon and for five resonances of 238 U
Evaluation and processing of covariance data
International Nuclear Information System (INIS)
Wagner, M.
1993-01-01
These proceedings of a specialists'meeting on evaluation and processing of covariance data is divided into 4 parts bearing on: part 1- Needs for evaluated covariance data (2 Papers), part 2- generation of covariance data (15 Papers), part 3- Processing of covariance files (2 Papers), part 4-Experience in the use of evaluated covariance data (2 Papers)
Galaxy-galaxy lensing estimators and their covariance properties
Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uroš; Slosar, Anže; Vazquez Gonzalez, Jose
2017-11-01
We study the covariance properties of real space correlation function estimators - primarily galaxy-shear correlations, or galaxy-galaxy lensing - using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.
Galaxy–galaxy lensing estimators and their covariance properties
International Nuclear Information System (INIS)
Singh, Sukhdeep; Mandelbaum, Rachel; Seljak, Uros; Slosar, Anze; Gonzalez, Jose Vazquez
2017-01-01
Here, we study the covariance properties of real space correlation function estimators – primarily galaxy–shear correlations, or galaxy–galaxy lensing – using SDSS data for both shear catalogues and lenses (specifically the BOSS LOWZ sample). Using mock catalogues of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the lens density field instead of the lens overdensity field. While the measurement using the lens density field is unbiased (in the absence of systematics), its error is significantly larger due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the overdensity, we find that the errors are dominated by the shape noise and lens clustering, which empirically estimated covariances (jackknife and standard deviation across mocks) that are consistent with theoretical estimates, and that both the connected parts of the four-point function and the supersample covariance can be neglected for the current levels of noise. While the trade-off between different terms in the covariance depends on the survey configuration (area, source number density), the diagnostics that we use in this work should be useful for future works to test their empirically determined covariances.
The utility of covariance of combining ability in plant breeding.
Arunachalam, V
1976-11-01
The definition of covariances of half- and full sibs, and hence that of variances of general and specific combining ability with regard to a quantitative character, is extended to take into account the respective covariances between a pair of characters. The interpretation of the dispersion and correlation matrices of general and specific combining ability is discussed by considering a set of single, three- and four-way crosses, made using diallel and line × tester mating systems in Pennisetum typhoides. The general implications of the concept of covariance of combining ability in plant breeding are discussed.
On Galilean covariant quantum mechanics
International Nuclear Information System (INIS)
Horzela, A.; Kapuscik, E.; Kempczynski, J.; Joint Inst. for Nuclear Research, Dubna
1991-08-01
Formalism exhibiting the Galilean covariance of wave mechanics is proposed. A new notion of quantum mechanical forces is introduced. The formalism is illustrated on the example of the harmonic oscillator. (author)
International Nuclear Information System (INIS)
Mahdid, M.
2014-01-01
In order to investigate the responses of leaf elongation rate (LER), turgor and osmotic adjustment (OA) during a short-term stress (7 hours) imposed by PEG6000 and a recovery phase, three durum wheat (Triticum durum L.) varieties (Inrat; MBB; and OZ ) were grown in aerated nutrient solutions. Leaf elongation kinetics of leaf 3 was estimated using LVDT. Turgor was estimated using a cell pressure probe; osmotic potential as well as total sugars and potassium (K+) concentrations were estimated from expressed sap of elongation zone. Growth recovered rapidly and then stabilised at a lower value. A significant difference was found in % recovery of LER between the varieties. The cessation of growth after stress coincided with a decrease in turgor followed by a recovery period reaching control values in MBB and Inrat. A strong correlation (R2 = 0.83) between the reduction in turgor (turgor) and % recovery of LER was found at 7 hours after stress. The difference in the partial recovery of LER between varieties was thus related to the capacity of partial turgor recovery. Partial turgor recovery is associated with sugar or K+ based OA which indicates its importance in maintaining high LER values under water deficit. (author)
Co-variations of Cholera with Climatic and Environmental ...
African Journals Online (AJOL)
Significant co-variations were found between seasonally adjusted cases and coastal ocean chlorophyll a and to some degree sea surface temperature, both lagged by one to four months. Cholera cases in Dar es Salaam were also weakly related to the Indian Ocean Dipole Mode Index lagged by 5 months, suggesting that it ...
DEFF Research Database (Denmark)
M. Gaspar, Raquel; Murgoci, Agatha
2010-01-01
A convexity adjustment (or convexity correction) in fixed income markets arises when one uses prices of standard (plain vanilla) products plus an adjustment to price nonstandard products. We explain the basic and appealing idea behind the use of convexity adjustments and focus on the situations...
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).
Needs for evaluated covariance data for reactor pressure vessel dosimetry
International Nuclear Information System (INIS)
Maerker, R.E.; Broadhead, B.L.; Wagschal, J.J.
1992-01-01
This report discusses new methodology for quantifying and then reducing uncertainties in the calculated pressure vessel fluences of a pressurized water reactor (PWR). The technique involves combining the integral results of the calculated and measured PWR surveillance dosimetry activities with the differential data used in the calculations, along with covariances of all the quantities, into a generalized linear least-squares adjustment procedure. Based on analysis of both PWRs and test reactor benchmarks, substantial evidence now exists to support the conclusion that, of all the nuclear as well as non-nuclear differential data considered, ENDF/B-VI values of the total inelastic iron cross sections and their covariances are the most important data controlling the outcome of the adjustment procedure. Predicted adjustments in these cross sections provided the stimulus for new measurements, the results of which impacted the ENDF/B-VI evaluation of iron 56
Covariance NMR Processing and Analysis for Protein Assignment.
Harden, Bradley J; Frueh, Dominique P
2018-01-01
During NMR resonance assignment it is often necessary to relate nuclei to one another indirectly, through their common correlations to other nuclei. Covariance NMR has emerged as a powerful technique to correlate such nuclei without relying on error-prone peak peaking. However, false-positive artifacts in covariance spectra have impeded a general application to proteins. We recently introduced pre- and postprocessing steps to reduce the prevalence of artifacts in covariance spectra, allowing for the calculation of a variety of 4D covariance maps obtained from diverse combinations of pairs of 3D spectra, and we have employed them to assign backbone and sidechain resonances in two large and challenging proteins. In this chapter, we present a detailed protocol describing how to (1) properly prepare existing 3D spectra for covariance, (2) understand and apply our processing script, and (3) navigate and interpret the resulting 4D spectra. We also provide solutions to a number of errors that may occur when using our script, and we offer practical advice when assigning difficult signals. We believe such 4D spectra, and covariance NMR in general, can play an integral role in the assignment of NMR signals.
GLq(N)-covariant quantum algebras and covariant differential calculus
International Nuclear Information System (INIS)
Isaev, A.P.; Pyatov, P.N.
1992-01-01
GL q (N)-covariant quantum algebras with generators satisfying quadratic polynomial relations are considered. It is that, up to some innessential arbitrariness, there are only two kinds of such quantum algebras, namely, the algebras with q-deformed commutation and q-deformed anticommutation relations. 25 refs
GLq(N)-covariant quantum algebras and covariant differential calculus
International Nuclear Information System (INIS)
Isaev, A.P.; Pyatov, P.N.
1993-01-01
We consider GL q (N)-covariant quantum algebras with generators satisfying quadratic polynomial relations. We show that, up to some inessential arbitrariness, there are only two kinds of such quantum algebras, namely, the algebras with q-deformed commutation and q-deformed anticommutation relations. The connection with the bicovariant differential calculus on the linear quantum groups is discussed. (orig.)
Cosmic censorship conjecture revisited: covariantly
International Nuclear Information System (INIS)
Hamid, Aymen I M; Goswami, Rituparno; Maharaj, Sunil D
2014-01-01
In this paper we study the dynamics of the trapped region using a frame independent semi-tetrad covariant formalism for general locally rotationally symmetric (LRS) class II spacetimes. We covariantly prove some important geometrical results for the apparent horizon, and state the necessary and sufficient conditions for a singularity to be locally naked. These conditions bring out, for the first time in a quantitative and transparent manner, the importance of the Weyl curvature in deforming and delaying the trapped region during continual gravitational collapse, making the central singularity locally visible. (paper)
On the a priori estimation of collocation error covariance functions: a feasibility study
DEFF Research Database (Denmark)
Arabelos, D.N.; Forsberg, René; Tscherning, C.C.
2007-01-01
and the associated error covariance functions were conducted in the Arctic region north of 64 degrees latitude. The correlation between the known features of the data and the parameters variance and correlation length of the computed error covariance functions was estimated using multiple regression analysis...
MATXTST, Basic Operations for Covariance Matrices
International Nuclear Information System (INIS)
Geraldo, Luiz P.; Smith, Donald
1989-01-01
1 - Description of program or function: MATXTST and MATXTST1 perform the following operations for a covariance matrix: - test for singularity; - test for positive definiteness; - compute the inverse if the matrix is non-singular; - compute the determinant; - determine the number of positive, negative, and zero eigenvalues; - examine all possible 3 X 3 cross correlations within a sub-matrix corresponding to a leading principal minor which is non-positive definite. While the two programs utilize the same input, the calculational procedures employed are somewhat different and their functions are complementary. The available input options include: i) the full covariance matrix, ii) the basic variables plus the relative covariance matrix, or iii) uncertainties in the basic variables plus the correlation matrix. 2 - Method of solution: MATXTST employs LINPACK subroutines SPOFA and SPODI to test for positive definiteness and to perform further optional calculations. Subroutine SPOFA factors a symmetric matrix M using the Cholesky algorithm to determine the elements of a matrix R which satisfies the relation M=R'R, where R' is the transposed matrix of R. Each leading principal minor of M is tested until the first one is found which is not positive definite. MATXTST1 uses LINPACK subroutines SSICO, SSIFA, and SSIDI to estimate whether the matrix is near to singularity or not (SSICO), and to perform the matrix diagonalization process (SSIFA). The algorithm used in SSIFA is generalization of the Method of Lagrange Reduction. SSIDI is used to compute the determinant and inertia of the matrix. 3 - Restrictions on the complexity of the problem: Matrices of sizes up to 50 X 50 elements can be treated by present versions of the programs
Covariance matrix estimation for stationary time series
Xiao, Han; Wu, Wei Biao
2011-01-01
We obtain a sharp convergence rate for banded covariance matrix estimates of stationary processes. A precise order of magnitude is derived for spectral radius of sample covariance matrices. We also consider a thresholded covariance matrix estimator that can better characterize sparsity if the true covariance matrix is sparse. As our main tool, we implement Toeplitz [Math. Ann. 70 (1911) 351–376] idea and relate eigenvalues of covariance matrices to the spectral densities or Fourier transforms...
Condition Number Regularized Covariance Estimation.
Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
2013-06-01
Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the "large p small n " setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required.
Condition Number Regularized Covariance Estimation*
Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
2012-01-01
Estimation of high-dimensional covariance matrices is known to be a difficult problem, has many applications, and is of current interest to the larger statistics community. In many applications including so-called the “large p small n” setting, the estimate of the covariance matrix is required to be not only invertible, but also well-conditioned. Although many regularization schemes attempt to do this, none of them address the ill-conditioning problem directly. In this paper, we propose a maximum likelihood approach, with the direct goal of obtaining a well-conditioned estimator. No sparsity assumption on either the covariance matrix or its inverse are are imposed, thus making our procedure more widely applicable. We demonstrate that the proposed regularization scheme is computationally efficient, yields a type of Steinian shrinkage estimator, and has a natural Bayesian interpretation. We investigate the theoretical properties of the regularized covariance estimator comprehensively, including its regularization path, and proceed to develop an approach that adaptively determines the level of regularization that is required. Finally, we demonstrate the performance of the regularized estimator in decision-theoretic comparisons and in the financial portfolio optimization setting. The proposed approach has desirable properties, and can serve as a competitive procedure, especially when the sample size is small and when a well-conditioned estimator is required. PMID:23730197
Covariant Gauss law commutator anomaly
International Nuclear Information System (INIS)
Dunne, G.V.; Trugenberger, C.A.; Massachusetts Inst. of Tech., Cambridge
1990-01-01
Using a (fixed-time) hamiltonian formalism we derive a covariant form for the anomaly in the commutator algebra of Gauss law generators for chiral fermions interacting with a dynamical non-abelian gauge field in 3+1 dimensions. (orig.)
Covariant gauges for constrained systems
International Nuclear Information System (INIS)
Gogilidze, S.A.; Khvedelidze, A.M.; Pervushin, V.N.
1995-01-01
The method of constructing of extended phase space for singular theories which permits the consideration of covariant gauges without the introducing of a ghost fields, is proposed. The extension of the phase space is carried out by the identification of the initial theory with an equivalent theory with higher derivatives and applying to it the Ostrogradsky method of Hamiltonian description. 7 refs
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.
Islamiyati, A.; Fatmawati; Chamidah, N.
2018-03-01
The correlation assumption of the longitudinal data with bi-response occurs on the measurement between the subjects of observation and the response. It causes the auto-correlation of error, and this can be overcome by using a covariance matrix. In this article, we estimate the covariance matrix based on the penalized spline regression model. Penalized spline involves knot points and smoothing parameters simultaneously in controlling the smoothness of the curve. Based on our simulation study, the estimated regression model of the weighted penalized spline with covariance matrix gives a smaller error value compared to the error of the model without covariance matrix.
Davenport, Daniel L; Henderson, William G; Mosca, Cecilia L; Khuri, Shukri F; Mentzer, Robert M
2007-12-01
Since the Institute of Medicine patient safety reports, a number of survey-based measures of organizational climate safety factors (OCSFs) have been developed. The goal of this study was to measure the impact of OCSFs on risk-adjusted surgical morbidity and mortality. Surveys were administered to staff on general/vascular surgery services during a year. Surveys included multiitem scales measuring OCSFs. Additionally, perceived levels of communication and collaboration with coworkers were assessed. The National Surgical Quality Improvement Program was used to assess risk-adjusted morbidity and mortality. Correlations between outcomes and OCSFs were calculated and between outcomes and communication/collaboration with attending and resident doctors, nurses, and other providers. Fifty-two sites participated in the survey: 44 Veterans Affairs and 8 academic medical centers. A total of 6,083 surveys were returned, for a response rate of 52%. The OCSF measures of teamwork climate, safety climate, working conditions, recognition of stress effects, job satisfaction, and burnout demonstrated internal validity but did not correlate with risk-adjusted outcomes. Reported levels of communication/collaboration with attending and resident doctors correlated with risk-adjusted morbidity. Survey-based teamwork, safety climate, and working conditions scales are not confirmed to measure organizational factors that influence risk-adjusted surgical outcomes. Reported communication/collaboration with attending and resident doctors on surgical services influenced patient morbidity. This suggests the importance of doctors' coordination and decision-making roles on surgical teams in providing high-quality and safe care. We propose risk-adjusted morbidity as an effective measure of surgical patient safety.
Large Covariance Estimation by Thresholding Principal Orthogonal Complements
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2012-01-01
This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented. PMID:24348088
Massive data compression for parameter-dependent covariance matrices
Heavens, Alan F.; Sellentin, Elena; de Mijolla, Damien; Vianello, Alvise
2017-12-01
We show how the massive data compression algorithm MOPED can be used to reduce, by orders of magnitude, the number of simulated data sets which are required to estimate the covariance matrix required for the analysis of Gaussian-distributed data. This is relevant when the covariance matrix cannot be calculated directly. The compression is especially valuable when the covariance matrix varies with the model parameters. In this case, it may be prohibitively expensive to run enough simulations to estimate the full covariance matrix throughout the parameter space. This compression may be particularly valuable for the next generation of weak lensing surveys, such as proposed for Euclid and Large Synoptic Survey Telescope, for which the number of summary data (such as band power or shear correlation estimates) is very large, ∼104, due to the large number of tomographic redshift bins which the data will be divided into. In the pessimistic case where the covariance matrix is estimated separately for all points in an Monte Carlo Markov Chain analysis, this may require an unfeasible 109 simulations. We show here that MOPED can reduce this number by a factor of 1000, or a factor of ∼106 if some regularity in the covariance matrix is assumed, reducing the number of simulations required to a manageable 103, making an otherwise intractable analysis feasible.
Large Covariance Estimation by Thresholding Principal Orthogonal Complements.
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2013-09-01
This paper deals with the estimation of a high-dimensional covariance with a conditional sparsity structure and fast-diverging eigenvalues. By assuming sparse error covariance matrix in an approximate factor model, we allow for the presence of some cross-sectional correlation even after taking out common but unobservable factors. We introduce the Principal Orthogonal complEment Thresholding (POET) method to explore such an approximate factor structure with sparsity. The POET estimator includes the sample covariance matrix, the factor-based covariance matrix (Fan, Fan, and Lv, 2008), the thresholding estimator (Bickel and Levina, 2008) and the adaptive thresholding estimator (Cai and Liu, 2011) as specific examples. We provide mathematical insights when the factor analysis is approximately the same as the principal component analysis for high-dimensional data. The rates of convergence of the sparse residual covariance matrix and the conditional sparse covariance matrix are studied under various norms. It is shown that the impact of estimating the unknown factors vanishes as the dimensionality increases. The uniform rates of convergence for the unobserved factors and their factor loadings are derived. The asymptotic results are also verified by extensive simulation studies. Finally, a real data application on portfolio allocation is presented.
Real-time probabilistic covariance tracking with efficient model update.
Wu, Yi; Cheng, Jian; Wang, Jinqiao; Lu, Hanqing; Wang, Jun; Ling, Haibin; Blasch, Erik; Bai, Li
2012-05-01
The recently proposed covariance region descriptor has been proven robust and versatile for a modest computational cost. The covariance matrix enables efficient fusion of different types of features, where the spatial and statistical properties, as well as their correlation, are characterized. The similarity between two covariance descriptors is measured on Riemannian manifolds. Based on the same metric but with a probabilistic framework, we propose a novel tracking approach on Riemannian manifolds with a novel incremental covariance tensor learning (ICTL). To address the appearance variations, ICTL incrementally learns a low-dimensional covariance tensor representation and efficiently adapts online to appearance changes of the target with only O(1) computational complexity, resulting in a real-time performance. The covariance-based representation and the ICTL are then combined with the particle filter framework to allow better handling of background clutter, as well as the temporary occlusions. We test the proposed probabilistic ICTL tracker on numerous benchmark sequences involving different types of challenges including occlusions and variations in illumination, scale, and pose. The proposed approach demonstrates excellent real-time performance, both qualitatively and quantitatively, in comparison with several previously proposed trackers.
A three domain covariance framework for EEG/MEG data.
Roś, Beata P; Bijma, Fetsje; de Gunst, Mathisca C M; de Munck, Jan C
2015-10-01
In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three components that correspond to space, time and epochs/trials, and consider maximum likelihood estimation of the unknown parameter values. An iterative algorithm that finds approximations of the maximum likelihood estimates is proposed. Our covariance model is applicable in a variety of cases where spontaneous EEG or MEG acts as source of noise and realistic noise covariance estimates are needed, such as in evoked activity studies, or where the properties of spontaneous EEG or MEG are themselves the topic of interest, like in combined EEG-fMRI experiments in which the correlation between EEG and fMRI signals is investigated. We use a simulation study to assess the performance of the estimator and investigate the influence of different assumptions about the covariance factors on the estimated covariance matrix and on its components. We apply our method to real EEG and MEG data sets. Copyright © 2015 Elsevier Inc. All rights reserved.
Alterations in Anatomical Covariance in the Prematurely Born.
Scheinost, Dustin; Kwon, Soo Hyun; Lacadie, Cheryl; Vohr, Betty R; Schneider, Karen C; Papademetris, Xenophon; Constable, R Todd; Ment, Laura R
2017-01-01
Preterm (PT) birth results in long-term alterations in functional and structural connectivity, but the related changes in anatomical covariance are just beginning to be explored. To test the hypothesis that PT birth alters patterns of anatomical covariance, we investigated brain volumes of 25 PTs and 22 terms at young adulthood using magnetic resonance imaging. Using regional volumetrics, seed-based analyses, and whole brain graphs, we show that PT birth is associated with reduced volume in bilateral temporal and inferior frontal lobes, left caudate, left fusiform, and posterior cingulate for prematurely born subjects at young adulthood. Seed-based analyses demonstrate altered patterns of anatomical covariance for PTs compared with terms. PTs exhibit reduced covariance with R Brodmann area (BA) 47, Broca's area, and L BA 21, Wernicke's area, and white matter volume in the left prefrontal lobe, but increased covariance with R BA 47 and left cerebellum. Graph theory analyses demonstrate that measures of network complexity are significantly less robust in PTs compared with term controls. Volumes in regions showing group differences are significantly correlated with phonological awareness, the fundamental basis for reading acquisition, for the PTs. These data suggest both long-lasting and clinically significant alterations in the covariance in the PTs at young adulthood. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Group covariance and metrical theory
International Nuclear Information System (INIS)
Halpern, L.
1983-01-01
The a priori introduction of a Lie group of transformations into a physical theory has often proved to be useful; it usually serves to describe special simplified conditions before a general theory can be worked out. Newton's assumptions of absolute space and time are examples where the Euclidian group and translation group have been introduced. These groups were extended to the Galilei group and modified in the special theory of relativity to the Poincare group to describe physics under the given conditions covariantly in the simplest way. The criticism of the a priori character leads to the formulation of the general theory of relativity. The general metric theory does not really give preference to a particular invariance group - even the principle of equivalence can be adapted to a whole family of groups. The physical laws covariantly inserted into the metric space are however adapted to the Poincare group. 8 references
Criteria of the validation of experimental and evaluated covariance data
International Nuclear Information System (INIS)
Badikov, S.
2008-01-01
The criteria of the validation of experimental and evaluated covariance data are reviewed. In particular: a) the criterion of the positive definiteness for covariance matrices, b) the relationship between the 'integral' experimental and estimated uncertainties, c) the validity of the statistical invariants, d) the restrictions imposed to correlations between experimental errors, are described. Applying these criteria in nuclear data evaluation was considered and 4 particular points have been examined. First preserving positive definiteness of covariance matrices in case of arbitrary transformation of a random vector was considered, properties of the covariance matrices in operations widely used in neutron and reactor physics (splitting and collapsing energy groups, averaging the physical values over energy groups, estimation parameters on the basis of measurements by means of generalized least squares method) were studied. Secondly, an algorithm for comparison of experimental and estimated 'integral' uncertainties was developed, square root of determinant of a covariance matrix is recommended for use in nuclear data evaluation as a measure of 'integral' uncertainty for vectors of experimental and estimated values. Thirdly, a set of statistical invariants-values which are preserved in statistical processing was presented. And fourthly, the inequality that signals a correlation between experimental errors that leads to unphysical values is given. An application is given concerning the cross-section of the (n,t) reaction on Li 6 with a neutron incident energy comprised between 1 and 100 keV
Altered structural covariance of the striatum in functional dyspepsia patients.
Liu, P; Zeng, F; Yang, F; Wang, J; Liu, X; Wang, Q; Zhou, G; Zhang, D; Zhu, M; Zhao, R; Wang, A; Gong, Q; Liang, F
2014-08-01
Functional dyspepsia (FD) is thought to be involved in dysregulation within the brain-gut axis. Recently, altered striatum activation has been reported in patients with FD. However, the gray matter (GM) volumes in the striatum and structural covariance patterns of this area are rarely explored. The purpose of this study was to examine the GM volumes and structural covariance patterns of the striatum between FD patients and healthy controls (HCs). T1-weighted magnetic resonance images were obtained from 44 FD patients and 39 HCs. Voxel-based morphometry (VBM) analysis was adopted to examine the GM volumes in the two groups. The caudate- or putamen-related regions identified from VBM analysis were then used as seeds to map the whole brain voxel-wise structural covariance patterns. Finally, a correlation analysis was used to investigate the effects of FD symptoms on the striatum. The results showed increased GM volumes in the bilateral putamen and right caudate. Compared with the structural covariance patterns of the HCs, the FD-related differences were mainly located in the amygdala, hippocampus/parahippocampus (HIPP/paraHIPP), thalamus, lingual gyrus, and cerebellum. And significant positive correlations were found between the volumes in the striatum and the FD duration in the patients. These findings provided preliminary evidence for GM changes in the striatum and different structural covariance patterns in patients with FD. The current results might expand our understanding of the pathophysiology of FD. © 2014 John Wiley & Sons Ltd.
Kramer, Guido; Kuniss, Nadine; Kloos, Christof; Lehmann, Thomas; Müller, Nicolle; Wolf, Gunter; Lorkowski, Stefan; Müller, Ulrich A
2016-06-01
Insulin dose self-adjustment (ISA) to different blood glucose levels, carbohydrate intake, exercise or illness is a core element of structured education programmes for people with diabetes mellitus type 1 (DM1). The aim of this study was to register the patients' current principles and frequency of ISA and to check the ability for correct adjustments. 117 people with DM1 (mean HbA1c 7.1%, diabetes duration 24y) were interviewed in a tertiary care centre. The number of ISA was drawn from the last 28days of the patients' diary. The ability to find the correct insulin dose was assessed using five different calculation examples. All patients had participated in a structured education programme. Mean frequency of ISA was 72.1±29.4 per 28days. ISA by adjustment rules was used in 48% (56/117) and by personal experience or feeling in 44% (52/117). Patients adjusting by feeling were older, did less ISA and had lower social status. There were no differences in HbA1c (feeling 7.2±0.8 vs. rules 7.0±0.9, p=0.403), non severe hypoglycaemia (feeling 1.7±1.8 vs. rules 1.9±1.9, p=0.132) and comprehensibility of ISA between both groups. Overall, the participants answered on average 2.8±2.3 of the five calculation examples correctly. Although all people were trained to use a factor for correction for ISA in case of high premeal blood glucose levels, only half of the patients adjusted their insulin dosage using the complex rules from the treatment and education programme. Patients, who performed their ISA based upon feeling, did not show worse metabolic control. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Positive Semidefinite Integrated Covariance Estimation, Factorizations and Asynchronicity
DEFF Research Database (Denmark)
Boudt, Kris; Laurent, Sébastien; Lunde, Asger
An estimator of the ex-post covariation of log-prices under asynchronicity and microstructure noise is proposed. It uses the Cholesky factorization on the correlation matrix in order to exploit the heterogeneity in trading intensity to estimate the different parameters sequentially with as many...
2010-01-01
A method of adjusting a signal processing parameter for a first hearing aid and a second hearing aid forming parts of a binaural hearing aid system to be worn by a user is provided. The binaural hearing aid system comprises a user specific model representing a desired asymmetry between a first ear
Modeling Covariance Breakdowns in Multivariate GARCH
Jin, Xin; Maheu, John M
2014-01-01
This paper proposes a flexible way of modeling dynamic heterogeneous covariance breakdowns in multivariate GARCH (MGARCH) models. During periods of normal market activity, volatility dynamics are governed by an MGARCH specification. A covariance breakdown is any significant temporary deviation of the conditional covariance matrix from its implied MGARCH dynamics. This is captured through a flexible stochastic component that allows for changes in the conditional variances, covariances and impl...
Undesirable effects of covariance matrix techniques for error analysis
International Nuclear Information System (INIS)
Seibert, D.
1994-01-01
Regression with χ 2 constructed from covariance matrices should not be used for some combinations of covariance matrices and fitting functions. Using the technique for unsuitable combinations can amplify systematic errors. This amplification is uncontrolled, and can produce arbitrarily inaccurate results that might not be ruled out by a χ 2 test. In addition, this technique can give incorrect (artificially small) errors for fit parameters. I give a test for this instability and a more robust (but computationally more intensive) method for fitting correlated data
Proofs of Contracted Length Non-covariance
International Nuclear Information System (INIS)
Strel'tsov, V.N.
1994-01-01
Different proofs of contracted length non covariance are discussed. The way based on the establishment of interval inconstancy (dependence on velocity) seems to be the most convincing one. It is stressed that the known non covariance of the electromagnetic field energy and momentum of a moving charge ('the problem 4/3') is a direct consequence of contracted length non covariance. 8 refs
Construction of covariance matrix for experimental data
International Nuclear Information System (INIS)
Liu Tingjin; Zhang Jianhua
1992-01-01
For evaluators and experimenters, the information is complete only in the case when the covariance matrix is given. The covariance matrix of the indirectly measured data has been constructed and discussed. As an example, the covariance matrix of 23 Na(n, 2n) cross section is constructed. A reasonable result is obtained
Zhao, Zhi-Gang; Du, Guo-Zhen; Huang, Shuang-Quan
2010-05-20
Floral traits within plants can vary with flower position or flowering time. Within an inflorescence, sexual allocation of early produced basal flowers is often female-biased while later produced distal flowers are male-biased. Such temporal adjustment of floral resource has been considered one of the potential advantages of modularity (regarding a flower as a module) in hermaphrodites. However, flowers are under constraints of independent evolution of a given trait. To understand flower diversification within inflorescences, here we examine variation and covariation in floral traits within racemes at the individual and the maternal family level respectively in an alpine herb Aconitum gymnandrum (Ranunculaceae). We found that floral traits varied significantly with flower position and among families, and position effects were family-specific. Most of the variance of floral traits was among individuals rather than among flowers within individuals or among families. Significant phenotypic correlations between traits were not affected by position, indicating trait integration under shared developmental regulation. In contrast, positive family-mean correlations in floral traits declined gradually from basal to distal flowers (nine significant correlations among floral traits in basal flowers and only three in distal flowers), showing position-specificity. Therefore, the pattern and magnitude of genetic correlations decreased with flower position. This finding on covariation pattern in floral reproductive structures within racemes has not been revealed before, providing insights into temporal variation and position effects in floral traits within plants and the potential advantages of modularity in hermaphrodites.
Directory of Open Access Journals (Sweden)
Du Guo-Zhen
2010-05-01
Full Text Available Abstract Background Floral traits within plants can vary with flower position or flowering time. Within an inflorescence, sexual allocation of early produced basal flowers is often female-biased while later produced distal flowers are male-biased. Such temporal adjustment of floral resource has been considered one of the potential advantages of modularity (regarding a flower as a module in hermaphrodites. However, flowers are under constraints of independent evolution of a given trait. To understand flower diversification within inflorescences, here we examine variation and covariation in floral traits within racemes at the individual and the maternal family level respectively in an alpine herb Aconitum gymnandrum (Ranunculaceae. Results We found that floral traits varied significantly with flower position and among families, and position effects were family-specific. Most of the variance of floral traits was among individuals rather than among flowers within individuals or among families. Significant phenotypic correlations between traits were not affected by position, indicating trait integration under shared developmental regulation. In contrast, positive family-mean correlations in floral traits declined gradually from basal to distal flowers (nine significant correlations among floral traits in basal flowers and only three in distal flowers, showing position-specificity. Therefore, the pattern and magnitude of genetic correlations decreased with flower position. Conclusions This finding on covariation pattern in floral reproductive structures within racemes has not been revealed before, providing insights into temporal variation and position effects in floral traits within plants and the potential advantages of modularity in hermaphrodites.
ZZ RRDF-98, Cross-sections and covariance matrices for 22 neutron induced dosimetry reactions
International Nuclear Information System (INIS)
Zolotarev, K.I.; Ignatyuk, A.V.; Mahokhin, V.N.; Pashchenko, A.B.
2005-01-01
1 - Description of program or function: Format: ENDF-6 format; Number of groups: Continuous energy; Dosimetry reactions: 6-C-12(n,2n), 8-O-16(n,2n), 9-F-19(n,2n), 12-Mg-24(n,p), 22-Ti-46(n,2n), 22-Ti-46(n,p), 22-Ti-47(n,x), 22-Ti-48(n,p), 22-Ti-48(n,x), 22-Ti-49(n,x), 23-V-51(n,alpha), 26-Fe-54(n,2n), 26-Fe-54(n,alpha), 26-Fe-56(n,p), 27-Co-59(n,alpha), 29-Cu-63(n,alpha), 33-As-75(n,2n), 41-Nb-93(n,2n), 41-Nb-93(n,n'), 45-Rh-103(n,n'), 49-In-115(n,n'), 59-Pr-141(n,2n); Origin: Russian Federation; Weighting spectrum: None. RRDF-98 contains original evaluations of cross section data performed at the Institute of Physics and Power Engineering, Obninsk, for 22 neutron induced dosimetry reactions. The dataset also contains the corresponding covariance matrices. 2 - Methods: The evaluation of excitation functions was performed on the basis of statistical analysis of corrected experimental data in the framework of generalized least squares method and taking into account the results of optical-statistical STAPRE and GNASH calculations. The experimental cross section data including the most recent results were critically reviewed and processed in this study. If necessary, the data were normalized in order to make adjustments in relevant cross sections and decay schemes. The covariance matrices were prepared and the evaluated cross section data are presented in ENDF-6 format (Files 3, 33). For estimation of correlations between experimental data the total uncertainties of measured cross sections have been separated into statistical and systematic parts and correlation coefficients between components of systematic parts were assigned according to information given in the original publications and EXFOR library. Then the correlation matrix of cross sections measured within one experiment was calculated and approximated by matrix with a constant (average) correlation coefficient. The overall correlation matrix was composed of such sub-matrices in the assumption that the cross
Covariant non-commutative space–time
Directory of Open Access Journals (Sweden)
Jonathan J. Heckman
2015-05-01
Full Text Available We introduce a covariant non-commutative deformation of 3+1-dimensional conformal field theory. The deformation introduces a short-distance scale ℓp, and thus breaks scale invariance, but preserves all space–time isometries. The non-commutative algebra is defined on space–times with non-zero constant curvature, i.e. dS4 or AdS4. The construction makes essential use of the representation of CFT tensor operators as polynomials in an auxiliary polarization tensor. The polarization tensor takes active part in the non-commutative algebra, which for dS4 takes the form of so(5,1, while for AdS4 it assembles into so(4,2. The structure of the non-commutative correlation functions hints that the deformed theory contains gravitational interactions and a Regge-like trajectory of higher spin excitations.
Covariant Derivatives and the Renormalization Group Equation
Dolan, Brian P.
The renormalization group equation for N-point correlation functions can be interpreted in a geometrical manner as an equation for Lie transport of amplitudes in the space of couplings. The vector field generating the diffeomorphism has components given by the β functions of the theory. It is argued that this simple picture requires modification whenever any one of the points at which the amplitude is evaluated becomes close to any other. This modification necessitates the introduction of a connection on the space of couplings and new terms appear in the renormalization group equation involving covariant derivatives of the β function and the curvature associated with the connection. It is shown how the connection is related to the operator product expansion coefficients, but there remains an arbitrariness in its definition.
Lorentz covariant theory of gravitation
International Nuclear Information System (INIS)
Fagundes, H.V.
1974-12-01
An alternative method for the calculation of second order effects, like the secular shift of Mercury's perihelium is developed. This method uses the basic ideas of thirring combined with the more mathematical approach of Feyman. In the case of a static source, the treatment used is greatly simplified. Besides, Einstein-Infeld-Hoffmann's Lagrangian for a system of two particles and spin-orbit and spin-spin interactions of two particles with classical spin, ie, internal angular momentum in Moller's sense, are obtained from the Lorentz covariant theory
International Nuclear Information System (INIS)
Sebestyen, A.
1975-07-01
The principle of covariance is extended to coordinates corresponding to internal degrees of freedom. The conditions for a system to be isolated are given. It is shown how internal forces arise in such systems. Equations for internal fields are derived. By an interpretation of the generalized coordinates based on group theory it is shown how particles of the ordinary sense enter into the model and as a simple application the gravitational interaction of two pointlike particles is considered and the shift of the perihelion is deduced. (Sz.Z.)
Covariant gauges at finite temperature
Landshoff, Peter V
1992-01-01
A prescription is presented for real-time finite-temperature perturbation theory in covariant gauges, in which only the two physical degrees of freedom of the gauge-field propagator acquire thermal parts. The propagators for the unphysical degrees of freedom of the gauge field, and for the Faddeev-Popov ghost field, are independent of temperature. This prescription is applied to the calculation of the one-loop gluon self-energy and the two-loop interaction pressure, and is found to be simpler to use than the conventional one.
HR Department
2008-01-01
In accordance with decisions taken by the Finance Committee and Council in December 2007, salaries are adjusted with effect from 1 January 2008. Scale of basic salaries and scale of stipends paid to fellows (Annex R A 5 and R A 6 respectively): increased by 0.71% with effect from 1 January 2008. As a result of the stability of the Geneva consumer price index, following elements do not increase: a) Family Allowance, Child Allowance and Infant Allowance (Annex R A 3). b) Reimbursement of education fees: maximum amounts of reimbursement (Annex R A 4.01) for the academic year 2007/2008. Related adjustments will be implemented, wherever applicable, to Paid Associates and Students. As in the past, the actual percentage increase of each salary position may vary, due to the application of a constant step value and the rounding effects. Human Resources Department Tel. 73566
HR Department
2008-01-01
In accordance with decisions taken by the Finance Committee and Council in December 2007, salaries are adjusted with effect from 1 January 2008. Scale of basic salaries and scale of stipends paid to fellows (Annex R A 5 and R A 6 respectively): increased by 0.71% with effect from 1 January 2008. As a result of the stability of the Geneva consumer price index, the following elements do not increase: a)\tFamily Allowance, Child Allowance and Infant Allowance (Annex R A 3); b)\tReimbursement of education fees: maximum amounts of reimbursement (Annex R A 4.01) for the academic year 2007/2008. Related adjustments will be applied, wherever applicable, to Paid Associates and Students. As in the past, the actual percentage increase of each salary position may vary, due to the application of a constant step value and rounding effects. Human Resources Department Tel. 73566
Harry, Herbert H.
1989-01-01
Apparatus and method for the adjustment and alignment of shafts in high power devices. A plurality of adjacent rotatable angled cylinders are positioned between a base and the shaft to be aligned which when rotated introduce an axial offset. The apparatus is electrically conductive and constructed of a structurally rigid material. The angled cylinders allow the shaft such as the center conductor in a pulse line machine to be offset in any desired alignment position within the range of the apparatus.
International Nuclear Information System (INIS)
Carlson, R.W.; Covic, J.; Leininger, G.
1981-01-01
In a rotating fan beam tomographic scanner there is included an adjustable collimator and shutter assembly. The assembly includes a fan angle collimation cylinder having a plurality of different length slots through which the beam may pass for adjusting the fan angle of the beam. It also includes a beam thickness cylinder having a plurality of slots of different widths for adjusting the thickness of the beam. Further, some of the slots have filter materials mounted therein so that the operator may select from a plurality of filters. Also disclosed is a servo motor system which allows the operator to select the desired fan angle, beam thickness and filter from a remote location. An additional feature is a failsafe shutter assembly which includes a spring biased shutter cylinder mounted in the collimation cylinders. The servo motor control circuit checks several system conditions before the shutter is rendered openable. Further, the circuit cuts off the radiation if the shutter fails to open or close properly. A still further feature is a reference radiation intensity monitor which includes a tuning-fork shaped light conducting element having a scintillation crystal mounted on each tine. The monitor is placed adjacent the collimator between it and the source with the pair of crystals to either side of the fan beam
Covariance Evaluation Methodology for Neutron Cross Sections
Energy Technology Data Exchange (ETDEWEB)
Herman,M.; Arcilla, R.; Mattoon, C.M.; Mughabghab, S.F.; Oblozinsky, P.; Pigni, M.; Pritychenko, b.; Songzoni, A.A.
2008-09-01
We present the NNDC-BNL methodology for estimating neutron cross section covariances in thermal, resolved resonance, unresolved resonance and fast neutron regions. The three key elements of the methodology are Atlas of Neutron Resonances, nuclear reaction code EMPIRE, and the Bayesian code implementing Kalman filter concept. The covariance data processing, visualization and distribution capabilities are integral components of the NNDC methodology. We illustrate its application on examples including relatively detailed evaluation of covariances for two individual nuclei and massive production of simple covariance estimates for 307 materials. Certain peculiarities regarding evaluation of covariances for resolved resonances and the consistency between resonance parameter uncertainties and thermal cross section uncertainties are also discussed.
Estimation of covariance matrix on the experimental data for nuclear data evaluation
International Nuclear Information System (INIS)
Murata, T.
1985-01-01
In order to evaluate fission and capture cross sections of some U and Pu isotopes for JENDL-3, we have a plan for evaluating them simultaneously with a least-squares method. For the simultaneous evaluation, the covariance matrix is required for each experimental data set. In the present work, we have studied the procedures for deriving the covariance matrix from the error data given in the experimental papers. The covariance matrices were obtained using the partial errors and estimated correlation coefficients between the same type partial errors for different neutron energy. Some examples of the covariance matrix estimation are explained and the preliminary results of the simultaneous evaluation are presented. (author)
Poincare covariance and κ-Minkowski spacetime
International Nuclear Information System (INIS)
Dabrowski, Ludwik; Piacitelli, Gherardo
2011-01-01
A fully Poincare covariant model is constructed as an extension of the κ-Minkowski spacetime. Covariance is implemented by a unitary representation of the Poincare group, and thus complies with the original Wigner approach to quantum symmetries. This provides yet another example (besides the DFR model), where Poincare covariance is realised a la Wigner in the presence of two characteristic dimensionful parameters: the light speed and the Planck length. In other words, a Doubly Special Relativity (DSR) framework may well be realised without deforming the meaning of 'Poincare covariance'. -- Highlights: → We construct a 4d model of noncommuting coordinates (quantum spacetime). → The coordinates are fully covariant under the undeformed Poincare group. → Covariance a la Wigner holds in presence of two dimensionful parameters. → Hence we are not forced to deform covariance (e.g. as quantum groups). → The underlying κ-Minkowski model is unphysical; covariantisation does not cure this.
Construction and use of gene expression covariation matrix
Directory of Open Access Journals (Sweden)
Bellis Michel
2009-07-01
Full Text Available Abstract Background One essential step in the massive analysis of transcriptomic profiles is the calculation of the correlation coefficient, a value used to select pairs of genes with similar or inverse transcriptional profiles across a large fraction of the biological conditions examined. Until now, the choice between the two available methods for calculating the coefficient has been dictated mainly by technological considerations. Specifically, in analyses based on double-channel techniques, researchers have been required to use covariation correlation, i.e. the correlation between gene expression changes measured between several pairs of biological conditions, expressed for example as fold-change. In contrast, in analyses of single-channel techniques scientists have been restricted to the use of coexpression correlation, i.e. correlation between gene expression levels. To our knowledge, nobody has ever examined the possible benefits of using covariation instead of coexpression in massive analyses of single channel microarray results. Results We describe here how single-channel techniques can be treated like double-channel techniques and used to generate both gene expression changes and covariation measures. We also present a new method that allows the calculation of both positive and negative correlation coefficients between genes. First, we perform systematic comparisons between two given biological conditions and classify, for each comparison, genes as increased (I, decreased (D, or not changed (N. As a result, the original series of n gene expression level measures assigned to each gene is replaced by an ordered string of n(n-1/2 symbols, e.g. IDDNNIDID....DNNNNNNID, with the length of the string corresponding to the number of comparisons. In a second step, positive and negative covariation matrices (CVM are constructed by calculating statistically significant positive or negative correlation scores for any pair of genes by comparing their
International Nuclear Information System (INIS)
Buckler, A.N.
1978-10-01
Details of the coding techniques, with flow diagrams are given for the correlation code DELILAH which is a replacement for the SAMSON code for SGHW and other thermal systems. An improved method of rejecting inaccurate channel power measurements is described in detail. A list of the input data requirements for the code will be published separately. (author)
Monte, Ralph C; Goulding, Sandra M; Compton, Michael T
2008-09-01
Motivated by a previous study among male veterans [Allen, D.N., Frantom, L.V., Strauss, G.P., van Kammen, D.P., 2005. Differential patterns of premorbid academic and social deterioration in patients with schizophrenia. Schizophr. Res. 75, 389-397], the present analysis examined: (1) patterns of premorbid academic and social functioning during childhood, early adolescence, and late adolescence, and (2) associations between these premorbid functioning dimensions and a number of clinical variables. Data on premorbid functioning were collected using the Premorbid Adjustment Scale (PAS) in 95 hospitalized first-episode patients. Analyses were similar to those conducted by Allen and colleagues (2005). Deterioration was evident in both academic and social functioning from childhood to early adolescence, along with a pronounced/accelerated deterioration in academic functioning from early adolescence to late adolescence, occurring in both male and female patients. Age at onset of prodromal symptoms was predicted by childhood/early adolescent/late adolescent academic functioning scores, and age at onset of psychotic symptoms was significantly associated only with childhood academic functioning. Severity of negative symptoms was predicted by childhood and late adolescent social functioning scores, and severity of general psychopathology symptoms was predicted by late adolescent academic functioning, as well as childhood and late adolescent social functioning scores. Consistent with prior findings, deterioration in premorbid functioning appears to be more pronounced in the academic than social dimension of the PAS. Some PAS scores are predictive of ages at onset of prodrome/psychosis and severity of psychotic symptoms. Ongoing research on premorbid adjustment in schizophrenia may have implications for future prevention goals.
COVARIANCE ASSISTED SCREENING AND ESTIMATION.
Ke, By Tracy; Jin, Jiashun; Fan, Jianqing
2014-11-01
Consider a linear model Y = X β + z , where X = X n,p and z ~ N (0, I n ). The vector β is unknown and it is of interest to separate its nonzero coordinates from the zero ones (i.e., variable selection). Motivated by examples in long-memory time series (Fan and Yao, 2003) and the change-point problem (Bhattacharya, 1994), we are primarily interested in the case where the Gram matrix G = X ' X is non-sparse but sparsifiable by a finite order linear filter. We focus on the regime where signals are both rare and weak so that successful variable selection is very challenging but is still possible. We approach this problem by a new procedure called the Covariance Assisted Screening and Estimation (CASE). CASE first uses a linear filtering to reduce the original setting to a new regression model where the corresponding Gram (covariance) matrix is sparse. The new covariance matrix induces a sparse graph, which guides us to conduct multivariate screening without visiting all the submodels. By interacting with the signal sparsity, the graph enables us to decompose the original problem into many separated small-size subproblems (if only we know where they are!). Linear filtering also induces a so-called problem of information leakage , which can be overcome by the newly introduced patching technique. Together, these give rise to CASE, which is a two-stage Screen and Clean (Fan and Song, 2010; Wasserman and Roeder, 2009) procedure, where we first identify candidates of these submodels by patching and screening , and then re-examine each candidate to remove false positives. For any procedure β̂ for variable selection, we measure the performance by the minimax Hamming distance between the sign vectors of β̂ and β. We show that in a broad class of situations where the Gram matrix is non-sparse but sparsifiable, CASE achieves the optimal rate of convergence. The results are successfully applied to long-memory time series and the change-point model.
Semiparametric estimation of covariance matrices for longitudinal data.
Fan, Jianqing; Wu, Yichao
2008-12-01
Estimation of longitudinal data covariance structure poses significant challenges because the data are usually collected at irregular time points. A viable semiparametric model for covariance matrices was proposed in Fan, Huang and Li (2007) that allows one to estimate the variance function nonparametrically and to estimate the correlation function parametrically via aggregating information from irregular and sparse data points within each subject. However, the asymptotic properties of their quasi-maximum likelihood estimator (QMLE) of parameters in the covariance model are largely unknown. In the current work, we address this problem in the context of more general models for the conditional mean function including parametric, nonparametric, or semi-parametric. We also consider the possibility of rough mean regression function and introduce the difference-based method to reduce biases in the context of varying-coefficient partially linear mean regression models. This provides a more robust estimator of the covariance function under a wider range of situations. Under some technical conditions, consistency and asymptotic normality are obtained for the QMLE of the parameters in the correlation function. Simulation studies and a real data example are used to illustrate the proposed approach.
Fitting direct covariance structures by the MSTRUCT modeling language of the CALIS procedure.
Yung, Yiu-Fai; Browne, Michael W; Zhang, Wei
2015-02-01
This paper demonstrates the usefulness and flexibility of the general structural equation modelling (SEM) approach to fitting direct covariance patterns or structures (as opposed to fitting implied covariance structures from functional relationships among variables). In particular, the MSTRUCT modelling language (or syntax) of the CALIS procedure (SAS/STAT version 9.22 or later: SAS Institute, 2010) is used to illustrate the SEM approach. The MSTRUCT modelling language supports a direct covariance pattern specification of each covariance element. It also supports the input of additional independent and dependent parameters. Model tests, fit statistics, estimates, and their standard errors are then produced under the general SEM framework. By using numerical and computational examples, the following tests of basic covariance patterns are illustrated: sphericity, compound symmetry, and multiple-group covariance patterns. Specification and testing of two complex correlation structures, the circumplex pattern and the composite direct product models with or without composite errors and scales, are also illustrated by the MSTRUCT syntax. It is concluded that the SEM approach offers a general and flexible modelling of direct covariance and correlation patterns. In conjunction with the use of SAS macros, the MSTRUCT syntax provides an easy-to-use interface for specifying and fitting complex covariance and correlation structures, even when the number of variables or parameters becomes large. © 2014 The British Psychological Society.
Non-Critical Covariant Superstrings
Grassi, P A
2005-01-01
We construct a covariant description of non-critical superstrings in even dimensions. We construct explicitly supersymmetric hybrid type variables in a linear dilaton background, and study an underlying N=2 twisted superconformal algebra structure. We find similarities between non-critical superstrings in 2n+2 dimensions and critical superstrings compactified on CY_(4-n) manifolds. We study the spectrum of the non-critical strings, and in particular the Ramond-Ramond massless fields. We use the supersymmetric variables to construct the non-critical superstrings sigma-model action in curved target space backgrounds with coupling to the Ramond-Ramond fields. We consider as an example non-critical type IIA strings on AdS_2 background with Ramond-Ramond 2-form flux.
Extendable linearised adjustment model for deformation analysis
Hiddo Velsink
2015-01-01
Author supplied: "This paper gives a linearised adjustment model for the affine, similarity and congruence transformations in 3D that is easily extendable with other parameters to describe deformations. The model considers all coordinates stochastic. Full positive semi-definite covariance matrices
Missing continuous outcomes under covariate dependent missingness in cluster randomised trials.
Hossain, Anower; Diaz-Ordaz, Karla; Bartlett, Jonathan W
2017-06-01
Attrition is a common occurrence in cluster randomised trials which leads to missing outcome data. Two approaches for analysing such trials are cluster-level analysis and individual-level analysis. This paper compares the performance of unadjusted cluster-level analysis, baseline covariate adjusted cluster-level analysis and linear mixed model analysis, under baseline covariate dependent missingness in continuous outcomes, in terms of bias, average estimated standard error and coverage probability. The methods of complete records analysis and multiple imputation are used to handle the missing outcome data. We considered four scenarios, with the missingness mechanism and baseline covariate effect on outcome either the same or different between intervention groups. We show that both unadjusted cluster-level analysis and baseline covariate adjusted cluster-level analysis give unbiased estimates of the intervention effect only if both intervention groups have the same missingness mechanisms and there is no interaction between baseline covariate and intervention group. Linear mixed model and multiple imputation give unbiased estimates under all four considered scenarios, provided that an interaction of intervention and baseline covariate is included in the model when appropriate. Cluster mean imputation has been proposed as a valid approach for handling missing outcomes in cluster randomised trials. We show that cluster mean imputation only gives unbiased estimates when missingness mechanism is the same between the intervention groups and there is no interaction between baseline covariate and intervention group. Multiple imputation shows overcoverage for small number of clusters in each intervention group.
Sang, Huiyan; Jun, Mikyoung; Huang, Jianhua Z.
2011-01-01
This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models
Rocco, Antonio; Martocchia, Antonio; Frugoni, Patrizia; Baldini, Rossella; Sani, Gabriele; Di Simone Di Giuseppe, Barbara; Vairano, Andrea; Girardi, Paolo; Monaco, Edoardo; Tatarelli, Roberto; Falaschi, Paolo
2007-10-01
Evidence in the literature suggests stress-related changes of hypothalamus-pituitary-adrenal (HPA) axis in mobbing. We investigated the association between HPA activity and psychological profiles in mobbing, using a multidisciplinary approach. Forty-eight victims of mobbing were evaluated by a working group of the Departments of Occupational Medicine, Psychiatry and Internal Medicine. After an informed consent, a detailed occupational history, a psychiatric interview with Minnesota Multiphasic Personality Inventory 2 (MMPI-2) administration and a blood sample (8:00 AM) for the determination of basal adrenocorticotropin (ACTH), cortisol and dehydroepiandrosterone sulphate (DHEAS) plasma levels were collected. Twenty-six patients received an overnight dexamethasone (dex) test. Mean ACTH, cortisol and DHEAS levels were within normal ranges. The dex-test response was normal, with a significant hormone suppression (ACTH pmobbing with adjustment disorders was observed. A larger group of patients is necessary to identify and validate a cut-off cortisol level that may become an innovative biological parameter for the diagnosis and follow-up in victims of mobbing.
Central subspace dimensionality reduction using covariance operators.
Kim, Minyoung; Pavlovic, Vladimir
2011-04-01
We consider the task of dimensionality reduction informed by real-valued multivariate labels. The problem is often treated as Dimensionality Reduction for Regression (DRR), whose goal is to find a low-dimensional representation, the central subspace, of the input data that preserves the statistical correlation with the targets. A class of DRR methods exploits the notion of inverse regression (IR) to discover central subspaces. Whereas most existing IR techniques rely on explicit output space slicing, we propose a novel method called the Covariance Operator Inverse Regression (COIR) that generalizes IR to nonlinear input/output spaces without explicit target slicing. COIR's unique properties make DRR applicable to problem domains with high-dimensional output data corrupted by potentially significant amounts of noise. Unlike recent kernel dimensionality reduction methods that employ iterative nonconvex optimization, COIR yields a closed-form solution. We also establish the link between COIR, other DRR techniques, and popular supervised dimensionality reduction methods, including canonical correlation analysis and linear discriminant analysis. We then extend COIR to semi-supervised settings where many of the input points lack their labels. We demonstrate the benefits of COIR on several important regression problems in both fully supervised and semi-supervised settings.
ISSUES IN NEUTRON CROSS SECTION COVARIANCES
Energy Technology Data Exchange (ETDEWEB)
Mattoon, C.M.; Oblozinsky,P.
2010-04-30
We review neutron cross section covariances in both the resonance and fast neutron regions with the goal to identify existing issues in evaluation methods and their impact on covariances. We also outline ideas for suitable covariance quality assurance procedures.We show that the topic of covariance data remains controversial, the evaluation methodologies are not fully established and covariances produced by different approaches have unacceptable spread. The main controversy is in very low uncertainties generated by rigorous evaluation methods and much larger uncertainties based on simple estimates from experimental data. Since the evaluators tend to trust the former, while the users tend to trust the latter, this controversy has considerable practical implications. Dedicated effort is needed to arrive at covariance evaluation methods that would resolve this issue and produce results accepted internationally both by evaluators and users.
Covariant diagrams for one-loop matching
Energy Technology Data Exchange (ETDEWEB)
Zhang, Zhengkang [Michigan Center for Theoretical Physics (MCTP), University of Michigan,450 Church Street, Ann Arbor, MI 48109 (United States); Deutsches Elektronen-Synchrotron (DESY),Notkestraße 85, 22607 Hamburg (Germany)
2017-05-30
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariant diagrams for one-loop matching
International Nuclear Information System (INIS)
Zhang, Zhengkang
2017-01-01
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed “covariant diagrams.” The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Improvement of covariance data for fast reactors
International Nuclear Information System (INIS)
Shibata, Keiichi; Hasegawa, Akira
2000-02-01
We estimated covariances of the JENDL-3.2 data on the nuclides and reactions needed to analyze fast-reactor cores for the past three years, and produced covariance files. The present work was undertaken to re-examine the covariance files and to make some improvements. The covariances improved are the ones for the inelastic scattering cross section of 16 O, the total cross section of 23 Na, the fission cross section of 235 U, the capture cross section of 238 U, and the resolved resonance parameters for 238 U. Moreover, the covariances of 233 U data were newly estimated by the present work. The covariances obtained were compiled in the ENDF-6 format. (author)
Effect of neural connectivity on autocovariance and cross covariance estimates
Directory of Open Access Journals (Sweden)
Stecker Mark M
2007-01-01
Full Text Available Abstract Background Measurements of auto and cross covariance functions are frequently used to investigate neural systems. In interpreting this data, it is commonly assumed that the largest contribution to the recordings comes from sources near the electrode. However, the potential recorded at an electrode represents the superimposition of the potentials generated by large numbers of active neural structures. This creates situations under which the measured auto and cross covariance functions are dominated by the activity in structures far from the electrode and in which the distance dependence of the cross-covariance function differs significantly from that describing the activity in the actual neural structures. Methods Direct application of electrostatics to calculate the theoretical auto and cross covariance functions that would be recorded from electrodes immersed in a large volume filled with active neural structures with specific statistical properties. Results It is demonstrated that the potentials recorded from a monopolar electrode surrounded by dipole sources in a uniform medium are predominantly due to activity in neural structures far from the electrode when neuronal correlations drop more slowly than 1/r3 or when the size of the neural system is much smaller than a known correlation distance. Recordings from quadrupolar sources are strongly dependent on distant neurons when correlations drop more slowly than 1/r or the size of the system is much smaller than the correlation distance. Differences between bipolar and monopolar recordings are discussed. It is also demonstrated that the cross covariance of the recorded in two spatially separated electrodes declines as a power-law function of the distance between them even when the electrical activity from different neuronal structures is uncorrelated. Conclusion When extracellular electrophysiologic recordings are made from systems containing large numbers of neural structures, it is
ANL Critical Assembly Covariance Matrix Generation - Addendum
Energy Technology Data Exchange (ETDEWEB)
McKnight, Richard D. [Argonne National Lab. (ANL), Argonne, IL (United States); Grimm, Karl N. [Argonne National Lab. (ANL), Argonne, IL (United States)
2014-01-13
In March 2012, a report was issued on covariance matrices for Argonne National Laboratory (ANL) critical experiments. That report detailed the theory behind the calculation of covariance matrices and the methodology used to determine the matrices for a set of 33 ANL experimental set-ups. Since that time, three new experiments have been evaluated and approved. This report essentially updates the previous report by adding in these new experiments to the preceding covariance matrix structure.
Modifications of Sp(2) covariant superfield quantization
Energy Technology Data Exchange (ETDEWEB)
Gitman, D.M.; Moshin, P.Yu
2003-12-04
We propose a modification of the Sp(2) covariant superfield quantization to realize a superalgebra of generating operators isomorphic to the massless limit of the corresponding superalgebra of the osp(1,2) covariant formalism. The modified scheme ensures the compatibility of the superalgebra of generating operators with extended BRST symmetry without imposing restrictions eliminating superfield components from the quantum action. The formalism coincides with the Sp(2) covariant superfield scheme and with the massless limit of the osp(1,2) covariant quantization in particular cases of gauge-fixing and solutions of the quantum master equations.
Competing risks and time-dependent covariates
DEFF Research Database (Denmark)
Cortese, Giuliana; Andersen, Per K
2010-01-01
Time-dependent covariates are frequently encountered in regression analysis for event history data and competing risks. They are often essential predictors, which cannot be substituted by time-fixed covariates. This study briefly recalls the different types of time-dependent covariates......, as classified by Kalbfleisch and Prentice [The Statistical Analysis of Failure Time Data, Wiley, New York, 2002] with the intent of clarifying their role and emphasizing the limitations in standard survival models and in the competing risks setting. If random (internal) time-dependent covariates...
Activities of covariance utilization working group
International Nuclear Information System (INIS)
Tsujimoto, Kazufumi
2013-01-01
During the past decade, there has been a interest in the calculational uncertainties induced by nuclear data uncertainties in the neutronics design of advanced nuclear system. The covariance nuclear data is absolutely essential for the uncertainty analysis. In the latest version of JENDL, JENDL-4.0, the covariance data for many nuclides, especially actinide nuclides, was substantialy enhanced. The growing interest in the uncertainty analysis and the covariance data has led to the organisation of the working group for covariance utilization under the JENDL committee. (author)
Working covariance model selection for generalized estimating equations.
Carey, Vincent J; Wang, You-Gan
2011-11-20
We investigate methods for data-based selection of working covariance models in the analysis of correlated data with generalized estimating equations. We study two selection criteria: Gaussian pseudolikelihood and a geodesic distance based on discrepancy between model-sensitive and model-robust regression parameter covariance estimators. The Gaussian pseudolikelihood is found in simulation to be reasonably sensitive for several response distributions and noncanonical mean-variance relations for longitudinal data. Application is also made to a clinical dataset. Assessment of adequacy of both correlation and variance models for longitudinal data should be routine in applications, and we describe open-source software supporting this practice. Copyright © 2011 John Wiley & Sons, Ltd.
International Nuclear Information System (INIS)
Smith, D.L.
1988-01-01
The last decade has been a period of rapid development in the implementation of covariance-matrix methodology in nuclear data research. This paper offers some perspective on the progress which has been made, on some of the unresolved problems, and on the potential yet to be realized. These discussions address a variety of issues related to the development of nuclear data. Topics examined are: the importance of designing and conducting experiments so that error information is conveniently generated; the procedures for identifying error sources and quantifying their magnitudes and correlations; the combination of errors; the importance of consistent and well-characterized measurement standards; the role of covariances in data parameterization (fitting); the estimation of covariances for values calculated from mathematical models; the identification of abnormalities in covariance matrices and the analysis of their consequences; the problems encountered in representing covariance information in evaluated files; the role of covariances in the weighting of diverse data sets; the comparison of various evaluations; the influence of primary-data covariance in the analysis of covariances for derived quantities (sensitivity); and the role of covariances in the merging of the diverse nuclear data information. 226 refs., 2 tabs
Adjusted functional boxplots for spatio-temporal data visualization and outlier detection
Sun, Ying
2011-10-24
This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio-temporal dependence and the 1.5 times the 50% central region empirical outlier detection rule. Then, we propose to simulate observations without outliers on the basis of a robust estimator of the covariance function of the data. We select the constant factor in the functional boxplot to control the probability of correctly detecting no outliers. Finally, we apply the selected factor to the functional boxplot of the original data. As applications, the factor selection procedure and the adjusted functional boxplots are demonstrated on sea surface temperatures, spatio-temporal precipitation and general circulation model (GCM) data. The outlier detection performance is also compared before and after the factor adjustment. © 2011 John Wiley & Sons, Ltd.
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. Copyright © 2015 Elsevier Ltd. All rights reserved.
Do Time-Varying Covariances, Volatility Comovement and Spillover Matter?
Lakshmi Balasubramanyan
2005-01-01
Financial markets and their respective assets are so intertwined; analyzing any single market in isolation ignores important information. We investigate whether time varying volatility comovement and spillover impact the true variance-covariance matrix under a time-varying correlation set up. Statistically significant volatility spillover and comovement between US, UK and Japan is found. To demonstrate the importance of modelling volatility comovement and spillover, we look at a simple portfo...
Co-movements among financial stocks and covariance matrix analysis
Sharifi, Saba
2003-01-01
The major theories of finance leading into the main body of this research are discussed and our experiments on studying the risk and co-movements among stocks are presented. This study leads to the application of Random Matrix Theory (RMT) The idea of this theory refers to the importance of the empirically measured correlation (or covariance) matrix, C, in finance and particularly in the theory of optimal portfolios However, this matrix has recently come into question, as a large part of ...
Treatment of Nuclear Data Covariance Information in Sample Generation
Energy Technology Data Exchange (ETDEWEB)
Swiler, Laura Painton [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Adams, Brian M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wieselquist, William [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Reactor and Nuclear Systems Division
2017-10-01
This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on developing a sampling capability that can handle the challenges of generating samples from nuclear cross-section data. The covariance information between energy groups tends to be very ill-conditioned and thus poses a problem using traditional methods for generated correlated samples. This report outlines a method that addresses the sample generation from cross-section matrices.
Treatment of Nuclear Data Covariance Information in Sample Generation
International Nuclear Information System (INIS)
Swiler, Laura Painton; Adams, Brian M.; Wieselquist, William
2017-01-01
This report summarizes a NEAMS (Nuclear Energy Advanced Modeling and Simulation) project focused on developing a sampling capability that can handle the challenges of generating samples from nuclear cross-section data. The covariance information between energy groups tends to be very ill-conditioned and thus poses a problem using traditional methods for generated correlated samples. This report outlines a method that addresses the sample generation from cross-section matrices.
The Goodness of Covariance Selection Problem from AUC Bounds
Khajavi, Navid Tafaghodi; Kuh, Anthony
2016-01-01
We conduct a study of graphical models and discuss the quality of model selection approximation by formulating the problem as a detection problem and examining the area under the curve (AUC). We are specifically looking at the model selection problem for jointly Gaussian random vectors. For Gaussian random vectors, this problem simplifies to the covariance selection problem which is widely discussed in literature by Dempster [1]. In this paper, we give the definition for the correlation appro...
Evaluating dynamic covariance matrix forecasting and portfolio optimization
Sendstad, Lars Hegnes; Holten, Dag Martin
2012-01-01
In this thesis we have evaluated the covariance forecasting ability of the simple moving average, the exponential moving average and the dynamic conditional correlation models. Overall we found that a dynamic portfolio can gain significant improvements by implementing a multivariate GARCH forecast. We further divided the global investment universe into sectors and regions in order to investigate the relative portfolio performance of several asset allocation strategies with both variance and c...
General covariance and quantum theory
International Nuclear Information System (INIS)
Mashhoon, B.
1986-01-01
The extension of the principle of relativity to general coordinate systems is based on the hypothesis that an accelerated observer is locally equivalent to a hypothetical inertial observer with the same velocity as the noninertial observer. This hypothesis of locality is expected to be valid for classical particle phenomena as well as for classical wave phenomena but only in the short-wavelength approximation. The generally covariant theory is therefore expected to be in conflict with the quantum theory which is based on wave-particle duality. This is explicitly demonstrated for the frequency of electromagnetic radiation measured by a uniformly rotating observer. The standard Doppler formula is shown to be valid only in the geometric optics approximation. A new definition for the frequency is proposed, and the resulting formula for the frequency measured by the rotating observer is shown to be consistent with expectations based on the classical theory of electrons. A tentative quantum theory is developed on the basis of the generalization of the Bohr frequency condition to include accelerated observers. The description of the causal sequence of events is assumed to be independent of the motion of the observer. Furthermore, the quantum hypothesis is supposed to be valid for all observers. The implications of this theory are critically examined. The new formula for frequency, which is still based on the hypothesis of locality, leads to the observation of negative energy quanta by the rotating observer and is therefore in conflict with the quantum theory
Structural covariance networks in the mouse brain.
Pagani, Marco; Bifone, Angelo; Gozzi, Alessandro
2016-04-01
The presence of networks of correlation between regional gray matter volume as measured across subjects in a group of individuals has been consistently described in several human studies, an approach termed structural covariance MRI (scMRI). Complementary to prevalent brain mapping modalities like functional and diffusion-weighted imaging, the approach can provide precious insights into the mutual influence of trophic and plastic processes in health and pathological states. To investigate whether analogous scMRI networks are present in lower mammal species amenable to genetic and experimental manipulation such as the laboratory mouse, we employed high resolution morphoanatomical MRI in a large cohort of genetically-homogeneous wild-type mice (C57Bl6/J) and mapped scMRI networks using a seed-based approach. We show that the mouse brain exhibits robust homotopic scMRI networks in both primary and associative cortices, a finding corroborated by independent component analyses of cortical volumes. Subcortical structures also showed highly symmetric inter-hemispheric correlations, with evidence of distributed antero-posterior networks in diencephalic regions of the thalamus and hypothalamus. Hierarchical cluster analysis revealed six identifiable clusters of cortical and sub-cortical regions corresponding to previously described neuroanatomical systems. Our work documents the presence of homotopic cortical and subcortical scMRI networks in the mouse brain, thus supporting the use of this species to investigate the elusive biological and neuroanatomical underpinnings of scMRI network development and its derangement in neuropathological states. The identification of scMRI networks in genetically homogeneous inbred mice is consistent with the emerging view of a key role of environmental factors in shaping these correlational networks. Copyright © 2016 Elsevier Inc. All rights reserved.
Conservative Sample Size Determination for Repeated Measures Analysis of Covariance.
Morgan, Timothy M; Case, L Douglas
2013-07-05
In the design of a randomized clinical trial with one pre and multiple post randomized assessments of the outcome variable, one needs to account for the repeated measures in determining the appropriate sample size. Unfortunately, one seldom has a good estimate of the variance of the outcome measure, let alone the correlations among the measurements over time. We show how sample sizes can be calculated by making conservative assumptions regarding the correlations for a variety of covariance structures. The most conservative choice for the correlation depends on the covariance structure and the number of repeated measures. In the absence of good estimates of the correlations, the sample size is often based on a two-sample t-test, making the 'ultra' conservative and unrealistic assumption that there are zero correlations between the baseline and follow-up measures while at the same time assuming there are perfect correlations between the follow-up measures. Compared to the case of taking a single measurement, substantial savings in sample size can be realized by accounting for the repeated measures, even with very conservative assumptions regarding the parameters of the assumed correlation matrix. Assuming compound symmetry, the sample size from the two-sample t-test calculation can be reduced at least 44%, 56%, and 61% for repeated measures analysis of covariance by taking 2, 3, and 4 follow-up measures, respectively. The results offer a rational basis for determining a fairly conservative, yet efficient, sample size for clinical trials with repeated measures and a baseline value.
BASACF, Integral Neutron Spectra Adjustment and Dosimetry
International Nuclear Information System (INIS)
Tichy, Milos
1996-01-01
1 - Description of program or function: Adjustment of a neutron spectrum based on integral detector measurements and calculation of an integral dosimetric quantity (integral flux, d.p.a., dose equivalent) and its variance. The program requires measured data (activities and their covariance matrix) and a priori information (spectrum, dosimetry cross sections, integral quantity conversion factor and their covariance matrices). All a priori covariance matrices can be read in from a file prepared by some other code or can be generated by means of three different methods (by subroutines included in the program). A subroutine which can normalize the a priori flux to measured data is also included. The program provides also adjusted dosimetry cross sections (with covariance matrix) so that it can be used for an adjustment of cross sections (or response functions of e.g. Bonner balls) by measurements in well-known neutron spectra. 2 - Method of solution: Bayesian theorem on conditional probability applied to linearized relation between activities, dosimetry cross sections and flux. All probability distributions are supposed to be normal and this supposition leads to minimizing of the same functional as least squares method (STAY'SL). This task is solved by a covariance filter method which avoids any matrix inversion and is numerically robust and stable. 3 - Restrictions on the complexity of the problem: This version can use 45 energy groups and 5 detectors and occupies 310 kB of main memory. This restriction can be modified according to available memory. The covariance matrix of activities is supposed diagonal. A solution is produced for any set of input data but in the case of non-consistent data, when measured activities do not match the a priori flux, the solution is not very meaningful
ANGELO-LAMBDA, Covariance matrix interpolation and mathematical verification
International Nuclear Information System (INIS)
Kodeli, Ivo
2007-01-01
1 - Description of program or function: The codes ANGELO-2.3 and LAMBDA-2.3 are used for the interpolation of the cross section covariance data from the original to a user defined energy group structure, and for the mathematical tests of the matrices, respectively. The LAMBDA-2.3 code calculates the eigenvalues of the matrices (both for the original or the converted) and lists them accordingly into positive and negative matrices. This verification is strongly recommended before using any covariance matrices. These versions of the two codes are the extended versions of the previous codes available in the Packages NEA-1264 - ZZ-VITAMIN-J/COVA. They were specifically developed for the purposes of the OECD LWR UAM benchmark, in particular for the processing of the ZZ-SCALE5.1/COVA-44G cross section covariance matrix library retrieved from the SCALE-5.1 package. Either the original SCALE-5.1 libraries or the libraries separated into several files by Nuclides can be (in principle) processed by ANGELO/LAMBDA codes, but the use of the one-nuclide data is strongly recommended. Due to large deviations of the correlation matrix terms from unity observed in some SCALE5.1 covariance matrices, the previous more severe acceptance condition in the ANGELO2.3 code was released. In case the correlation coefficients exceed 1.0, only a warning message is issued, and coefficients are replaced by 1.0. 2 - Methods: ANGELO-2.3 interpolates the covariance matrices to a union grid using flat weighting. LAMBDA-2.3 code includes the mathematical routines to calculate the eigenvalues of the covariance matrices. 3 - Restrictions on the complexity of the problem: The algorithm used in ANGELO is relatively simple, therefore the interpolations involving energy group structure which are very different from the original (e.g. large difference in the number of energy groups) may not be accurate. In particular in the case of the MT=1018 data (fission spectra covariances) the algorithm may not be
Topics in data adjustment theory and applications
International Nuclear Information System (INIS)
Hwang, R.N.
1988-01-01
The methodologies of the uncertainty analysis and data adjustment have been well-developed and widely used abroad since the early 70's. With limited amount of covariance data on the differential cross section and the integral experiments available at the time, their accomplishments are, indeed, astounding. The fundamental adjustment equations, however, remain qualitatively unchanged. For the past few year, extensive efforts on these subjects have also begun at ANL in order to utilize the massive amount of integral experiments accumulated over years to provide the basis for improving the reactor parameters encountered in various design calculations. Pertinent covariance matrices and sensitivity matrices of the existing integral experiments have been evaluated and systematically compiled in the data files along with the cross section covariance data derived from the ENDF-B/V for the 21 group structure currently under consideration. A production code GMADJ that provides the adjusted quantities for a large number of cross section types has been developed by Poenitz for routine applications. The primary purpose of the present paper is to improve understanding of the application oriented issues important to the data adjustment theory and the subsequent usage of the adjusted quantities in the design calculations in support of these activities. 30 refs., 12 figs., 5 tabs
Globally covering a-priori regional gravity covariance models
Directory of Open Access Journals (Sweden)
D. Arabelos
2003-01-01
Full Text Available Gravity anomaly data generated using Wenzel’s GPM98A model complete to degree 1800, from which OSU91A has been subtracted, have been used to estimate covariance functions for a set of globally covering equal-area blocks of size 22.5° × 22.5° at Equator, having a 2.5° overlap. For each block an analytic covariance function model was determined. The models are based on 4 parameters: the depth to the Bjerhammar sphere (determines correlation, the free-air gravity anomaly variance, a scale factor of the OSU91A error degree-variances and a maximal summation index, N, of the error degree-variances. The depth of Bjerhammar-sphere varies from -134km to nearly zero, N varies from 360 to 40, the scale factor from 0.03 to 38.0 and the gravity variance from 1081 to 24(10µms-22. The parameters are interpreted in terms of the quality of the data used to construct OSU91A and GPM98A and general conditions such as the occurrence of mountain chains. The variation of the parameters show that it is necessary to use regional covariance models in order to obtain a realistic signal to noise ratio in global applications.Key words. GOCE mission, Covariance function, Spacewise approach`
A Small Guide to Generating Covariances of Experimental Data
International Nuclear Information System (INIS)
Mannhart, Wolf
2011-05-01
A complete description of the uncertainties of an experiment can only be realized by a detailed list of all the uncertainty components, their value and a specification of existing correlations between the data. Based on such information the covariance matrix can be generated, which is necessary for any further proceeding with the experimental data. It is not necessary, and not recommended, that an experimenter evaluates this covariance matrix. The reason for this is that a incorrectly evaluated final covariance matrix can never be corrected if the details are not given. (Such obviously wrong covariance matrices have recently occasionally been found in the literature). Hence quotation of a covariance matrix is an additional step which should not occur without quoting a detailed list of the various uncertainty components and their correlations as well. It must be hoped that editors of journals will understand these necessary requirements. The generalized least squares procedure shown permits an easy way of interchanging data D 0 with parameter estimates P. This means new data can easily be combined with an earlier evaluation. However, it must be mentioned that this is only valid as long as the new data have no correlation with any of the older data of the prior evaluation. Otherwise the old data which show correlation with new data have to be extracted from the evaluation and then, together with the new data and taking account of the correlation, have again to be added to the reduced evaluation. In most cases this step cannot be performed and the evaluation has to be completely redone. A partial way out is given if the evaluation is performed step by step and the results of each step are stored. Then the evaluation need only be repeated from the step which contains correlated data for the first time while all earlier steps remain unchanged. Finally it should be noted that the addition of a small set of new data to a prior evaluation consisting of a large number of
Parameters of the covariance function of galaxies
International Nuclear Information System (INIS)
Fesenko, B.I.; Onuchina, E.V.
1988-01-01
The two-point angular covariance functions for two samples of galaxies are considered using quick methods of analysis. It is concluded that in the previous investigations the amplitude of the covariance function in the Lick counts was overestimated and the rate of decrease of the function underestimated
Covariance Function for Nearshore Wave Assimilation Systems
2018-01-30
which is applicable for any spectral wave model. The four dimensional variational (4DVar) assimilation methods are based on the mathematical ...covariance can be modeled by a parameterized Gaussian function, for nearshore wave assimilation applications , the covariance function depends primarily on...SPECTRAL ACTION DENSITY, RESPECTIVELY. ............................ 5 FIGURE 2. TOP ROW: STATISTICAL ANALYSIS OF THE WAVE-FIELD PROPERTIES AT THE
Treatment Effects with Many Covariates and Heteroskedasticity
DEFF Research Database (Denmark)
Cattaneo, Matias D.; Jansson, Michael; Newey, Whitney K.
The linear regression model is widely used in empirical work in Economics. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroskedasticity. Our results...
Covariance and sensitivity data generation at ORNL
International Nuclear Information System (INIS)
Leal, L. C.; Derrien, H.; Larson, N. M.; Alpan, A.
2005-01-01
Covariance data are required to assess uncertainties in design parameters in several nuclear applications. The error estimation of calculated quantities relies on the nuclear data uncertainty information available in the basic nuclear data libraries, such as the US Evaluated Nuclear Data Library, ENDF/B. The uncertainty files in the ENDF/B library are obtained from the analysis of experimental data and are stored as variance and covariance data. In this paper we address the generation of covariance data in the resonance region done with the computer code SAMMY. SAMMY is used in the evaluation of the experimental data in the resolved and unresolved resonance energy regions. The data fitting of cross sections is based on the generalised least-squares formalism (Bayesian theory) together with the resonance formalism described by R-matrix theory. Two approaches are used in SAMMY for the generation of resonance parameter covariance data. In the evaluation process SAMMY generates a set of resonance parameters that fit the data, and, it provides the resonance parameter covariances. For resonance parameter evaluations where there are no resonance parameter covariance data available, the alternative is to use an approach called the 'retroactive' resonance parameter covariance generation. In this paper, we describe the application of the retroactive covariance generation approach for the gadolinium isotopes. (authors)
Position Error Covariance Matrix Validation and Correction
Frisbee, Joe, Jr.
2016-01-01
In order to calculate operationally accurate collision probabilities, the position error covariance matrices predicted at times of closest approach must be sufficiently accurate representations of the position uncertainties. This presentation will discuss why the Gaussian distribution is a reasonable expectation for the position uncertainty and how this assumed distribution type is used in the validation and correction of position error covariance matrices.
Quality Quantification of Evaluated Cross Section Covariances
International Nuclear Information System (INIS)
Varet, S.; Dossantos-Uzarralde, P.; Vayatis, N.
2015-01-01
Presently, several methods are used to estimate the covariance matrix of evaluated nuclear cross sections. Because the resulting covariance matrices can be different according to the method used and according to the assumptions of the method, we propose a general and objective approach to quantify the quality of the covariance estimation for evaluated cross sections. The first step consists in defining an objective criterion. The second step is computation of the criterion. In this paper the Kullback-Leibler distance is proposed for the quality quantification of a covariance matrix estimation and its inverse. It is based on the distance to the true covariance matrix. A method based on the bootstrap is presented for the estimation of this criterion, which can be applied with most methods for covariance matrix estimation and without the knowledge of the true covariance matrix. The full approach is illustrated on the 85 Rb nucleus evaluations and the results are then used for a discussion on scoring and Monte Carlo approaches for covariance matrix estimation of the cross section evaluations
Treating Sample Covariances for Use in Strongly Coupled Atmosphere-Ocean Data Assimilation
Smith, Polly J.; Lawless, Amos S.; Nichols, Nancy K.
2018-01-01
Strongly coupled data assimilation requires cross-domain forecast error covariances; information from ensembles can be used, but limited sampling means that ensemble derived error covariances are routinely rank deficient and/or ill-conditioned and marred by noise. Thus, they require modification before they can be incorporated into a standard assimilation framework. Here we compare methods for improving the rank and conditioning of multivariate sample error covariance matrices for coupled atmosphere-ocean data assimilation. The first method, reconditioning, alters the matrix eigenvalues directly; this preserves the correlation structures but does not remove sampling noise. We show that it is better to recondition the correlation matrix rather than the covariance matrix as this prevents small but dynamically important modes from being lost. The second method, model state-space localization via the Schur product, effectively removes sample noise but can dampen small cross-correlation signals. A combination that exploits the merits of each is found to offer an effective alternative.
On the algebraic structure of covariant anomalies and covariant Schwinger terms
International Nuclear Information System (INIS)
Kelnhofer, G.
1992-01-01
A cohomological characterization of covariant anomalies and covariant Schwinger terms in an anomalous Yang-Mills theory is formulated and w ill be geometrically interpreted. The BRS and anti-BRS transformations are defined as purely differential geometric objects. Finally the covariant descent equations are formulated within this context. (author)
Covariant diagrams for one-loop matching
International Nuclear Information System (INIS)
Zhang, Zhengkang
2016-10-01
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Covariant diagrams for one-loop matching
Energy Technology Data Exchange (ETDEWEB)
Zhang, Zhengkang [Michigan Univ., Ann Arbor, MI (United States). Michigan Center for Theoretical Physics; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)
2016-10-15
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gaugecovariant quantities and are thus dubbed ''covariant diagrams.'' The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
Familial aggregation and linkage analysis with covariates for metabolic syndrome risk factors.
Naseri, Parisa; Khodakarim, Soheila; Guity, Kamran; Daneshpour, Maryam S
2018-06-15
Mechanisms of metabolic syndrome (MetS) causation are complex, genetic and environmental factors are important factors for the pathogenesis of MetS In this study, we aimed to evaluate familial and genetic influences on metabolic syndrome risk factor and also assess association between FTO (rs1558902 and rs7202116) and CETP(rs1864163) genes' single nucleotide polymorphisms (SNP) with low HDL_C in the Tehran Lipid and Glucose Study (TLGS). The design was a cross-sectional study of 1776 members of 227 randomly-ascertained families. Selected families contained at least one affected metabolic syndrome and at least two members of the family had suffered a loss of HDL_C according to ATP III criteria. In this study, after confirming the familial aggregation with intra-trait correlation coefficients (ICC) of Metabolic syndrome (MetS) and the quantitative lipid traits, the genetic linkage analysis of HDL_C was performed using conditional logistic method with adjusted sex and age. The results of the aggregation analysis revealed a higher correlation between siblings than between parent-offspring pairs representing the role of genetic factors in MetS. In addition, the conditional logistic model with covariates showed that the linkage results between HDL_C and three marker, rs1558902, rs7202116 and rs1864163 were significant. In summary, a high risk of MetS was found in siblings confirming the genetic influences of metabolic syndrome risk factor. Moreover, the power to detect linkage increases in the one parameter conditional logistic model regarding the use of age and sex as covariates. Copyright © 2018. Published by Elsevier B.V.
An alternative covariance estimator to investigate genetic heterogeneity in populations.
Heslot, Nicolas; Jannink, Jean-Luc
2015-11-26
For genomic prediction and genome-wide association studies (GWAS) using mixed models, covariance between individuals is estimated using molecular markers. Based on the properties of mixed models, using available molecular data for prediction is optimal if this covariance is known. Under this assumption, adding individuals to the analysis should never be detrimental. However, some empirical studies showed that increasing training population size decreased prediction accuracy. Recently, results from theoretical models indicated that even if marker density is high and the genetic architecture of traits is controlled by many loci with small additive effects, the covariance between individuals, which depends on relationships at causal loci, is not always well estimated by the whole-genome kinship. We propose an alternative covariance estimator named K-kernel, to account for potential genetic heterogeneity between populations that is characterized by a lack of genetic correlation, and to limit the information flow between a priori unknown populations in a trait-specific manner. This is similar to a multi-trait model and parameters are estimated by REML and, in extreme cases, it can allow for an independent genetic architecture between populations. As such, K-kernel is useful to study the problem of the design of training populations. K-kernel was compared to other covariance estimators or kernels to examine its fit to the data, cross-validated accuracy and suitability for GWAS on several datasets. It provides a significantly better fit to the data than the genomic best linear unbiased prediction model and, in some cases it performs better than other kernels such as the Gaussian kernel, as shown by an empirical null distribution. In GWAS simulations, alternative kernels control type I errors as well as or better than the classical whole-genome kinship and increase statistical power. No or small gains were observed in cross-validated prediction accuracy. This alternative
Mikosch, Jochen; Patchkovskii, Serguei
2013-10-01
We use an analytical theory of noisy Poisson processes, developed in the preceding companion publication, to compare coincidence and covariance measurement approaches in photoelectron and -ion spectroscopy. For non-unit detection efficiencies, coincidence data acquisition (DAQ) suffers from false coincidences. The rate of false coincidences grows quadratically with the rate of elementary ionization events. To minimize false coincidences for rare event outcomes, very low event rates may hence be required. Coincidence measurements exhibit high tolerance to noise introduced by unstable experimental conditions. Covariance DAQ on the other hand is free of systematic errors as long as stable experimental conditions are maintained. In the presence of noise, all channels in a covariance measurement become correlated. Under favourable conditions, covariance DAQ may allow orders of magnitude reduction in measurement times. Finally, we use experimental data for strong-field ionization of 1,3-butadiene to illustrate how fluctuations in experimental conditions can contaminate a covariance measurement, and how such contamination can be detected.
ARMA Cholesky Factor Models for the Covariance Matrix of Linear Models.
Lee, Keunbaik; Baek, Changryong; Daniels, Michael J
2017-11-01
In longitudinal studies, serial dependence of repeated outcomes must be taken into account to make correct inferences on covariate effects. As such, care must be taken in modeling the covariance matrix. However, estimation of the covariance matrix is challenging because there are many parameters in the matrix and the estimated covariance matrix should be positive definite. To overcomes these limitations, two Cholesky decomposition approaches have been proposed: modified Cholesky decomposition for autoregressive (AR) structure and moving average Cholesky decomposition for moving average (MA) structure, respectively. However, the correlations of repeated outcomes are often not captured parsimoniously using either approach separately. In this paper, we propose a class of flexible, nonstationary, heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the covariance matrix that we denote as ARMACD. We analyze a recent lung cancer study to illustrate the power of our proposed methods.
ERRORJ, Multigroup covariance matrices generation from ENDF-6 format
International Nuclear Information System (INIS)
Chiba, Go
2007-01-01
1 - Description of program or function: ERRORJ produces multigroup covariance matrices from ENDF-6 format following mainly the methods of the ERRORR module in NJOY94.105. New version differs from previous version in the following features: Additional features in ERRORJ with respect to the NJOY94.105/ERRORR module: - expands processing for the covariance matrices of resolved and unresolved resonance parameters; - processes average cosine of scattering angle and fission spectrum; - treats cross-correlation between different materials and reactions; - accepts input of multigroup constants with various forms (user input, GENDF, etc.); - outputs files with various formats through utility NJOYCOVX (COVERX format, correlation matrix, relative error and standard deviation); - uses a 1% sensitivity method for processing of resonance parameters; - ERRORJ can process the JENDL-3.2 and 3.3 covariance matrices. Additional features of the version 2 with respect to the previous version of ERRORJ: - Since the release of version 2, ERRORJ has been modified to increase its reliability and stability, - calculation of the correlation coefficients in the resonance region, - Option for high-speed calculation is implemented, - Perturbation amount is optimised in a sensitivity calculation, - Effect of the resonance self-shielding can be considered, - a compact covariance format (LCOMP=2) proposed by N. M. Larson can be read. Additional features of the version 2.2.1 with respect to the previous version of ERRORJ: - Several routines were modified to reduce calculation time. The new one needs shorter calculation time (50-70%) than the old version without changing results. - In the U-233 and Pu-241 files of JENDL-3.3 an inconsistency between resonance parameters in MF=32 and those in MF=2 was corrected. NEA-1676/06: This version differs from the previous one (NEA-1676/05) in the following: ERRORJ2.2.1 was modified to treat the self-shielding effect accurately. NEA-1676/07: This version
Selecting groups of covariates in the elastic net
DEFF Research Database (Denmark)
Clemmensen, Line Katrine Harder
This paper introduces a novel method to select groups of variables in sparse regression and classication settings. The groups are formed based on the correlations between covariates and ensure that for example spatial or spectral relations are preserved without explicitly coding for these....... The preservation of relations gives increased interpretability. The method is based on the elastic net and adaptively selects highly correlated groups of variables and does therefore not waste time in grouping irrelevant variables for the problem at hand. The method is illustrated on a simulated data set...
Super-sample covariance approximations and partial sky coverage
Lacasa, Fabien; Lima, Marcos; Aguena, Michel
2018-04-01
Super-sample covariance (SSC) is the dominant source of statistical error on large scale structure (LSS) observables for both current and future galaxy surveys. In this work, we concentrate on the SSC of cluster counts, also known as sample variance, which is particularly useful for the self-calibration of the cluster observable-mass relation; our approach can similarly be applied to other observables, such as galaxy clustering and lensing shear. We first examined the accuracy of two analytical approximations proposed in the literature for the flat sky limit, finding that they are accurate at the 15% and 30-35% level, respectively, for covariances of counts in the same redshift bin. We then developed a harmonic expansion formalism that allows for the prediction of SSC in an arbitrary survey mask geometry, such as large sky areas of current and future surveys. We show analytically and numerically that this formalism recovers the full sky and flat sky limits present in the literature. We then present an efficient numerical implementation of the formalism, which allows fast and easy runs of covariance predictions when the survey mask is modified. We applied our method to a mask that is broadly similar to the Dark Energy Survey footprint, finding a non-negligible negative cross-z covariance, i.e. redshift bins are anti-correlated. We also examined the case of data removal from holes due to, for example bright stars, quality cuts, or systematic removals, and find that this does not have noticeable effects on the structure of the SSC matrix, only rescaling its amplitude by the effective survey area. These advances enable analytical covariances of LSS observables to be computed for current and future galaxy surveys, which cover large areas of the sky where the flat sky approximation fails.
Covariant quantizations in plane and curved spaces
International Nuclear Information System (INIS)
Assirati, J.L.M.; Gitman, D.M.
2017-01-01
We present covariant quantization rules for nonsingular finite-dimensional classical theories with flat and curved configuration spaces. In the beginning, we construct a family of covariant quantizations in flat spaces and Cartesian coordinates. This family is parametrized by a function ω(θ), θ element of (1,0), which describes an ambiguity of the quantization. We generalize this construction presenting covariant quantizations of theories with flat configuration spaces but already with arbitrary curvilinear coordinates. Then we construct a so-called minimal family of covariant quantizations for theories with curved configuration spaces. This family of quantizations is parametrized by the same function ω(θ). Finally, we describe a more wide family of covariant quantizations in curved spaces. This family is already parametrized by two functions, the previous one ω(θ) and by an additional function Θ(x,ξ). The above mentioned minimal family is a part at Θ = 1 of the wide family of quantizations. We study constructed quantizations in detail, proving their consistency and covariance. As a physical application, we consider a quantization of a non-relativistic particle moving in a curved space, discussing the problem of a quantum potential. Applying the covariant quantizations in flat spaces to an old problem of constructing quantum Hamiltonian in polar coordinates, we directly obtain a correct result. (orig.)
Covariant quantizations in plane and curved spaces
Energy Technology Data Exchange (ETDEWEB)
Assirati, J.L.M. [University of Sao Paulo, Institute of Physics, Sao Paulo (Brazil); Gitman, D.M. [Tomsk State University, Department of Physics, Tomsk (Russian Federation); P.N. Lebedev Physical Institute, Moscow (Russian Federation); University of Sao Paulo, Institute of Physics, Sao Paulo (Brazil)
2017-07-15
We present covariant quantization rules for nonsingular finite-dimensional classical theories with flat and curved configuration spaces. In the beginning, we construct a family of covariant quantizations in flat spaces and Cartesian coordinates. This family is parametrized by a function ω(θ), θ element of (1,0), which describes an ambiguity of the quantization. We generalize this construction presenting covariant quantizations of theories with flat configuration spaces but already with arbitrary curvilinear coordinates. Then we construct a so-called minimal family of covariant quantizations for theories with curved configuration spaces. This family of quantizations is parametrized by the same function ω(θ). Finally, we describe a more wide family of covariant quantizations in curved spaces. This family is already parametrized by two functions, the previous one ω(θ) and by an additional function Θ(x,ξ). The above mentioned minimal family is a part at Θ = 1 of the wide family of quantizations. We study constructed quantizations in detail, proving their consistency and covariance. As a physical application, we consider a quantization of a non-relativistic particle moving in a curved space, discussing the problem of a quantum potential. Applying the covariant quantizations in flat spaces to an old problem of constructing quantum Hamiltonian in polar coordinates, we directly obtain a correct result. (orig.)
Weak lensing of the cosmic microwave background: Power spectrum covariance
International Nuclear Information System (INIS)
Cooray, Asantha
2002-01-01
We discuss the non-Gaussian contribution to the power spectrum covariance of cosmic microwave background (CMB) anisotropies resulting through weak gravitational lensing angular deflections and the correlation of deflections with secondary sources of temperature fluctuations generated by the large scale structure, such as the integrated Sachs-Wolfe effect and the Sunyaev-Zel'dovich effect. This additional contribution to the covariance of binned angular power spectrum, beyond the well known cosmic variance and any associated instrumental noise, results from a trispectrum, or a four point correlation function, in temperature anisotropy data. With substantially wide bins in multipole space, the resulting non-Gaussian contribution from lensing to the binned power spectrum variance is insignificant out to multipoles of a few thousand and is not likely to affect the cosmological parameter estimation with acoustic peaks and the damping tail. The non-Gaussian contribution to covariance, however, should be considered when interpreting binned CMB power spectrum measurements at multipoles of a few thousand corresponding to angular scales of few arcminutes and less
A New Bias Corrected Version of Heteroscedasticity Consistent Covariance Estimator
Directory of Open Access Journals (Sweden)
Munir Ahmed
2016-06-01
Full Text Available In the presence of heteroscedasticity, different available flavours of the heteroscedasticity consistent covariance estimator (HCCME are used. However, the available literature shows that these estimators can be considerably biased in small samples. Cribari–Neto et al. (2000 introduce a bias adjustment mechanism and give the modified White estimator that becomes almost bias-free even in small samples. Extending these results, Cribari-Neto and Galvão (2003 present a similar bias adjustment mechanism that can be applied to a wide class of HCCMEs’. In the present article, we follow the same mechanism as proposed by Cribari-Neto and Galvão to give bias-correction version of HCCME but we use adaptive HCCME rather than the conventional HCCME. The Monte Carlo study is used to evaluate the performance of our proposed estimators.
Yee, Yohan; Fernandes, Darren J; French, Leon; Ellegood, Jacob; Cahill, Lindsay S; Vousden, Dulcie A; Spencer Noakes, Leigh; Scholz, Jan; van Eede, Matthijs C; Nieman, Brian J; Sled, John G; Lerch, Jason P
2018-05-18
An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the
DANTE, Activation Analysis Neutron Spectra Unfolding by Covariance Matrix Method
International Nuclear Information System (INIS)
Petilli, M.
1981-01-01
1 - Description of problem or function: The program evaluates activation measurements of reactor neutron spectra and unfolds the results for dosimetry purposes. Different evaluation options are foreseen: absolute or relative fluxes and different iteration algorithms. 2 - Method of solution: A least-square fit method is used. A correlation between available data and their uncertainties has been introduced by means of flux and activity variance-covariance matrices. Cross sections are assumed to be constant, i.e. with variance-covariance matrix equal to zero. The Lagrange multipliers method has been used for calculating the solution. 3 - Restrictions on the complexity of the problem: 9 activation experiments can be analyzed. 75 energy groups are accepted
Students’ Covariational Reasoning in Solving Integrals’ Problems
Harini, N. V.; Fuad, Y.; Ekawati, R.
2018-01-01
Covariational reasoning plays an important role to indicate quantities vary in learning calculus. This study investigates students’ covariational reasoning during their studies concerning two covarying quantities in integral problem. Six undergraduate students were chosen to solve problems that involved interpreting and representing how quantities change in tandem. Interviews were conducted to reveal the students’ reasoning while solving covariational problems. The result emphasizes that undergraduate students were able to construct the relation of dependent variables that changes in tandem with the independent variable. However, students faced difficulty in forming images of continuously changing rates and could not accurately apply the concept of integrals. These findings suggest that learning calculus should be increased emphasis on coordinating images of two quantities changing in tandem about instantaneously rate of change and to promote conceptual knowledge in integral techniques.
Covariant Quantization with Extended BRST Symmetry
Geyer, B.; Gitman, D. M.; Lavrov, P. M.
1999-01-01
A short rewiev of covariant quantization methods based on BRST-antiBRST symmetry is given. In particular problems of correct definition of Sp(2) symmetric quantization scheme known as triplectic quantization are considered.
Covariant extensions and the nonsymmetric unified field
International Nuclear Information System (INIS)
Borchsenius, K.
1976-01-01
The problem of generally covariant extension of Lorentz invariant field equations, by means of covariant derivatives extracted from the nonsymmetric unified field, is considered. It is shown that the contracted curvature tensor can be expressed in terms of a covariant gauge derivative which contains the gauge derivative corresponding to minimal coupling, if the universal constant p, characterizing the nonsymmetric theory, is fixed in terms of Planck's constant and the elementary quantum of charge. By this choice the spinor representation of the linear connection becomes closely related to the spinor affinity used by Infeld and Van Der Waerden (Sitzungsber. Preuss. Akad. Wiss. Phys. Math. Kl.; 9:380 (1933)) in their generally covariant formulation of Dirac's equation. (author)
Covariant amplitudes in Polyakov string theory
International Nuclear Information System (INIS)
Aoyama, H.; Dhar, A.; Namazie, M.A.
1986-01-01
A manifestly Lorentz-covariant and reparametrization-invariant procedure for computing string amplitudes using Polyakov's formulation is described. Both bosonic and superstring theories are dealt with. The computation of string amplitudes is greatly facilitated by this formalism. (orig.)
Covariance upperbound controllers for networked control systems
International Nuclear Information System (INIS)
Ko, Sang Ho
2012-01-01
This paper deals with designing covariance upperbound controllers for a linear system that can be used in a networked control environment in which control laws are calculated in a remote controller and transmitted through a shared communication link to the plant. In order to compensate for possible packet losses during the transmission, two different techniques are often employed: the zero-input and the hold-input strategy. These use zero input and the latest control input, respectively, when a packet is lost. For each strategy, we synthesize a class of output covariance upperbound controllers for a given covariance upperbound and a packet loss probability. Existence conditions of the covariance upperbound controller are also provided for each strategy. Through numerical examples, performance of the two strategies is compared in terms of feasibility of implementing the controllers
Covariance data evaluation for experimental data
International Nuclear Information System (INIS)
Liu Tingjin
1993-01-01
Some methods and codes have been developed and utilized for covariance data evaluation of experimental data, including parameter analysis, physical analysis, Spline fitting etc.. These methods and codes can be used in many different cases
Earth Observing System Covariance Realism Updates
Ojeda Romero, Juan A.; Miguel, Fred
2017-01-01
This presentation will be given at the International Earth Science Constellation Mission Operations Working Group meetings June 13-15, 2017 to discuss the Earth Observing System Covariance Realism updates.
Laser Covariance Vibrometry for Unsymmetrical Mode Detection
National Research Council Canada - National Science Library
Kobold, Michael C
2006-01-01
Simulated cross - spectral covariance (CSC) from optical return from simulated surface vibration indicates CW phase modulation may be an appropriate phenomenology for adequate classification of vehicles by structural mode...
Error Covariance Estimation of Mesoscale Data Assimilation
National Research Council Canada - National Science Library
Xu, Qin
2005-01-01
The goal of this project is to explore and develop new methods of error covariance estimation that will provide necessary statistical descriptions of prediction and observation errors for mesoscale data assimilation...
Heteroscedasticity resistant robust covariance matrix estimator
Czech Academy of Sciences Publication Activity Database
Víšek, Jan Ámos
2010-01-01
Roč. 17, č. 27 (2010), s. 33-49 ISSN 1212-074X Grant - others:GA UK(CZ) GA402/09/0557 Institutional research plan: CEZ:AV0Z10750506 Keywords : Regression * Covariance matrix * Heteroscedasticity * Resistant Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2011/SI/visek-heteroscedasticity resistant robust covariance matrix estimator.pdf
Phase-covariant quantum cloning of qudits
International Nuclear Information System (INIS)
Fan Heng; Imai, Hiroshi; Matsumoto, Keiji; Wang, Xiang-Bin
2003-01-01
We study the phase-covariant quantum cloning machine for qudits, i.e., the input states in a d-level quantum system have complex coefficients with arbitrary phase but constant module. A cloning unitary transformation is proposed. After optimizing the fidelity between input state and single qudit reduced density operator of output state, we obtain the optimal fidelity for 1 to 2 phase-covariant quantum cloning of qudits and the corresponding cloning transformation
Noncommutative Gauge Theory with Covariant Star Product
International Nuclear Information System (INIS)
Zet, G.
2010-01-01
We present a noncommutative gauge theory with covariant star product on a space-time with torsion. In order to obtain the covariant star product one imposes some restrictions on the connection of the space-time. Then, a noncommutative gauge theory is developed applying this product to the case of differential forms. Some comments on the advantages of using a space-time with torsion to describe the gravitational field are also given.
Covariant phase difference observables in quantum mechanics
International Nuclear Information System (INIS)
Heinonen, Teiko; Lahti, Pekka; Pellonpaeae, Juha-Pekka
2003-01-01
Covariant phase difference observables are determined in two different ways, by a direct computation and by a group theoretical method. A characterization of phase difference observables which can be expressed as the difference of two phase observables is given. The classical limits of such phase difference observables are determined and the Pegg-Barnett phase difference distribution is obtained from the phase difference representation. The relation of Ban's theory to the covariant phase theories is exhibited
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-07
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-05
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Covariate analysis of bivariate survival data
Energy Technology Data Exchange (ETDEWEB)
Bennett, L.E.
1992-01-01
The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methods have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul
2015-01-01
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander; Genton, Marc G.; Sun, Ying; Tempone, Raul
2015-01-01
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
Covariant perturbations of Schwarzschild black holes
International Nuclear Information System (INIS)
Clarkson, Chris A; Barrett, Richard K
2003-01-01
We present a new covariant and gauge-invariant perturbation formalism for dealing with spacetimes having spherical symmetry (or some preferred spatial direction) in the background, and apply it to the case of gravitational wave propagation in a Schwarzschild black-hole spacetime. The 1 + 3 covariant approach is extended to a '1 + 1 + 2 covariant sheet' formalism by introducing a radial unit vector in addition to the timelike congruence, and decomposing all covariant quantities with respect to this. The background Schwarzschild solution is discussed and a covariant characterization is given. We give the full first-order system of linearized 1 + 1 + 2 covariant equations, and we show how, by introducing (time and spherical) harmonic functions, these may be reduced to a system of first-order ordinary differential equations and algebraic constraints for the 1 + 1 + 2 variables which may be solved straightforwardly. We show how both odd- and even-parity perturbations may be unified by the discovery of a covariant, frame- and gauge-invariant, transverse-traceless tensor describing gravitational waves, which satisfies a covariant wave equation equivalent to the Regge-Wheeler equation for both even- and odd-parity perturbations. We show how the Zerilli equation may be derived from this tensor, and derive a similar transverse-traceless tensor equation equivalent to this equation. The so-called special quasinormal modes with purely imaginary frequency emerge naturally. The significance of the degrees of freedom in the choice of the two frame vectors is discussed, and we demonstrate that, for a certain frame choice, the underlying dynamics is governed purely by the Regge-Wheeler tensor. The two transverse-traceless Weyl tensors which carry the curvature of gravitational waves are discussed, and we give the closed system of four first-order ordinary differential equations describing their propagation. Finally, we consider the extension of this work to the study of
PSI collapse and relativistic covariance
International Nuclear Information System (INIS)
Costa de Beauregard, Olivier
1980-01-01
We call macrorelativistic a theory invariant under the orthochronous Lorentz group and obeying the 'factlike' principle of retarded causality, and microrelativistic a theory invariant under the full Lorentz group and CPT symmetric. The Einstein correlations either direct (non-separability of measurements issuing from a common preparation) or reversed (non-separability of preparations producing a common measurement) are incompatible with the macro-, but compatible with the microrelativity. We assume that fundamental physics is fully Lorentz and CPT invariant (the transition to macrophysics introducing a 'factlike asymmetry) and consequently define the collapse-and-retrocollapse concept [fr
International Nuclear Information System (INIS)
Wagschal, J.J.; Maerker, R.E.; Gilliam, D.M.
1979-01-01
Integral measurements together with accompanying uncertainty estimates have been used for the past fifteen years in cross section adjustments. As the field of cross section adjustment came of age, the crude uncertainty estimates were replaced - only in principle, initially - by a quantitative cross section uncertainty covariance description and by uncertainty correlations of integral experiments. There is current interest in the fission reaction rate ratio measurements in the NBS standard neutron fields by people involved in fast reactor cross sections. Also those in the LWR pressure vessel surveillance dosimetry program are interested in these measurements and in similar measurements performed in the Oak Ridge Pool Critical Assembly (PCA). A careful re-examination of uncertainty analysis is presented
Gosho, Masahiko; Hirakawa, Akihiro; Noma, Hisashi; Maruo, Kazushi; Sato, Yasunori
2017-10-01
In longitudinal clinical trials, some subjects will drop out before completing the trial, so their measurements towards the end of the trial are not obtained. Mixed-effects models for repeated measures (MMRM) analysis with "unstructured" (UN) covariance structure are increasingly common as a primary analysis for group comparisons in these trials. Furthermore, model-based covariance estimators have been routinely used for testing the group difference and estimating confidence intervals of the difference in the MMRM analysis using the UN covariance. However, using the MMRM analysis with the UN covariance could lead to convergence problems for numerical optimization, especially in trials with a small-sample size. Although the so-called sandwich covariance estimator is robust to misspecification of the covariance structure, its performance deteriorates in settings with small-sample size. We investigated the performance of the sandwich covariance estimator and covariance estimators adjusted for small-sample bias proposed by Kauermann and Carroll ( J Am Stat Assoc 2001; 96: 1387-1396) and Mancl and DeRouen ( Biometrics 2001; 57: 126-134) fitting simpler covariance structures through a simulation study. In terms of the type 1 error rate and coverage probability of confidence intervals, Mancl and DeRouen's covariance estimator with compound symmetry, first-order autoregressive (AR(1)), heterogeneous AR(1), and antedependence structures performed better than the original sandwich estimator and Kauermann and Carroll's estimator with these structures in the scenarios where the variance increased across visits. The performance based on Mancl and DeRouen's estimator with these structures was nearly equivalent to that based on the Kenward-Roger method for adjusting the standard errors and degrees of freedom with the UN structure. The model-based covariance estimator with the UN structure under unadjustment of the degrees of freedom, which is frequently used in applications
A special covariance structure for random coefficient models with both between and within covariates
International Nuclear Information System (INIS)
Riedel, K.S.
1990-07-01
We review random coefficient (RC) models in linear regression and propose a bias correction to the maximum likelihood (ML) estimator. Asymmptotic expansion of the ML equations are given when the between individual variance is much larger or smaller than the variance from within individual fluctuations. The standard model assumes all but one covariate varies within each individual, (we denote the within covariates by vector χ 1 ). We consider random coefficient models where some of the covariates do not vary in any single individual (we denote the between covariates by vector χ 0 ). The regression coefficients, vector β k , can only be estimated in the subspace X k of X. Thus the number of individuals necessary to estimate vector β and the covariance matrix Δ of vector β increases significantly in the presence of more than one between covariate. When the number of individuals is sufficient to estimate vector β but not the entire matrix Δ , additional assumptions must be imposed on the structure of Δ. A simple reduced model is that the between component of vector β is fixed and only the within component varies randomly. This model fails because it is not invariant under linear coordinate transformations and it can significantly overestimate the variance of new observations. We propose a covariance structure for Δ without these difficulties by first projecting the within covariates onto the space perpendicular to be between covariates. (orig.)
Exploiting Data Sparsity In Covariance Matrix Computations on Heterogeneous Systems
Charara, Ali M.
2018-05-24
Covariance matrices are ubiquitous in computational sciences, typically describing the correlation of elements of large multivariate spatial data sets. For example, covari- ance matrices are employed in climate/weather modeling for the maximum likelihood estimation to improve prediction, as well as in computational ground-based astronomy to enhance the observed image quality by filtering out noise produced by the adap- tive optics instruments and atmospheric turbulence. The structure of these covariance matrices is dense, symmetric, positive-definite, and often data-sparse, therefore, hier- archically of low-rank. This thesis investigates the performance limit of dense matrix computations (e.g., Cholesky factorization) on covariance matrix problems as the number of unknowns grows, and in the context of the aforementioned applications. We employ recursive formulations of some of the basic linear algebra subroutines (BLAS) to accelerate the covariance matrix computation further, while reducing data traffic across the memory subsystems layers. However, dealing with large data sets (i.e., covariance matrices of billions in size) can rapidly become prohibitive in memory footprint and algorithmic complexity. Most importantly, this thesis investigates the tile low-rank data format (TLR), a new compressed data structure and layout, which is valuable in exploiting data sparsity by approximating the operator. The TLR com- pressed data structure allows approximating the original problem up to user-defined numerical accuracy. This comes at the expense of dealing with tasks with much lower arithmetic intensities than traditional dense computations. In fact, this thesis con- solidates the two trends of dense and data-sparse linear algebra for HPC. Not only does the thesis leverage recursive formulations for dense Cholesky-based matrix al- gorithms, but it also implements a novel TLR-Cholesky factorization using batched linear algebra operations to increase hardware occupancy and
Bayesian source term determination with unknown covariance of measurements
Belal, Alkomiet; Tichý, Ondřej; Šmídl, Václav
2017-04-01
Determination of a source term of release of a hazardous material into the atmosphere is a very important task for emergency response. We are concerned with the problem of estimation of the source term in the conventional linear inverse problem, y = Mx, where the relationship between the vector of observations y is described using the source-receptor-sensitivity (SRS) matrix M and the unknown source term x. Since the system is typically ill-conditioned, the problem is recast as an optimization problem minR,B(y - Mx)TR-1(y - Mx) + xTB-1x. The first term minimizes the error of the measurements with covariance matrix R, and the second term is a regularization of the source term. There are different types of regularization arising for different choices of matrices R and B, for example, Tikhonov regularization assumes covariance matrix B as the identity matrix multiplied by scalar parameter. In this contribution, we adopt a Bayesian approach to make inference on the unknown source term x as well as unknown R and B. We assume prior on x to be a Gaussian with zero mean and unknown diagonal covariance matrix B. The covariance matrix of the likelihood R is also unknown. We consider two potential choices of the structure of the matrix R. First is the diagonal matrix and the second is a locally correlated structure using information on topology of the measuring network. Since the inference of the model is intractable, iterative variational Bayes algorithm is used for simultaneous estimation of all model parameters. The practical usefulness of our contribution is demonstrated on an application of the resulting algorithm to real data from the European Tracer Experiment (ETEX). This research is supported by EEA/Norwegian Financial Mechanism under project MSMT-28477/2014 Source-Term Determination of Radionuclide Releases by Inverse Atmospheric Dispersion Modelling (STRADI).
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix
Hu, Zongliang
2017-09-27
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix.
Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun
2017-09-21
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix
Hu, Zongliang; Dong, Kai; Dai, Wenlin; Tong, Tiejun
2017-01-01
The determinant of the covariance matrix for high-dimensional data plays an important role in statistical inference and decision. It has many real applications including statistical tests and information theory. Due to the statistical and computational challenges with high dimensionality, little work has been proposed in the literature for estimating the determinant of high-dimensional covariance matrix. In this paper, we estimate the determinant of the covariance matrix using some recent proposals for estimating high-dimensional covariance matrix. Specifically, we consider a total of eight covariance matrix estimation methods for comparison. Through extensive simulation studies, we explore and summarize some interesting comparison results among all compared methods. We also provide practical guidelines based on the sample size, the dimension, and the correlation of the data set for estimating the determinant of high-dimensional covariance matrix. Finally, from a perspective of the loss function, the comparison study in this paper may also serve as a proxy to assess the performance of the covariance matrix estimation.
Recent Advances with the AMPX Covariance Processing Capabilities in PUFF-IV
International Nuclear Information System (INIS)
Wiarda, Dorothea; Arbanas, Goran; Leal, Luiz C.; Dunn, Michael E.
2008-01-01
The program PUFF-IV is used to process resonance parameter covariance information given in ENDF/B File 32 and point-wise covariance matrices given in ENDF/B File 33 into group-averaged covariances matrices on a user-supplied group structure. For large resonance covariance matrices, found for example in 235U, the execution time of PUFF-IV can be quite long. Recently the code was modified to take advandage of Basic Linear Algebra Subprograms (BLAS) routines for the most time-consuming matrix multiplications. This led to a substantial decrease in execution time. This faster processing capability allowed us to investigate the conversion of File 32 data into File 33 data using a larger number of user-defined groups. While conversion substantially reduces the ENDF/B file size requirements for evaluations with a large number of resonances, a trade-off is made between the number of groups used to represent the resonance parameter covariance as a point-wise covariance matrix and the file size. We are also investigating a hybrid version of the conversion, in which the low-energy part of the File 32 resonance parameter covariances matrix is retained and the correlations with higher energies as well as the high energy part are given in File 33.
Cross-covariance functions for multivariate geostatistics
Genton, Marc G.
2015-05-01
Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
Schroedinger covariance states in anisotropic waveguides
International Nuclear Information System (INIS)
Angelow, A.; Trifonov, D.
1995-03-01
In this paper Squeezed and Covariance States based on Schroedinger inequality and their connection with other nonclassical states are considered for particular case of anisotropic waveguide in LiNiO 3 . Here, the problem of photon creation and generation of squeezed and Schroedinger covariance states in optical waveguides is solved in two steps: 1. Quantization of electromagnetic field is provided in the presence of dielectric waveguide using normal-mode expansion. The photon creation and annihilation operators are introduced, expanding the solution A-vector(r-vector,t) in a series in terms of the Sturm - Liouville mode-functions. 2. In terms of these operators the Hamiltonian of the field in a nonlinear waveguide is derived. For such Hamiltonian we construct the covariance states as stable (with nonzero covariance), which minimize the Schroedinger uncertainty relation. The evolutions of the three second momenta of q-circumflex j and p-circumflex j are calculated. For this Hamiltonian all three momenta are expressed in terms of one real parameters s only. It is found out how covariance, via this parameter s, depends on the waveguide profile n(x,y), on the mode-distributions u-vector j (x,y), and on the waveguide phase mismatching Δβ. (author). 37 refs
Form of the manifestly covariant Lagrangian
Johns, Oliver Davis
1985-10-01
The preferred form for the manifestly covariant Lagrangian function of a single, charged particle in a given electromagnetic field is the subject of some disagreement in the textbooks. Some authors use a ``homogeneous'' Lagrangian and others use a ``modified'' form in which the covariant Hamiltonian function is made to be nonzero. We argue in favor of the ``homogeneous'' form. We show that the covariant Lagrangian theories can be understood only if one is careful to distinguish quantities evaluated on the varied (in the sense of the calculus of variations) world lines from quantities evaluated on the unvaried world lines. By making this distinction, we are able to derive the Hamilton-Jacobi and Klein-Gordon equations from the ``homogeneous'' Lagrangian, even though the covariant Hamiltonian function is identically zero on all world lines. The derivation of the Klein-Gordon equation in particular gives Lagrangian theoretical support to the derivations found in standard quantum texts, and is also shown to be consistent with the Feynman path-integral method. We conclude that the ``homogeneous'' Lagrangian is a completely adequate basis for covariant Lagrangian theory both in classical and quantum mechanics. The article also explores the analogy with the Fermat theorem of optics, and illustrates a simple invariant notation for the Lagrangian and other four-vector equations.
Cross-covariance functions for multivariate geostatistics
Genton, Marc G.; Kleiber, William
2015-01-01
Continuously indexed datasets with multiple variables have become ubiquitous in the geophysical, ecological, environmental and climate sciences, and pose substantial analysis challenges to scientists and statisticians. For many years, scientists developed models that aimed at capturing the spatial behavior for an individual process; only within the last few decades has it become commonplace to model multiple processes jointly. The key difficulty is in specifying the cross-covariance function, that is, the function responsible for the relationship between distinct variables. Indeed, these cross-covariance functions must be chosen to be consistent with marginal covariance functions in such a way that the second-order structure always yields a nonnegative definite covariance matrix. We review the main approaches to building cross-covariance models, including the linear model of coregionalization, convolution methods, the multivariate Matérn and nonstationary and space-time extensions of these among others. We additionally cover specialized constructions, including those designed for asymmetry, compact support and spherical domains, with a review of physics-constrained models. We illustrate select models on a bivariate regional climate model output example for temperature and pressure, along with a bivariate minimum and maximum temperature observational dataset; we compare models by likelihood value as well as via cross-validation co-kriging studies. The article closes with a discussion of unsolved problems. © Institute of Mathematical Statistics, 2015.
Convex Banding of the Covariance Matrix.
Bien, Jacob; Bunea, Florentina; Xiao, Luo
2016-01-01
We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which the variables have a known ordering. Our estimator, which is the solution to a convex optimization problem, is equivalently expressed as an estimator which tapers the sample covariance matrix by a Toeplitz, sparsely-banded, data-adaptive matrix. As a result of this adaptivity, the convex banding estimator enjoys theoretical optimality properties not attained by previous banding or tapered estimators. In particular, our convex banding estimator is minimax rate adaptive in Frobenius and operator norms, up to log factors, over commonly-studied classes of covariance matrices, and over more general classes. Furthermore, it correctly recovers the bandwidth when the true covariance is exactly banded. Our convex formulation admits a simple and efficient algorithm. Empirical studies demonstrate its practical effectiveness and illustrate that our exactly-banded estimator works well even when the true covariance matrix is only close to a banded matrix, confirming our theoretical results. Our method compares favorably with all existing methods, in terms of accuracy and speed. We illustrate the practical merits of the convex banding estimator by showing that it can be used to improve the performance of discriminant analysis for classifying sound recordings.
Covariances for measured activation and fission ratios data
International Nuclear Information System (INIS)
Smith, D.L.; Meadows, J.W.; Watanabe, Y.
1986-01-01
Methods which are routinely used in the determination of covariance matrices for both integral and differential activation and fission-ratios data acquired at the Argonne National Laboratory Fast-Neutron Generator Facility (FNG) are discussed. Special consideration is given to problems associated with the estimation of correlations between various identified sources of experimental error. Approximation methods which are commonly used to reduce the labor involved in this analysis to manageable levels are described. Results from some experiments which have been recently carried out in this laboratory are presented to illustrate these procedures. 13 refs., 1 fig., 5 tabs
A measure of association between vectors based on "similarity covariance"
Pascual-Marqui, Roberto D.; Lehmann, Dietrich; Kochi, Kieko; Kinoshita, Toshihiko; Yamada, Naoto
2013-01-01
The "maximum similarity correlation" definition introduced in this study is motivated by the seminal work of Szekely et al on "distance covariance" (Ann. Statist. 2007, 35: 2769-2794; Ann. Appl. Stat. 2009, 3: 1236-1265). Instead of using Euclidean distances "d" as in Szekely et al, we use "similarity", which can be defined as "exp(-d/s)", where the scaling parameter s>0 controls how rapidly the similarity falls off with distance. Scale parameters are chosen by maximizing the similarity corre...
Mean-Lagrangian formalism and covariance of fluid turbulence.
Ariki, Taketo
2017-05-01
Mean-field-based Lagrangian framework is developed for the fluid turbulence theory, which enables physically objective discussions, especially, of the history effect. Mean flow serves as a purely geometrical object of Lie group theory, providing useful operations to measure the objective rate and history integration of the general tensor field. The proposed framework is applied, on the one hand, to one-point closure model, yielding an objective expression of the turbulence viscoelastic effect. Application to two-point closure, on the other hand, is also discussed, where natural extension of known Lagrangian correlation is discovered on the basis of an extended covariance group.
Accounting for covariate measurement error in a Cox model analysis of recurrence of depression.
Liu, K; Mazumdar, S; Stone, R A; Dew, M A; Houck, P R; Reynolds, C F
2001-01-01
When a covariate measured with error is used as a predictor in a survival analysis using the Cox model, the parameter estimate is usually biased. In clinical research, covariates measured without error such as treatment procedure or sex are often used in conjunction with a covariate measured with error. In a randomized clinical trial of two types of treatments, we account for the measurement error in the covariate, log-transformed total rapid eye movement (REM) activity counts, in a Cox model analysis of the time to recurrence of major depression in an elderly population. Regression calibration and two variants of a likelihood-based approach are used to account for measurement error. The likelihood-based approach is extended to account for the correlation between replicate measures of the covariate. Using the replicate data decreases the standard error of the parameter estimate for log(total REM) counts while maintaining the bias reduction of the estimate. We conclude that covariate measurement error and the correlation between replicates can affect results in a Cox model analysis and should be accounted for. In the depression data, these methods render comparable results that have less bias than the results when measurement error is ignored.
Buchy, Lisa; Barbato, Mariapaola; Makowski, Carolina; Bray, Signe; MacMaster, Frank P; Deighton, Stephanie; Addington, Jean
2017-11-01
People with psychosis show deficits recognizing facial emotions and disrupted activation in the underlying neural circuitry. We evaluated associations between facial emotion recognition and cortical thickness using a correlation-based approach to map structural covariance networks across the brain. Fifteen people with an early psychosis provided magnetic resonance scans and completed the Penn Emotion Recognition and Differentiation tasks. Fifteen historical controls provided magnetic resonance scans. Cortical thickness was computed using CIVET and analyzed with linear models. Seed-based structural covariance analysis was done using the mapping anatomical correlations across the cerebral cortex methodology. To map structural covariance networks involved in facial emotion recognition, the right somatosensory cortex and bilateral fusiform face areas were selected as seeds. Statistics were run in SurfStat. Findings showed increased cortical covariance between the right fusiform face region seed and right orbitofrontal cortex in controls than early psychosis subjects. Facial emotion recognition scores were not significantly associated with thickness in any region. A negative effect of Penn Differentiation scores on cortical covariance was seen between the left fusiform face area seed and right superior parietal lobule in early psychosis subjects. Results suggest that facial emotion recognition ability is related to covariance in a temporal-parietal network in early psychosis. Copyright © 2017 Elsevier B.V. All rights reserved.
Harden, Bradley J; Nichols, Scott R; Frueh, Dominique P
2014-09-24
Nuclear magnetic resonance (NMR) studies of larger proteins are hampered by difficulties in assigning NMR resonances. Human intervention is typically required to identify NMR signals in 3D spectra, and subsequent procedures depend on the accuracy of this so-called peak picking. We present a method that provides sequential connectivities through correlation maps constructed with covariance NMR, bypassing the need for preliminary peak picking. We introduce two novel techniques to minimize false correlations and merge the information from all original 3D spectra. First, we take spectral derivatives prior to performing covariance to emphasize coincident peak maxima. Second, we multiply covariance maps calculated with different 3D spectra to destroy erroneous sequential correlations. The maps are easy to use and can readily be generated from conventional triple-resonance experiments. Advantages of the method are demonstrated on a 37 kDa nonribosomal peptide synthetase domain subject to spectral overlap.
Institute of Scientific and Technical Information of China (English)
Xiaogu ZHENG
2009-01-01
An adaptive estimation of forecast error covariance matrices is proposed for Kalman filtering data assimilation. A forecast error covariance matrix is initially estimated using an ensemble of perturbation forecasts. This initially estimated matrix is then adjusted with scale parameters that are adaptively estimated by minimizing -2log-likelihood of observed-minus-forecast residuals. The proposed approach could be applied to Kalman filtering data assimilation with imperfect models when the model error statistics are not known. A simple nonlinear model (Burgers' equation model) is used to demonstrate the efficacy of the proposed approach.
Approaches for the generation of a covariance matrix for the Cf-252 fission-neutron spectrum
International Nuclear Information System (INIS)
Mannhart, W.
1983-01-01
After a brief retrospective glance is cast at the situation, the evaluation of the Cf-252 neutron spectrum with a complete covariance matrix based on the results of integral experiments is proposed. The different steps already taken in such an evaluation and work in progress are reviewed. It is shown that special attention should be given to the normalization of the neutron spectrum which must be reflected in the covariance matrix. The result of the least-squares adjustment procedure applied can easily be combined with the results of direct spectrum measurements and should be regarded as the first step in a new evaluation of the Cf-252 fission-neutron spectrum. (author)
Partial distance correlation with methods for dissimilarities
Székely, Gábor J.; Rizzo, Maria L.
2014-01-01
Distance covariance and distance correlation are scalar coefficients that characterize independence of random vectors in arbitrary dimension. Properties, extensions, and applications of distance correlation have been discussed in the recent literature, but the problem of defining the partial distance correlation has remained an open question of considerable interest. The problem of partial distance correlation is more complex than partial correlation partly because the squared distance covari...
Group covariant protocols for quantum string commitment
International Nuclear Information System (INIS)
Tsurumaru, Toyohiro
2006-01-01
We study the security of quantum string commitment (QSC) protocols with group covariant encoding scheme. First we consider a class of QSC protocol, which is general enough to incorporate all the QSC protocols given in the preceding literatures. Then among those protocols, we consider group covariant protocols and show that the exact upperbound on the binding condition can be calculated. Next using this result, we prove that for every irreducible representation of a finite group, there always exists a corresponding nontrivial QSC protocol which reaches a level of security impossible to achieve classically
The covariant entropy bound in gravitational collapse
International Nuclear Information System (INIS)
Gao, Sijie; Lemos, Jose P. S.
2004-01-01
We study the covariant entropy bound in the context of gravitational collapse. First, we discuss critically the heuristic arguments advanced by Bousso. Then we solve the problem through an exact model: a Tolman-Bondi dust shell collapsing into a Schwarzschild black hole. After the collapse, a new black hole with a larger mass is formed. The horizon, L, of the old black hole then terminates at the singularity. We show that the entropy crossing L does not exceed a quarter of the area of the old horizon. Therefore, the covariant entropy bound is satisfied in this process. (author)
Modular invariance and covariant loop calculus
International Nuclear Information System (INIS)
Petersen, J.L.; Roland, K.O.; Sidenius, J.R.
1988-01-01
The covariant loop calculus provides and efficient technique for computing explicit expressions for the density on moduli space corresponding to arbitrary (bosonic string) loop diagrams. Since modular invariance is not manifest, however, we carry out a detailed comparison with known explicit 2- and 3- loop results derived using analytic geometry (1 loop is known to be ok). We establish identity to 'high' order in some moduli and exactly in others. Agreement is found as a result of various non-trivial cancellations, in part related to number theory. We feel our results provide very strong support for the correctness of the covariant loop calculus approach. (orig.)
Remarks on Bousso's covariant entropy bound
Mayo, A E
2002-01-01
Bousso's covariant entropy bound is put to the test in the context of a non-singular cosmological solution of general relativity found by Bekenstein. Although the model complies with every assumption made in Bousso's original conjecture, the entropy bound is violated due to the occurrence of negative energy density associated with the interaction of some the matter components in the model. We demonstrate how this property allows for the test model to 'elude' a proof of Bousso's conjecture which was given recently by Flanagan, Marolf and Wald. This corroborates the view that the covariant entropy bound should be applied only to stable systems for which every matter component carries positive energy density.
Modular invariance and covariant loop calculus
International Nuclear Information System (INIS)
Petersen, J.L.; Roland, K.O.; Sidenius, J.R.
1988-01-01
The covariant loop calculus provides an efficient technique for computing explicit expressions for the density on moduli space corresponding to arbitrary (bosonic string) loop diagrams. Since modular invariance is not manifest, however, we carry out a detailed comparison with known explicit two- and three-loop results derived using analytic geometry (one loop is known to be okay). We establish identity to 'high' order in some moduli and exactly in others. Agreement is found as a result of various nontrivial cancellations, in part related to number theory. We feel our results provide very strong support for the correctness of the covariant loop calculus approach. (orig.)
Covariant n2-plet mass formulas
International Nuclear Information System (INIS)
Davidson, A.
1979-01-01
Using a generalized internal symmetry group analogous to the Lorentz group, we have constructed a covariant n 2 -plet mass operator. This operator is built as a scalar matrix in the (n;n*) representation, and its SU(n) breaking parameters are identified as intrinsic boost ones. Its basic properties are: covariance, Hermiticity, positivity, charge conjugation, quark contents, and a self-consistent n 2 -1, 1 mixing. The GMO and the Okubo formulas are obtained by considering two different limits of the same generalized mass formula
Activities on covariance estimation in Japanese Nuclear Data Committee
Energy Technology Data Exchange (ETDEWEB)
Shibata, Keiichi [Japan Atomic Energy Research Inst., Tokai, Ibaraki (Japan). Tokai Research Establishment
1997-03-01
Described are activities on covariance estimation in the Japanese Nuclear Data Committee. Covariances are obtained from measurements by using the least-squares methods. A simultaneous evaluation was performed to deduce covariances of fission cross sections of U and Pu isotopes. A code system, KALMAN, is used to estimate covariances of nuclear model calculations from uncertainties in model parameters. (author)
Reconstruction of sparse connectivity in neural networks from spike train covariances
International Nuclear Information System (INIS)
Pernice, Volker; Rotter, Stefan
2013-01-01
The inference of causation from correlation is in general highly problematic. Correspondingly, it is difficult to infer the existence of physical synaptic connections between neurons from correlations in their activity. Covariances in neural spike trains and their relation to network structure have been the subject of intense research, both experimentally and theoretically. The influence of recurrent connections on covariances can be characterized directly in linear models, where connectivity in the network is described by a matrix of linear coupling kernels. However, as indirect connections also give rise to covariances, the inverse problem of inferring network structure from covariances can generally not be solved unambiguously. Here we study to what degree this ambiguity can be resolved if the sparseness of neural networks is taken into account. To reconstruct a sparse network, we determine the minimal set of linear couplings consistent with the measured covariances by minimizing the L 1 norm of the coupling matrix under appropriate constraints. Contrary to intuition, after stochastic optimization of the coupling matrix, the resulting estimate of the underlying network is directed, despite the fact that a symmetric matrix of count covariances is used for inference. The performance of the new method is best if connections are neither exceedingly sparse, nor too dense, and it is easily applicable for networks of a few hundred nodes. Full coupling kernels can be obtained from the matrix of full covariance functions. We apply our method to networks of leaky integrate-and-fire neurons in an asynchronous–irregular state, where spike train covariances are well described by a linear model. (paper)
International Nuclear Information System (INIS)
Fiorito, L.; Diez, C.J.; Cabellos, O.; Stankovskiy, A.; Van den Eynde, G.; Labeau, P.E.
2014-01-01
Highlights: • Fission yield data and uncertainty comparison between major nuclear data libraries. • Fission yield covariance generation through Bayesian technique. • Study of the effect of fission yield correlations on decay heat calculations. • Covariance information contribute to reduce fission pulse decay heat uncertainty. - Abstract: Fission product yields are fundamental parameters in burnup/activation calculations and the impact of their uncertainties was widely studied in the past. Evaluations of these uncertainties were released, still without covariance data. Therefore, the nuclear community expressed the need of full fission yield covariance matrices to be able to produce inventory calculation results that take into account the complete uncertainty data. State-of-the-art fission yield data and methodologies for fission yield covariance generation were researched in this work. Covariance matrices were generated and compared to the original data stored in the library. Then, we focused on the effect of fission yield covariance information on fission pulse decay heat results for thermal fission of 235 U. Calculations were carried out using different libraries and codes (ACAB and ALEPH-2) after introducing the new covariance values. Results were compared with those obtained with the uncertainty data currently provided by the libraries. The uncertainty quantification was performed first with Monte Carlo sampling and then compared with linear perturbation. Indeed, correlations between fission yields strongly affect the uncertainty of decay heat. Eventually, a sensitivity analysis of fission product yields to fission pulse decay heat was performed in order to provide a full set of the most sensitive nuclides for such a calculation
Covariant canonical quantization of fields and Bohmian mechanics
International Nuclear Information System (INIS)
Nikolic, H.
2005-01-01
We propose a manifestly covariant canonical method of field quantization based on the classical De Donder-Weyl covariant canonical formulation of field theory. Owing to covariance, the space and time arguments of fields are treated on an equal footing. To achieve both covariance and consistency with standard non-covariant canonical quantization of fields in Minkowski spacetime, it is necessary to adopt a covariant Bohmian formulation of quantum field theory. A preferred foliation of spacetime emerges dynamically owing to a purely quantum effect. The application to a simple time-reparametrization invariant system and quantum gravity is discussed and compared with the conventional non-covariant Wheeler-DeWitt approach. (orig.)
Rigorous covariance propagation of geoid errors to geodetic MDT estimates
Pail, R.; Albertella, A.; Fecher, T.; Savcenko, R.
2012-04-01
The mean dynamic topography (MDT) is defined as the difference between the mean sea surface (MSS) derived from satellite altimetry, averaged over several years, and the static geoid. Assuming geostrophic conditions, from the MDT the ocean surface velocities as important component of global ocean circulation can be derived from it. Due to the availability of GOCE gravity field models, for the very first time MDT can now be derived solely from satellite observations (altimetry and gravity) down to spatial length-scales of 100 km and even below. Global gravity field models, parameterized in terms of spherical harmonic coefficients, are complemented by the full variance-covariance matrix (VCM). Therefore, for the geoid component a realistic statistical error estimate is available, while the error description of the altimetric component is still an open issue and is, if at all, attacked empirically. In this study we make the attempt to perform, based on the full gravity VCM, rigorous error propagation to derived geostrophic surface velocities, thus also considering all correlations. For the definition of the static geoid we use the third release of the time-wise GOCE model, as well as the satellite-only combination model GOCO03S. In detail, we will investigate the velocity errors resulting from the geoid component in dependence of the harmonic degree, and the impact of using/no using covariances on the MDT errors and its correlations. When deriving an MDT, it is spectrally filtered to a certain maximum degree, which is usually driven by the signal content of the geoid model, by applying isotropic or non-isotropic filters. Since this filtering is acting also on the geoid component, the consistent integration of this filter process into the covariance propagation shall be performed, and its impact shall be quantified. The study will be performed for MDT estimates in specific test areas of particular oceanographic interest.
SCALE-6 Sensitivity/Uncertainty Methods and Covariance Data
International Nuclear Information System (INIS)
Williams, Mark L.; Rearden, Bradley T.
2008-01-01
Computational methods and data used for sensitivity and uncertainty analysis within the SCALE nuclear analysis code system are presented. The methodology used to calculate sensitivity coefficients and similarity coefficients and to perform nuclear data adjustment is discussed. A description is provided of the SCALE-6 covariance library based on ENDF/B-VII and other nuclear data evaluations, supplemented by 'low-fidelity' approximate covariances. SCALE (Standardized Computer Analyses for Licensing Evaluation) is a modular code system developed by Oak Ridge National Laboratory (ORNL) to perform calculations for criticality safety, reactor physics, and radiation shielding applications. SCALE calculations typically use sequences that execute a predefined series of executable modules to compute particle fluxes and responses like the critical multiplication factor. SCALE also includes modules for sensitivity and uncertainty (S/U) analysis of calculated responses. The S/U codes in SCALE are collectively referred to as TSUNAMI (Tools for Sensitivity and UNcertainty Analysis Methodology Implementation). SCALE-6-scheduled for release in 2008-contains significant new capabilities, including important enhancements in S/U methods and data. The main functions of TSUNAMI are to (a) compute nuclear data sensitivity coefficients and response uncertainties, (b) establish similarity between benchmark experiments and design applications, and (c) reduce uncertainty in calculated responses by consolidating integral benchmark experiments. TSUNAMI includes easy-to-use graphical user interfaces for defining problem input and viewing three-dimensional (3D) geometries, as well as an integrated plotting package.
Covariance methodology applied to uncertainties in I-126 disintegration rate measurements
International Nuclear Information System (INIS)
Fonseca, K.A.; Koskinas, M.F.; Dias, M.S.
1996-01-01
The covariance methodology applied to uncertainties in 126 I disintegration rate measurements is described. Two different coincidence systems were used due to the complex decay scheme of this radionuclide. The parameters involved in the determination of the disintegration rate in each experimental system present correlated components. In this case, the conventional statistical methods to determine the uncertainties (law of propagation) result in wrong values for the final uncertainty. Therefore, use of the methodology of the covariance matrix is necessary. The data from both systems were combined taking into account all possible correlations between the partial uncertainties. (orig.)
Directory of Open Access Journals (Sweden)
C. Spirig
2005-01-01
Full Text Available Within the framework of the AFO 2000 project ECHO, two PTR-MS instruments were operated in combination with sonic anemometers to determine biogenic VOC fluxes from a mixed deciduous forest site in North-Western Germany. The measurement site was characterised by a forest of inhomogeneous composition, complex canopy structure, limited extension in certain wind directions and frequent calm wind conditions during night time. The eddy covariance (EC technique was applied since it represents the most direct flux measurement approach on the canopy scale and is, therefore, least susceptible to these non-ideal conditions. A specific flux calculation method was used to account for the sequential multi-component PTR-MS measurements and allowing an individual delay time adjustment as well as a rigorous quality control based on cospectral analysis. The validated flux results are consistent with light and temperature dependent emissions of isoprene and monoterpenes from this forest, with average daytime emissions of 0.94 and 0.3µg m-2s-1, respectively. Emissions of methanol reached on average 0.087µg m-2s-1 during daytime, but fluxes were too small to be detected during night time. Upward fluxes of the isoprene oxidation products methyl vinyl ketone (MVK and methacrolein (MACR were also found, being two orders of magnitude lower than those of isoprene. Calculations with an analytical footprint model indicate that the observed isoprene fluxes correlate with the fraction of oaks within the footprints of the flux measurement.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander; Genton, Marc G.; Sun, Ying
2015-01-01
We approximate large non-structured Matérn covariance matrices of size n×n in the H-matrix format with a log-linear computational cost and storage O(kn log n), where rank k ≪ n is a small integer. Applications are: spatial statistics, machine learning and image analysis, kriging and optimal design.
Zero curvature conditions and conformal covariance
International Nuclear Information System (INIS)
Akemann, G.; Grimm, R.
1992-05-01
Two-dimensional zero curvature conditions were investigated in detail, with special emphasis on conformal properties, and the appearance of covariant higher order differential operators constructed in terms of a projective connection was elucidated. The analysis is based on the Kostant decomposition of simple Lie algebras in terms of representations with respect to their 'principal' SL(2) subalgebra. (author) 27 refs
On superfield covariant quantization in general coordinates
International Nuclear Information System (INIS)
Gitman, D.M.; Moshin, P. Yu.; Tomazelli, J.L.
2005-01-01
We propose a natural extension of the BRST-antiBRST superfield covariant scheme in general coordinates. Thus, the coordinate dependence of the basic tensor fields and scalar density of the formalism is extended from the base supermanifold to the complete set of superfield variables. (orig.)
On superfield covariant quantization in general coordinates
Energy Technology Data Exchange (ETDEWEB)
Gitman, D.M. [Universidade de Sao Paulo, Instituto de Fisica, Sao Paulo, S.P (Brazil); Moshin, P. Yu. [Universidade de Sao Paulo, Instituto de Fisica, Sao Paulo, S.P (Brazil); Tomsk State Pedagogical University, Tomsk (Russian Federation); Tomazelli, J.L. [UNESP, Departamento de Fisica e Quimica, Campus de Guaratingueta (Brazil)
2005-12-01
We propose a natural extension of the BRST-antiBRST superfield covariant scheme in general coordinates. Thus, the coordinate dependence of the basic tensor fields and scalar density of the formalism is extended from the base supermanifold to the complete set of superfield variables. (orig.)
Covariant field theory of closed superstrings
International Nuclear Information System (INIS)
Siopsis, G.
1989-01-01
The authors construct covariant field theories of both type-II and heterotic strings. Toroidal compactification is also considered. The interaction vertices are based on Witten's vertex representing three strings interacting at the mid-point. For closed strings, the authors thus obtain a bilocal interaction
Conformally covariant composite operators in quantum chromodynamics
International Nuclear Information System (INIS)
Craigie, N.S.; Dobrev, V.K.; Todorov, I.T.
1983-03-01
Conformal covariance is shown to determine renormalization properties of composite operators in QCD and in the C 6 3 -model at the one-loop level. Its relevance to higher order (renormalization group improved) perturbative calculations in the short distance limit is also discussed. Light cone operator product expansions and spectral representations for wave functions in QCD are derived. (author)
Soft covariant gauges on the lattice
Energy Technology Data Exchange (ETDEWEB)
Henty, D.S.; Oliveira, O.; Parrinello, C.; Ryan, S. [Department of Physics and Astronomy, University of Edinburgh, Edinburgh EH9 3JZ, Scotland (UKQCD Collaboration)
1996-12-01
We present an exploratory study of a one-parameter family of covariant, nonperturbative lattice gauge-fixing conditions that can be implemented through a simple Monte Carlo algorithm. We demonstrate that at the numerical level the procedure is feasible, and as a first application we examine the gauge dependence of the gluon propagator. {copyright} {ital 1996 The American Physical Society.}
Covariant differential calculus on the quantum hyperplane
International Nuclear Information System (INIS)
Wess, J.
1991-01-01
We develop a differential calculus on the quantum hyperplane covariant with respect to the action of the quantum group GL q (n). This is a concrete example of noncommutative differential geometry. We describe the general constraints for a noncommutative differential calculus and verify that the example given here satisfies all these constraints. We also discuss briefly the integration over the quantum plane. (orig.)
Covariant single-hole optical potential
International Nuclear Information System (INIS)
Kam, J. de
1982-01-01
In this investigation a covariant optical potential model is constructed for scattering processes of mesons from nuclei in which the meson interacts repeatedly with one of the target nucleons. The nuclear binding interactions in the intermediate scattering state are consistently taken into account. In particular for pions and K - projectiles this is important in view of the strong energy dependence of the elementary projectile-nucleon amplitude. Furthermore, this optical potential satisfies unitarity and relativistic covariance. The starting point in our discussion is the three-body model for the optical potential. To obtain a practical covariant theory I formulate the three-body model as a relativistic quasi two-body problem. Expressions for the transition interactions and propagators in the quasi two-body equations are found by imposing the correct s-channel unitarity relations and by using dispersion integrals. This is done in such a way that the correct non-relativistic limit is obtained, avoiding clustering problems. Corrections to the quasi two-body treatment from the Pauli principle and the required ground-state exclusion are taken into account. The covariant equations that we arrive at are amenable to practical calculations. (orig.)
Nonlinear realization of general covariance group
International Nuclear Information System (INIS)
Hamamoto, Shinji
1979-01-01
The structure of the theory resulting from the nonlinear realization of general covariance group is analysed. We discuss the general form of free Lagrangian for Goldstone fields, and propose as a special choice one reasonable form which is shown to describe a gravitational theory with massless tensor graviton and massive vector tordion. (author)
Covariant quantum mechanics on a null plane
International Nuclear Information System (INIS)
Leutwyler, H.; Stern, J.
1977-03-01
Lorentz invariance implies that the null plane wave functions factorize into a kinematical part describing the motion of the system as a whole and an inner wave function that involves the specific dynamical properties of the system - in complete correspondence with the non-relativistic situation. Covariance is equivalent to an angular condition which admits non-trivial solutions
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-11-30
We approximate large non-structured Matérn covariance matrices of size n×n in the H-matrix format with a log-linear computational cost and storage O(kn log n), where rank k ≪ n is a small integer. Applications are: spatial statistics, machine learning and image analysis, kriging and optimal design.
Approximate methods for derivation of covariance data
International Nuclear Information System (INIS)
Tagesen, S.
1992-01-01
Several approaches for the derivation of covariance information for evaluated nuclear data files (EFF2 and ENDF/B-VI) have been developed and used at IRK and ORNL respectively. Considerations, governing the choice of a distinct method depending on the quantity and quality of available data are presented, advantages/disadvantages are discussed and examples of results are given
Optimal covariate designs theory and applications
Das, Premadhis; Mandal, Nripes Kumar; Sinha, Bikas Kumar
2015-01-01
This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for...
Asymptotics for the minimum covariance determinant estimator
Butler, R.W.; Davies, P.L.; Jhun, M.
1993-01-01
Consistency is shown for the minimum covariance determinant (MCD) estimators of multivariate location and scale and asymptotic normality is shown for the former. The proofs are made possible by showing a separating ellipsoid property for the MCD subset of observations. An analogous property is shown
EQUIVALENT MODELS IN COVARIANCE STRUCTURE-ANALYSIS
LUIJBEN, TCW
1991-01-01
Defining equivalent models as those that reproduce the same set of covariance matrices, necessary and sufficient conditions are stated for the local equivalence of two expanded identified models M1 and M2 when fitting the more restricted model M0. Assuming several regularity conditions, the rank
ENDF-6 File 30: Data covariances obtained from parameter covariances and sensitivities
International Nuclear Information System (INIS)
Muir, D.W.
1989-01-01
File 30 is provided as a means of describing the covariances of tabulated cross sections, multiplicities, and energy-angle distributions that result from propagating the covariances of a set of underlying parameters (for example, the input parameters of a nuclear-model code), using an evaluator-supplied set of parameter covariances and sensitivities. Whenever nuclear data are evaluated primarily through the application of nuclear models, the covariances of the resulting data can be described very adequately, and compactly, by specifying the covariance matrix for the underlying nuclear parameters, along with a set of sensitivity coefficients giving the rate of change of each nuclear datum of interest with respect to each of the model parameters. Although motivated primarily by these applications of nuclear theory, use of File 30 is not restricted to any one particular evaluation methodology. It can be used to describe data covariances of any origin, so long as they can be formally separated into a set of parameters with specified covariances and a set of data sensitivities
Structural covariance networks across healthy young adults and their consistency.
Guo, Xiaojuan; Wang, Yan; Guo, Taomei; Chen, Kewei; Zhang, Jiacai; Li, Ke; Jin, Zhen; Yao, Li
2015-08-01
To investigate structural covariance networks (SCNs) as measured by regional gray matter volumes with structural magnetic resonance imaging (MRI) from healthy young adults, and to examine their consistency and stability. Two independent cohorts were included in this study: Group 1 (82 healthy subjects aged 18-28 years) and Group 2 (109 healthy subjects aged 20-28 years). Structural MRI data were acquired at 3.0T and 1.5T using a magnetization prepared rapid-acquisition gradient echo sequence for these two groups, respectively. We applied independent component analysis (ICA) to construct SCNs and further applied the spatial overlap ratio and correlation coefficient to evaluate the spatial consistency of the SCNs between these two datasets. Seven and six independent components were identified for Group 1 and Group 2, respectively. Moreover, six SCNs including the posterior default mode network, the visual and auditory networks consistently existed across the two datasets. The overlap ratios and correlation coefficients of the visual network reached the maximums of 72% and 0.71. This study demonstrates the existence of consistent SCNs corresponding to general functional networks. These structural covariance findings may provide insight into the underlying organizational principles of brain anatomy. © 2014 Wiley Periodicals, Inc.
Nguyen, Tri-Long; Collins, Gary S; Spence, Jessica; Daurès, Jean-Pierre; Devereaux, P J; Landais, Paul; Le Manach, Yannick
2017-04-28
Double-adjustment can be used to remove confounding if imbalance exists after propensity score (PS) matching. However, it is not always possible to include all covariates in adjustment. We aimed to find the optimal imbalance threshold for entering covariates into regression. We conducted a series of Monte Carlo simulations on virtual populations of 5,000 subjects. We performed PS 1:1 nearest-neighbor matching on each sample. We calculated standardized mean differences across groups to detect any remaining imbalance in the matched samples. We examined 25 thresholds (from 0.01 to 0.25, stepwise 0.01) for considering residual imbalance. The treatment effect was estimated using logistic regression that contained only those covariates considered to be unbalanced by these thresholds. We showed that regression adjustment could dramatically remove residual confounding bias when it included all of the covariates with a standardized difference greater than 0.10. The additional benefit was negligible when we also adjusted for covariates with less imbalance. We found that the mean squared error of the estimates was minimized under the same conditions. If covariate balance is not achieved, we recommend reiterating PS modeling until standardized differences below 0.10 are achieved on most covariates. In case of remaining imbalance, a double adjustment might be worth considering.
Directory of Open Access Journals (Sweden)
José Ernandes Rufino de Sousa
2011-01-01
Full Text Available It was used 4,313 weight records from birth to 196 days of age from 946 Anglo-nubiana breed goats, progenies from 43 sires and 279 dams, controlled in the period from 1980 to 2005, with the objective of estimating covariance functions and genetic parameters of animals by using random regression models. It was evaluated 12 random regression models, with degrees ranging from 1 to 7 for direct additive genetic and maternal and animal permanent environment effect and residual variance adjusted by using animal age ordinary polynomial of third order. Models were compared by using likelihood ratio test and by Bayesian information criterion of Schwarz and Akaike information criterion. The model selected based on Bayesian information criterion was the one that considered the maternal and direct additive genetic effect adjusted by a quadratic polynomial and the animal permanent environmental effect adjusted by a cubic polynomial (M334. Heritability estimates for direct effect were lower in the beginning and at the end of the studied period and maternal heritability estimates were higher at 196 days of age in comparison to the other growth phases. Genetic correlation ranged from moderate to high and they decreased as the distance between ages increased. Higher efficiency in selection for weight can be obtained by considering weights close to weaning, which is a period when the highest estimates of genetic variance and heritability are obtained.Foram utilizados 4.313 registros de pesos do nascimento aos 196 dias de idade de 946 animais da raça Anglo-Nubiana, filhos de 43 reprodutores e 279 cabras, controlados no período de 1980 a 2005, com o objetivo de estimar funções de covariância e parâmetros genéticos dos animais por meio de modelos de regressão aleatória. Foram avaliados 12 modelos de regressão aleatória, com graus variando de 1 a 7 para os efeitos genéticos aditivo direto e materno e de ambiente permanente de animal e com vari
Evaluation of covariance data for chromium, iron and nickel contained in JENDL-3.2
International Nuclear Information System (INIS)
Oh, Soo-Youl; Shibata, Keiichi.
1998-01-01
An evaluation has been made for the covariances of neutron cross sections of 52 Cr, 56 Fe, 58 Ni and 60 Ni contained in JENDL-3.2. Reactions considered were the threshold reactions such as (n, 2n), (n, nα), (n, np), (n, p), (n, d), (n, t) and (n, α), the radiative capture reaction above the resonance region, and the inelastic scattering to discrete and continuum levels. Evaluation guidelines and procedures were established during the work. A generalized least-squares fitting code GMA was used in estimating covariances for reactions of which JENDL-3.2 cross sections had been evaluated by taking account of many measured data. For cross sections that had been evaluated by nuclear reaction model calculations, the KALMAN code, which yields covariances of cross sections and of associated model parameters on the basis of the Bayesian statistics, was used in conjunction with reaction model codes EGNASH and CASTHY. The evaluated uncertainties of a few percent to 30% in the cross sections look reasonable, and the correlation matrices show understandable trends. Even though there is no strict way to confirm the validity of the evaluated covariances, tools and procedures adopted in the present work are appropriate for producing covariance files based on JENDL-3.2. The covariances obtained will be compiled into JENDL in the near future. Meanwhile, new sets of optical model and level density parameters were proposed as one of byproducts obtained from the KALMAN calculations. (author)
Directional selection effects on patterns of phenotypic (co)variation in wild populations.
Assis, A P A; Patton, J L; Hubbe, A; Marroig, G
2016-11-30
Phenotypic (co)variation is a prerequisite for evolutionary change, and understanding how (co)variation evolves is of crucial importance to the biological sciences. Theoretical models predict that under directional selection, phenotypic (co)variation should evolve in step with the underlying adaptive landscape, increasing the degree of correlation among co-selected traits as well as the amount of genetic variance in the direction of selection. Whether either of these outcomes occurs in natural populations is an open question and thus an important gap in evolutionary theory. Here, we documented changes in the phenotypic (co)variation structure in two separate natural populations in each of two chipmunk species (Tamias alpinus and T. speciosus) undergoing directional selection. In populations where selection was strongest (those of T. alpinus), we observed changes, at least for one population, in phenotypic (co)variation that matched theoretical expectations, namely an increase of both phenotypic integration and (co)variance in the direction of selection and a re-alignment of the major axis of variation with the selection gradient. © 2016 The Author(s).
Covariance J-resolved spectroscopy: Theory and application in vivo.
Iqbal, Zohaib; Verma, Gaurav; Kumar, Anand; Thomas, M Albert
2017-08-01
Magnetic resonance spectroscopy (MRS) is a powerful tool capable of investigating the metabolic status of several tissues in vivo. In particular, single-voxel-based 1 H spectroscopy provides invaluable biochemical information from a volume of interest (VOI) and has therefore been used in a variety of studies. Unfortunately, typical one-dimensional MRS data suffer from severe signal overlap and thus important metabolites are difficult to distinguish. One method that is used to disentangle overlapping resonances is the two-dimensional J-resolved spectroscopy (JPRESS) experiment. Due to the long acquisition duration of the JPRESS experiment, a limited number of points are acquired in the indirect dimension, leading to poor spectral resolution along this dimension. Poor spectral resolution is problematic because proper peak assignment may be hindered, which is why the zero-filling method is often used to improve resolution as a post-processing step. However, zero-filling leads to spectral artifacts, which may affect visualization and quantitation of spectra. A novel method utilizing a covariance transformation, called covariance J-resolved spectroscopy (CovJ), was developed in order to improve spectral resolution along the indirect dimension (F 1 ). Comparison of simulated data demonstrates that peak structures remain qualitatively similar between JPRESS and the novel method along the diagonal region (F 1 = 0 Hz), whereas differences arise in the cross-peak (F 1 ≠0 Hz) regions. In addition, quantitative results of in vivo JPRESS data acquired on a 3T scanner show significant correlations (r 2 >0.86, pCOVariance Spectral Evaluation of 1 H Acquisitions using Representative prior knowledge' (Cov-SEHAR), was developed in order to quantify γ-aminobutyric acid and glutamate from the CovJ spectra. These preliminary findings indicate that the CovJ method may be used to improve spectral resolution without hindering metabolite quantitation for J-resolved spectra
Covariance analysis of symmetry energy observables from heavy ion collision
Directory of Open Access Journals (Sweden)
Yingxun Zhang
2015-10-01
Full Text Available Using covariance analysis, we quantify the correlations between the interaction parameters in a transport model and the observables commonly used to extract information of the Equation of State of Asymmetric Nuclear Matter in experiments. By simulating 124Sn + 124Sn, 124Sn + 112Sn and 112Sn + 112Sn reactions at beam energies of 50 and 120 MeV per nucleon, we have identified that the nucleon effective mass splitting is most strongly correlated to the neutrons and protons yield ratios with high kinetic energy from central collisions especially at high incident energy. The best observable to determine the slope of the symmetry energy, L, at saturation density is the isospin diffusion observable even though the correlation is not very strong (∼0.7. Similar magnitude of correlation but opposite in sign exists for isospin diffusion and nucleon isoscalar effective mass. At 120 MeV/u, the effective mass splitting and the isoscalar effective mass also have opposite correlation for the double n/p and isoscaling p/p yield ratios. By combining data and simulations at different beam energies, it should be possible to place constraints on the slope of symmetry energy (L and effective mass splitting with reasonable uncertainties.
Determination of covariant Schwinger terms in anomalous gauge theories
International Nuclear Information System (INIS)
Kelnhofer, G.
1991-01-01
A functional integral method is used to determine equal time commutators between the covariant currents and the covariant Gauss-law operators in theories which are affected by an anomaly. By using a differential geometrical setup we show how the derivation of consistent- and covariant Schwinger terms can be understood on an equal footing. We find a modified consistency condition for the covariant anomaly. As a by-product the Bardeen-Zumino functional, which relates consistent and covariant anomalies, can be interpreted as connection on a certain line bundle over all gauge potentials. Finally the covariant commutator anomalies are calculated for the two- and four dimensional case. (orig.)
Paragrassmann analysis and covariant quantum algebras
International Nuclear Information System (INIS)
Filippov, A.T.; Isaev, A.P.; Kurdikov, A.B.; Pyatov, P.N.
1993-01-01
This report is devoted to the consideration from the algebraic point of view the paragrassmann algebras with one and many paragrassmann generators Θ i , Θ p+1 i = 0. We construct the paragrassmann versions of the Heisenberg algebra. For the special case, this algebra is nothing but the algebra for coordinates and derivatives considered in the context of covariant differential calculus on quantum hyperplane. The parameter of deformation q in our case is (p+1)-root of unity. Our construction is nondegenerate only for even p. Taking bilinear combinations of paragrassmann derivatives and coordinates we realize generators for the covariant quantum algebras as tensor products of (p+1) x (p+1) matrices. (orig./HSI)
Covariant holography of a tachyonic accelerating universe
Energy Technology Data Exchange (ETDEWEB)
Rozas-Fernandez, Alberto [Consejo Superior de Investigaciones Cientificas, Instituto de Fisica Fundamental, Madrid (Spain); University of Portsmouth, Institute of Cosmology and Gravitation, Portsmouth (United Kingdom)
2014-08-15
We apply the holographic principle to a flat dark energy dominated Friedmann-Robertson-Walker spacetime filled with a tachyon scalar field with constant equation of state w = p/ρ, both for w > -1 and w < -1. By using a geometrical covariant procedure, which allows the construction of holographic hypersurfaces, we have obtained for each case the position of the preferred screen and have then compared these with those obtained by using the holographic dark energy model with the future event horizon as the infrared cutoff. In the phantom scenario, one of the two obtained holographic screens is placed on the big rip hypersurface, both for the covariant holographic formalism and the holographic phantom model. It is also analyzed whether the existence of these preferred screens allows a mathematically consistent formulation of fundamental theories based on the existence of an S-matrix at infinite distances. (orig.)
On covariance structure in noisy, big data
Paffenroth, Randy C.; Nong, Ryan; Du Toit, Philip C.
2013-09-01
Herein we describe theory and algorithms for detecting covariance structures in large, noisy data sets. Our work uses ideas from matrix completion and robust principal component analysis to detect the presence of low-rank covariance matrices, even when the data is noisy, distorted by large corruptions, and only partially observed. In fact, the ability to handle partial observations combined with ideas from randomized algorithms for matrix decomposition enables us to produce asymptotically fast algorithms. Herein we will provide numerical demonstrations of the methods and their convergence properties. While such methods have applicability to many problems, including mathematical finance, crime analysis, and other large-scale sensor fusion problems, our inspiration arises from applying these methods in the context of cyber network intrusion detection.
International Nuclear Information System (INIS)
Gebbie, Tim; Ellis, G.F.R.
2000-01-01
This is the first of a series of papers systematically extending a 1+3 covariant and gauge-invariant treatment of kinetic theory in curved space-times to a treatment of cosmic microwave background temperature anisotropies arising from inhomogeneities in the early universe. The present paper deals with algebraic issues, both generically and in the context of models linearised about Robertson-Walker geometries. The approach represents radiation anisotropies by projected symmetric and trace-free tensors. The angular correlation functions for the mode coefficients are found in terms of these quantities, following the Wilson-Silk approach, but derived and dealt with in 1+3 covariant and gauge-invariant form. The covariant multipole and mode-expanded angular correlation functions are related to the usual treatments in the literature. The 1+3 covariant and gauge-invariant mode expansion is related to the coordinate approach by linking the Legendre functions to the projected symmetric trace-free representation, using a covariant addition theorem for the tensors to generate the Legendre polynomial recursion relation. This paper lays the foundation for further papers in the series, which use this formalism in a covariant and gauge-invariant approach to developing solutions of the Boltzmann and Liouville equations for the cosmic microwave background before and after decoupling, thus providing a unified covariant and gauge-invariant derivation of the variety of approaches to cosmic microwave background anisotropies in the current literature, as well as a basis for extension of the theory to include nonlinearities
PUFF-III: A Code for Processing ENDF Uncertainty Data Into Multigroup Covariance Matrices
International Nuclear Information System (INIS)
Dunn, M.E.
2000-01-01
PUFF-III is an extension of the previous PUFF-II code that was developed in the 1970s and early 1980s. The PUFF codes process the Evaluated Nuclear Data File (ENDF) covariance data and generate multigroup covariance matrices on a user-specified energy grid structure. Unlike its predecessor, PUFF-III can process the new ENDF/B-VI data formats. In particular, PUFF-III has the capability to process the spontaneous fission covariances for fission neutron multiplicity. With regard to the covariance data in File 33 of the ENDF system, PUFF-III has the capability to process short-range variance formats, as well as the lumped reaction covariance data formats that were introduced in ENDF/B-V. In addition to the new ENDF formats, a new directory feature is now available that allows the user to obtain a detailed directory of the uncertainty information in the data files without visually inspecting the ENDF data. Following the correlation matrix calculation, PUFF-III also evaluates the eigenvalues of each correlation matrix and tests each matrix for positive definiteness. Additional new features are discussed in the manual. PUFF-III has been developed for implementation in the AMPX code system, and several modifications were incorporated to improve memory allocation tasks and input/output operations. Consequently, the resulting code has a structure that is similar to other modules in the AMPX code system. With the release of PUFF-III, a new and improved covariance processing code is available to process ENDF covariance formats through Version VI
Twisted covariant noncommutative self-dual gravity
International Nuclear Information System (INIS)
Estrada-Jimenez, S.; Garcia-Compean, H.; Obregon, O.; Ramirez, C.
2008-01-01
A twisted covariant formulation of noncommutative self-dual gravity is presented. The formulation for constructing twisted noncommutative Yang-Mills theories is used. It is shown that the noncommutative torsion is solved at any order of the θ expansion in terms of the tetrad and some extra fields of the theory. In the process the first order expansion in θ for the Plebanski action is explicitly obtained.
Superfield quantization in Sp(2) covariant formalism
Lavrov, P M
2001-01-01
The rules of the superfield Sp(2) covariant quantization of the arbitrary gauge theories for the case of the introduction of the gauging with the derivative equations for the gauge functional are generalized. The possibilities of realization of the expanded anti-brackets are considered and it is shown, that only one of the realizations is compatible with the transformations of the expanded BRST-symmetry in the form of super translations along the Grassmann superspace coordinates
Torsion and geometrostasis in covariant superstrings
International Nuclear Information System (INIS)
Zachos, C.
1985-01-01
The covariant action for freely propagating heterotic superstrings consists of a metric and a torsion term with a special relative strength. It is shown that the strength for which torsion flattens the underlying 10-dimensional superspace geometry is precisely that which yields free oscillators on the light cone. This is in complete analogy with the geometrostasis of two-dimensional sigma-models with Wess-Zumino interactions. 13 refs
Covariant derivatives of the Berezin transform
Czech Academy of Sciences Publication Activity Database
Engliš, Miroslav; Otáhalová, R.
2011-01-01
Roč. 363, č. 10 (2011), s. 5111-5129 ISSN 0002-9947 R&D Projects: GA AV ČR IAA100190802 Keywords : Berezin transform * Berezin symbol * covariant derivative Subject RIV: BA - General Mathematics Impact factor: 1.093, year: 2011 http://www.ams.org/journals/tran/2011-363-10/S0002-9947-2011-05111-1/home.html
Torsion and geometrostasis in covariant superstrings
Energy Technology Data Exchange (ETDEWEB)
Zachos, C.
1985-01-01
The covariant action for freely propagating heterotic superstrings consists of a metric and a torsion term with a special relative strength. It is shown that the strength for which torsion flattens the underlying 10-dimensional superspace geometry is precisely that which yields free oscillators on the light cone. This is in complete analogy with the geometrostasis of two-dimensional sigma-models with Wess-Zumino interactions. 13 refs.
Covariance expressions for eigenvalue and eigenvector problems
Liounis, Andrew J.
There are a number of important scientific and engineering problems whose solutions take the form of an eigenvalue--eigenvector problem. Some notable examples include solutions to linear systems of ordinary differential equations, controllability of linear systems, finite element analysis, chemical kinetics, fitting ellipses to noisy data, and optimal estimation of attitude from unit vectors. In many of these problems, having knowledge of the eigenvalue and eigenvector Jacobians is either necessary or is nearly as important as having the solution itself. For instance, Jacobians are necessary to find the uncertainty in a computed eigenvalue or eigenvector estimate. This uncertainty, which is usually represented as a covariance matrix, has been well studied for problems similar to the eigenvalue and eigenvector problem, such as singular value decomposition. There has been substantially less research on the covariance of an optimal estimate originating from an eigenvalue-eigenvector problem. In this thesis we develop two general expressions for the Jacobians of eigenvalues and eigenvectors with respect to the elements of their parent matrix. The expressions developed make use of only the parent matrix and the eigenvalue and eigenvector pair under consideration. In addition, they are applicable to any general matrix (including complex valued matrices, eigenvalues, and eigenvectors) as long as the eigenvalues are simple. Alongside this, we develop expressions that determine the uncertainty in a vector estimate obtained from an eigenvalue-eigenvector problem given the uncertainty of the terms of the matrix. The Jacobian expressions developed are numerically validated with forward finite, differencing and the covariance expressions are validated using Monte Carlo analysis. Finally, the results from this work are used to determine covariance expressions for a variety of estimation problem examples and are also applied to the design of a dynamical system.
Linear Covariance Analysis for a Lunar Lander
Jang, Jiann-Woei; Bhatt, Sagar; Fritz, Matthew; Woffinden, David; May, Darryl; Braden, Ellen; Hannan, Michael
2017-01-01
A next-generation lunar lander Guidance, Navigation, and Control (GNC) system, which includes a state-of-the-art optical sensor suite, is proposed in a concept design cycle. The design goal is to allow the lander to softly land within the prescribed landing precision. The achievement of this precision landing requirement depends on proper selection of the sensor suite. In this paper, a robust sensor selection procedure is demonstrated using a Linear Covariance (LinCov) analysis tool developed by Draper.
The covariant formulation of f ( T ) gravity
International Nuclear Information System (INIS)
Krššák, Martin; Saridakis, Emmanuel N
2016-01-01
We show that the well-known problem of frame dependence and violation of local Lorentz invariance in the usual formulation of f ( T ) gravity is a consequence of neglecting the role of spin connection. We re-formulate f ( T ) gravity starting from, instead of the ‘pure tetrad’ teleparallel gravity, the covariant teleparallel gravity, using both the tetrad and the spin connection as dynamical variables, resulting in a fully covariant, consistent, and frame-independent version of f ( T ) gravity, which does not suffer from the notorious problems of the usual, pure tetrad, f ( T ) theory. We present the method to extract solutions for the most physically important cases, such as the Minkowski, the Friedmann–Robertson–Walker (FRW) and the spherically symmetric ones. We show that in covariant f ( T ) gravity we are allowed to use an arbitrary tetrad in an arbitrary coordinate system along with the corresponding spin connection, resulting always in the same physically relevant field equations. (paper)
Development of covariance capabilities in EMPIRE code
Energy Technology Data Exchange (ETDEWEB)
Herman,M.; Pigni, M.T.; Oblozinsky, P.; Mughabghab, S.F.; Mattoon, C.M.; Capote, R.; Cho, Young-Sik; Trkov, A.
2008-06-24
The nuclear reaction code EMPIRE has been extended to provide evaluation capabilities for neutron cross section covariances in the thermal, resolved resonance, unresolved resonance and fast neutron regions. The Atlas of Neutron Resonances by Mughabghab is used as a primary source of information on uncertainties at low energies. Care is taken to ensure consistency among the resonance parameter uncertainties and those for thermal cross sections. The resulting resonance parameter covariances are formatted in the ENDF-6 File 32. In the fast neutron range our methodology is based on model calculations with the code EMPIRE combined with experimental data through several available approaches. The model-based covariances can be obtained using deterministic (Kalman) or stochastic (Monte Carlo) propagation of model parameter uncertainties. We show that these two procedures yield comparable results. The Kalman filter and/or the generalized least square fitting procedures are employed to incorporate experimental information. We compare the two approaches analyzing results for the major reaction channels on {sup 89}Y. We also discuss a long-standing issue of unreasonably low uncertainties and link it to the rigidity of the model.
Covariant electrodynamics in linear media: Optical metric
Thompson, Robert T.
2018-03-01
While the postulate of covariance of Maxwell's equations for all inertial observers led Einstein to special relativity, it was the further demand of general covariance—form invariance under general coordinate transformations, including between accelerating frames—that led to general relativity. Several lines of inquiry over the past two decades, notably the development of metamaterial-based transformation optics, has spurred a greater interest in the role of geometry and space-time covariance for electrodynamics in ponderable media. I develop a generally covariant, coordinate-free framework for electrodynamics in general dielectric media residing in curved background space-times. In particular, I derive a relation for the spatial medium parameters measured by an arbitrary timelike observer. In terms of those medium parameters I derive an explicit expression for the pseudo-Finslerian optical metric of birefringent media and show how it reduces to a pseudo-Riemannian optical metric for nonbirefringent media. This formulation provides a basis for a unified approach to ray and congruence tracing through media in curved space-times that may smoothly vary among positively refracting, negatively refracting, and vacuum.
SG39 Deliverables. Comments on Covariance Data
International Nuclear Information System (INIS)
Yokoyama, Kenji
2015-01-01
The covariance matrix of a scattered data set, x_i (i=1,n), must be symmetric and positive-definite. As one of WPEC/SG39 contributions to the SG40/CIELO project, several comments or recommendations on the covariance data are described here from the viewpoint of nuclear-data users. To make the comments concrete and useful for nuclear-data evaluators, the covariance data of the latest evaluated nuclear data library, JENDL-4.0 and ENDF/B-VII.1 are treated here as the representative materials. The surveyed nuclides are five isotopes that are most important for fast reactor application. The nuclides, reactions and energy regions dealt with are followings: Pu-239: fission (2.5∼10 keV) and capture (2.5∼10 keV), U-235: fission (500 eV∼10 keV) and capture (500 eV∼30 keV), U-238: fission (1∼10 MeV), capture (below 20 keV, 20∼150 keV), inelastic (above 100 keV) and elastic (above 20 keV), Fe-56: elastic (below 850 keV) and average scattering cosine (above 10 keV), and, Na-23: capture (600 eV∼600 keV), inelastic (above 1 MeV) and elastic (around 2 keV)
Directory of Open Access Journals (Sweden)
Yichong Li
Full Text Available BACKGROUND: Chronic diseases have become the leading causes of mortality in China and related behavioral risk factors (BRFs changed dramatically in past decades. We aimed to examine the prevalence, co-variations, clustering and the independent correlates of five BRFs at the national level. METHODOLOGY/PRINCIPAL FINDINGS: We used data from the 2007 China Chronic Disease and Risk Factor Surveillance, in which multistage clustering sampling was adopted to collect a nationally representative sample of 49,247 Chinese aged 15 to 69 years. We estimated the prevalence and clustering (mean number of BRFs of five BRFs: tobacco use, excessive alcohol drinking, insufficient intake of vegetable and fruit, physical inactivity, and overweight or obesity. We conducted binary logistic regression models to examine the co-variations among five BRFs with adjustment of demographic and socioeconomic factors, chronic conditions and other BRFs. Ordinal logistic regression was constructed to investigate the independent associations between each covariate and the clustering of BRFs within individuals. Overall, 57.0% of Chinese population had at least two BRFs and the mean number of BRFs is 1.80 (95% confidence interval: 1.78-1.83. Eight of the ten pairs of bivariate associations between the five BRFs were found statistically significant. Chinese with older age, being a male, living in rural areas, having lower education level and lower yearly household income experienced increased likelihood of having more BRFs. CONCLUSIONS/SIGNIFICANCE: Current BRFs place the majority of Chinese aged 15 to 69 years at risk for the future development of chronic disease, which calls for urgent public health programs to reduce these risk factors. Prominent correlations between BRFs imply that a combined package of interventions targeting multiple BRFs might be appropriate. These interventions should target elder population, men, and rural residents, especially those with lower SES.
Directory of Open Access Journals (Sweden)
Minghua Xu
2014-01-01
Full Text Available We consider the problem of seeking a symmetric positive semidefinite matrix in a closed convex set to approximate a given matrix. This problem may arise in several areas of numerical linear algebra or come from finance industry or statistics and thus has many applications. For solving this class of matrix optimization problems, many methods have been proposed in the literature. The proximal alternating direction method is one of those methods which can be easily applied to solve these matrix optimization problems. Generally, the proximal parameters of the proximal alternating direction method are greater than zero. In this paper, we conclude that the restriction on the proximal parameters can be relaxed for solving this kind of matrix optimization problems. Numerical experiments also show that the proximal alternating direction method with the relaxed proximal parameters is convergent and generally has a better performance than the classical proximal alternating direction method.
A Geometrical Framework for Covariance Matrices of Continuous and Categorical Variables
Vernizzi, Graziano; Nakai, Miki
2015-01-01
It is well known that a categorical random variable can be represented geometrically by a simplex. Accordingly, several measures of association between categorical variables have been proposed and discussed in the literature. Moreover, the standard definitions of covariance and correlation coefficient for continuous random variables have been…
Renormalizable Non-Covariant Gauges and Coulomb Gauge Limit
Baulieu, L
1999-01-01
To study ``physical'' gauges such as the Coulomb, light-cone, axial or temporal gauge, we consider ``interpolating'' gauges which interpolate linearly between a covariant gauge, such as the Feynman or Landau gauge, and a physical gauge. Lorentz breaking by the gauge-fixing term of interpolating gauges is controlled by extending the BRST method to include not only the local gauge group, but also the global Lorentz group. We enumerate the possible divergences of interpolating gauges, and show that they are renormalizable, and we show that the expectation value of physical observables is the same as in a covariant gauge. In the second part of the article we study the Coulomb-gauge as the singular limit of the Landau-Coulomb interpolating gauge. We find that unrenormalized and renormalized correlation functions are finite in this limit. We also find that there are finite two-loop diagrams of ``unphysical'' particles that are not present in formal canonical quantization in the Coulomb gauge. We verify that in the ...
The Covariance and Bicovariance of the Stochastic Neutron Field
International Nuclear Information System (INIS)
Perez, R.B.; Mattingly, J.K.; Valentine, T.E.; Mihalczo, J.T.
2000-01-01
On the basis of the general stochastic neutron field theory developed by Munoz-Cobo et al, results on the covariance and bicovariance of the neutron field have been presented. These two statistical quantities are obtained from the counts observed in detectors operating during a period of time (gate length), Δ qc . A classical example is the so called Feynmann Y-function that is defined as the variance to mean ratio of the neutron field. Upon taking the limit of the covariance and bicovariance function for Δ qc r a rrow O , one obtains the two and three detector cross correlation functions respectively. The mathematical structure of the results so obtained have a transparent physical interpretation in terms of the space and delay time overlap between the field-of-view of the detectors. For the first time, an expression has been obtained for the bispectrum function of the stochastic neutron field and for the appropriate weight functions to be used as space-energy-angle correction factors for the one-point kinetics approximation
ERRORJ. Covariance processing code. Version 2.2
International Nuclear Information System (INIS)
Chiba, Go
2004-07-01
ERRORJ is the covariance processing code that can produce covariance data of multi-group cross sections, which are essential for uncertainty analyses of nuclear parameters, such as neutron multiplication factor. The ERRORJ code can process the covariance data of cross sections including resonance parameters, angular and energy distributions of secondary neutrons. Those covariance data cannot be processed by the other covariance processing codes. ERRORJ has been modified and the version 2.2 has been developed. This document describes the modifications and how to use. The main topics of the modifications are as follows. Non-diagonal elements of covariance matrices are calculated in the resonance energy region. Option for high-speed calculation is implemented. Perturbation amount is optimized in a sensitivity calculation. Effect of the resonance self-shielding on covariance of multi-group cross section can be considered. It is possible to read a compact covariance format proposed by N.M. Larson. (author)
Department of Housing and Urban Development — The Department of Housing and Urban Development establishes the rent adjustment factors - called Annual Adjustment Factors (AAFs) - on the basis of Consumer Price...
Finance Division
2001-01-01
On 15 June 2001 the Council approved the correction of the discrepancy identified in the net salary adjustment implemented on 1st January 2001 by retroactively increasing the scale of basic salaries to achieve the 2.8% average net salary adjustment approved in December 2000. We should like to inform you that the corresponding adjustment will be made to your July salary. Full details of the retroactive adjustments will consequently be shown on your pay slip.
The structural, connectomic and network covariance of the human brain.
Irimia, Andrei; Van Horn, John D
2013-02-01
Though it is widely appreciated that complex structural, functional and morphological relationships exist between distinct areas of the human cerebral cortex, the extent to which such relationships coincide remains insufficiently appreciated. Here we determine the extent to which correlations between brain regions are modulated by either structural, connectomic or network-theoretic properties using a structural neuroimaging data set of magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) volumes acquired from N=110 healthy human adults. To identify the linear relationships between all available pairs of regions, we use canonical correlation analysis to test whether a statistically significant correlation exists between each pair of cortical parcels as quantified via structural, connectomic or network-theoretic measures. In addition to this, we investigate (1) how each group of canonical variables (whether structural, connectomic or network-theoretic) contributes to the overall correlation and, additionally, (2) whether each individual variable makes a significant contribution to the test of the omnibus null hypothesis according to which no correlation between regions exists across subjects. We find that, although region-to-region correlations are extensively modulated by structural and connectomic measures, there are appreciable differences in how these two groups of measures drive inter-regional correlation patterns. Additionally, our results indicate that the network-theoretic properties of the cortex are strong modulators of region-to-region covariance. Our findings are useful for understanding the structural and connectomic relationship between various parts of the brain, and can inform theoretical and computational models of cortical information processing. Published by Elsevier Inc.
Generation of integral experiment covariance data and their impact on criticality safety validation
Energy Technology Data Exchange (ETDEWEB)
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
Generation of integral experiment covariance data and their impact on criticality safety validation
International Nuclear Information System (INIS)
Stuke, Maik; Peters, Elisabeth; Sommer, Fabian
2016-11-01
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 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 application
relationship between parenting styles and marital adjustment
African Journals Online (AJOL)
PROF. BARTH EKWEME
positive and significant joint relationship between the parenting styles and marital adjustment of married ... correlate significantly with marital adjustment of married teachers in secondary ... In other words, it refers to the management of ... dealing with each other so as to reduce ill-feeling. ..... Behavior exchange in happy.
Religiousity, Spirituality and Adolescents' Self-Adjustment
Japar, Muhammad; Purwati
2014-01-01
Religiuosity, spirituality, and adolescents' self-adjustment. The objective of this study is to test the correlation among religiosity, spirituality and adolescents' self-adjustment. A quantitative approach was employed in this study. Data were collected from 476 junior high schools students of 13 State Junior High Schools and one Junior High…
Characteristic Polynomials of Sample Covariance Matrices: The Non-Square Case
Kösters, Holger
2009-01-01
We consider the sample covariance matrices of large data matrices which have i.i.d. complex matrix entries and which are non-square in the sense that the difference between the number of rows and the number of columns tends to infinity. We show that the second-order correlation function of the characteristic polynomial of the sample covariance matrix is asymptotically given by the sine kernel in the bulk of the spectrum and by the Airy kernel at the edge of the spectrum. Similar results are g...
Non-stationary pre-envelope covariances of non-classically damped systems
Muscolino, G.
1991-08-01
A new formulation is given to evaluate the stationary and non-stationary response of linear non-classically damped systems subjected to multi-correlated non-separable Gaussian input processes. This formulation is based on a new and more suitable definition of the impulse response function matrix for such systems. It is shown that, when using this definition, the stochastic response of non-classically damped systems involves the evaluation of quantities similar to those of classically damped ones. Furthermore, considerations about non-stationary cross-covariances, spectral moments and pre-envelope cross-covariances are presented for a monocorrelated input process.
Comparative Analyses of Phenotypic Trait Covariation within and among Populations.
Peiman, Kathryn S; Robinson, Beren W
2017-10-01
Many morphological, behavioral, physiological, and life-history traits covary across the biological scales of individuals, populations, and species. However, the processes that cause traits to covary also change over these scales, challenging our ability to use patterns of trait covariance to infer process. Trait relationships are also widely assumed to have generic functional relationships with similar evolutionary potentials, and even though many different trait relationships are now identified, there is little appreciation that these may influence trait covariation and evolution in unique ways. We use a trait-performance-fitness framework to classify and organize trait relationships into three general classes, address which ones more likely generate trait covariation among individuals in a population, and review how selection shapes phenotypic covariation. We generate predictions about how trait covariance changes within and among populations as a result of trait relationships and in response to selection and consider how these can be tested with comparative data. Careful comparisons of covariation patterns can narrow the set of hypothesized processes that cause trait covariation when the form of the trait relationship and how it responds to selection yield clear predictions about patterns of trait covariation. We discuss the opportunities and limitations of comparative approaches to evaluate hypotheses about the evolutionary causes and consequences of trait covariation and highlight the importance of evaluating patterns within populations replicated in the same and in different selective environments. Explicit hypotheses about trait relationships are key to generating effective predictions about phenotype and its evolution using covariance data.
Covariant differential calculus on quantum spheres of odd dimension
International Nuclear Information System (INIS)
Welk, M.
1998-01-01
Covariant differential calculus on the quantum spheres S q 2N-1 is studied. Two classification results for covariant first order differential calculi are proved. As an important step towards a description of the noncommutative geometry of the quantum spheres, a framework of covariant differential calculus is established, including first and higher order calculi and a symmetry concept. (author)
Evaluation of covariance in theoretical calculation of nuclear data
International Nuclear Information System (INIS)
Kikuchi, Yasuyuki
1981-01-01
Covariances of the cross sections are discussed on the statistical model calculations. Two categories of covariance are discussed: One is caused by the model approximation and the other by the errors in the model parameters. As an example, the covariances are calculated for 100 Ru. (author)
Earth Observation System Flight Dynamics System Covariance Realism
Zaidi, Waqar H.; Tracewell, David
2016-01-01
This presentation applies a covariance realism technique to the National Aeronautics and Space Administration (NASA) Earth Observation System (EOS) Aqua and Aura spacecraft based on inferential statistics. The technique consists of three parts: collection calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics.
Evaluation of covariance for 238U cross sections
International Nuclear Information System (INIS)
Kawano, Toshihiko; Nakamura, Masahiro; Matsuda, Nobuyuki; Kanda, Yukinori
1995-01-01
Covariances of 238 U are generated using analytic functions for representation of the cross sections. The covariances of the (n,2n) and (n,3n) reactions are derived with a spline function, while the covariances of the total and the inelastic scattering cross section are estimated with a linearized nuclear model calculation. (author)
Culture, emotion regulation, and adjustment.
Matsumoto, David; Yoo, Seung Hee; Nakagawa, Sanae
2008-06-01
This article reports differences across 23 countries on 2 processes of emotion regulation--reappraisal and suppression. Cultural dimensions were correlated with country means on both and the relationship between them. Cultures that emphasized the maintenance of social order--that is, those that were long-term oriented and valued embeddedness and hierarchy--tended to have higher scores on suppression, and reappraisal and suppression tended to be positively correlated. In contrast, cultures that minimized the maintenance of social order and valued individual Affective Autonomy and Egalitarianism tended to have lower scores on Suppression, and Reappraisal and Suppression tended to be negatively correlated. Moreover, country-level emotion regulation was significantly correlated with country-level indices of both positive and negative adjustment. (PsycINFO Database Record (c) 2008 APA, all rights reserved).
The production and transmission of covariance in the evaluation processing of fission yield data
International Nuclear Information System (INIS)
Liu Tingjin
2001-01-01
The production and transmission of correlation in the evaluation processing of fission yield data, including average with weight, ratio and sum consistence adjusting, are researched. The variation of the averaged and adjusted yields and/or rations with the correlation coefficient of the input data are investigated. The results obtained are reasonable in physics
Non-evaluation applications for covariance matrices
Energy Technology Data Exchange (ETDEWEB)
Smith, D.L.
1982-05-01
The possibility for application of covariance matrix techniques to a variety of common research problems other than formal data evaluation are demonstrated by means of several examples. These examples deal with such matters as fitting spectral data, deriving uncertainty estimates for results calculated from experimental data, obtaining the best values for plurally-measured quantities, and methods for analysis of cross section errors based on properties of the experiment. The examples deal with realistic situations encountered in the laboratory, and they are treated in sufficient detail to enable a careful reader to extrapolate the methods to related problems.
Covariant, chirally symmetric, confining model of mesons
International Nuclear Information System (INIS)
Gross, F.; Milana, J.
1991-01-01
We introduce a new model of mesons as quark-antiquark bound states. The model is covariant, confining, and chirally symmetric. Our equations give an analytic solution for a zero-mass pseudoscalar bound state in the case of exact chiral symmetry, and also reduce to the familiar, highly successful nonrelativistic linear potential models in the limit of heavy-quark mass and lightly bound systems. In this fashion we are constructing a unified description of all the mesons from the π through the Υ. Numerical solutions for other cases are also presented
Cosmology of a covariant Galilean field.
De Felice, Antonio; Tsujikawa, Shinji
2010-09-10
We study the cosmology of a covariant scalar field respecting a Galilean symmetry in flat space-time. We show the existence of a tracker solution that finally approaches a de Sitter fixed point responsible for cosmic acceleration today. The viable region of model parameters is clarified by deriving conditions under which ghosts and Laplacian instabilities of scalar and tensor perturbations are absent. The field equation of state exhibits a peculiar phantomlike behavior along the tracker, which allows a possibility to observationally distinguish the Galileon gravity from the cold dark matter model with a cosmological constant.
Covariant differential complexes of quantum linear groups
International Nuclear Information System (INIS)
Isaev, A.P.; Pyatov, P.N.
1993-01-01
We consider the possible covariant external algebra structures for Cartan's 1-forms (Ω) on G L q (N) and S L q (N). Our starting point is that Ω s realize an adjoint representation of quantum group and all monomials of Ω s possess the unique ordering. For the obtained external algebras we define the differential mapping d possessing the usual nilpotence condition, and the generally deformed version of Leibnitz rules. The status of the known examples of G L q (N)-differential calculi in the proposed classification scheme and the problems of S L q (N)-reduction are discussed. (author.). 26 refs
Minimal covariant observables identifying all pure states
Energy Technology Data Exchange (ETDEWEB)
Carmeli, Claudio, E-mail: claudio.carmeli@gmail.com [D.I.M.E., Università di Genova, Via Cadorna 2, I-17100 Savona (Italy); I.N.F.N., Sezione di Genova, Via Dodecaneso 33, I-16146 Genova (Italy); Heinosaari, Teiko, E-mail: teiko.heinosaari@utu.fi [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku (Finland); Toigo, Alessandro, E-mail: alessandro.toigo@polimi.it [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); I.N.F.N., Sezione di Milano, Via Celoria 16, I-20133 Milano (Italy)
2013-09-02
It has been recently shown by Heinosaari, Mazzarella and Wolf (2013) [1] that an observable that identifies all pure states of a d-dimensional quantum system has minimally 4d−4 outcomes or slightly less (the exact number depending on d). However, no simple construction of this type of minimal observable is known. We investigate covariant observables that identify all pure states and have minimal number of outcomes. It is shown that the existence of this kind of observables depends on the dimension of the Hilbert space.
Linear Covariance Analysis and Epoch State Estimators
Markley, F. Landis; Carpenter, J. Russell
2014-01-01
This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.
Agnostic Estimation of Mean and Covariance
Lai, Kevin A.; Rao, Anup B.; Vempala, Santosh
2016-01-01
We consider the problem of estimating the mean and covariance of a distribution from iid samples in $\\mathbb{R}^n$, in the presence of an $\\eta$ fraction of malicious noise; this is in contrast to much recent work where the noise itself is assumed to be from a distribution of known type. The agnostic problem includes many interesting special cases, e.g., learning the parameters of a single Gaussian (or finding the best-fit Gaussian) when $\\eta$ fraction of data is adversarially corrupted, agn...
On the Galilean covariance of classical mechanics
International Nuclear Information System (INIS)
Horzela, A.; Kapuscik, E.; Kempczynski, J.; Joint Inst. for Nuclear Research, Dubna
1991-08-01
A Galilean covariant approach to classical mechanics of a single interacting particle is described. In this scheme constitutive relations defining forces are rejected and acting forces are determined by some fundamental differential equations. It is shown that total energy of the interacting particle transforms under Galilean transformations differently from the kinetic energy. The statement is illustrated on the exactly solvable examples of the harmonic oscillator and the case of constant forces and also, in the suitable version of the perturbation theory, for the anharmonic oscillator. (author)
Determination of covariant Schwinger terms in anomalous gauge theories
International Nuclear Information System (INIS)
Kelnhofer, G.
1991-01-01
A functional integral method is used to determine equal time commutators between the covariant currents and the covariant Gauss-law operators in theories which are affected by an anomaly. By using a differential geometrical setup we show how the derivation of consistent- and covariant Schwinger terms can be understood on an equal footing. We find a modified consistency condition for the covariant anomaly. As a by-product the Bardeen-Zumino functional, which relates consistent and covariant anomalies, can be interpreted as connection on a certain line bundle over all gauge potentials. Finally the commutator anomalies are calculated for the two- and four dimensional case. (Author) 13 refs
ERRORJ. Covariance processing code system for JENDL. Version 2
International Nuclear Information System (INIS)
Chiba, Gou
2003-09-01
ERRORJ is the covariance processing code system for Japanese Evaluated Nuclear Data Library (JENDL) that can produce group-averaged covariance data to apply it to the uncertainty analysis of nuclear characteristics. ERRORJ can treat the covariance data for cross sections including resonance parameters as well as angular distributions and energy distributions of secondary neutrons which could not be dealt with by former covariance processing codes. In addition, ERRORJ can treat various forms of multi-group cross section and produce multi-group covariance file with various formats. This document describes an outline of ERRORJ and how to use it. (author)
PIA and REWIND: Two New Methodologies for Cross Section Adjustment
Energy Technology Data Exchange (ETDEWEB)
Palmiotti, G.; Salvatores, M.
2017-02-01
This paper presents two new cross section adjustment methodologies intended for coping with the problem of compensations. The first one PIA, Progressive Incremental Adjustment, gives priority to the utilization of experiments of elemental type (those sensitive to a specific cross section), following a definite hierarchy on which type of experiment to use. Once the adjustment is performed, both the new adjusted data and the new covariance matrix are kept. The second methodology is called REWIND (Ranking Experiments by Weighting for Improved Nuclear Data). This new proposed approach tries to establish a methodology for ranking experiments by looking at the potential gain they can produce in an adjustment. Practical applications for different adjustments illustrate the results of the two methodologies against the current one and show the potential improvement for reducing uncertainties in target reactors.
van Binsbergen, R; Veerkamp, R F; Calus, M P L
2012-04-01
The correlated responses between traits may differ depending on the makeup of genetic covariances, and may differ from the predictions of polygenic covariances. Therefore, the objective of the present study was to investigate the makeup of the genetic covariances between the well-studied traits: milk yield, fat yield, protein yield, and their percentages in more detail. Phenotypic records of 1,737 heifers of research farms in 4 different countries were used after homogenizing and adjusting for management effects. All cows had a genotype for 37,590 single nucleotide polymorphisms (SNP). A bayesian stochastic search variable selection model was used to estimate the SNP effects for each trait. About 0.5 to 1.0% of the SNP had a significant effect on 1 or more traits; however, the SNP without a significant effect explained most of the genetic variances and covariances of the traits. Single nucleotide polymorphism correlations differed from the polygenic correlations, but only 10 regions were found with an effect on multiple traits; in 1 of these regions the DGAT1 gene was previously reported with an effect on multiple traits. This region explained up to 41% of the variances of 4 traits and explained a major part of the correlation between fat yield and fat percentage and contributes to asymmetry in correlated response between fat yield and fat percentage. Overall, for the traits in this study, the infinitesimal model is expected to be sufficient for the estimation of the variances and covariances. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Use of error files in uncertainty analysis and data adjustment
International Nuclear Information System (INIS)
Chestnutt, M.M.; McCracken, A.K.; McCracken, A.K.
1979-01-01
Some results are given from uncertainty analyses on Pressurized Water Reactor (PWR) and Fast Reactor Theoretical Benchmarks. Upper limit estimates of calculated quantities are shown to be significantly reduced by the use of ENDF/B data covariance files and recently published few-group covariance matrices. Some problems in the analysis of single-material benchmark experiments are discussed with reference to the Winfrith iron benchmark experiment. Particular attention is given to the difficulty of making use of very extensive measurements which are likely to be a feature of this type of experiment. Preliminary results of an adjustment in iron are shown
Sang, Huiyan
2011-12-01
This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models. Our method allows for a nonseparable and nonstationary cross-covariance structure. We also present a covariance approximation approach to facilitate the computation in the modeling and analysis of very large multivariate spatial data sets. The covariance approximation consists of two parts: a reduced-rank part to capture the large-scale spatial dependence, and a sparse covariance matrix to correct the small-scale dependence error induced by the reduced rank approximation. We pay special attention to the case that the second part of the approximation has a block-diagonal structure. Simulation results of model fitting and prediction show substantial improvement of the proposed approximation over the predictive process approximation and the independent blocks analysis. We then apply our computational approach to the joint statistical modeling of multiple climate model errors. © 2012 Institute of Mathematical Statistics.
Li, Baoyue; Bruyneel, Luk; Lesaffre, Emmanuel
2014-05-20
A traditional Gaussian hierarchical model assumes a nested multilevel structure for the mean and a constant variance at each level. We propose a Bayesian multivariate multilevel factor model that assumes a multilevel structure for both the mean and the covariance matrix. That is, in addition to a multilevel structure for the mean we also assume that the covariance matrix depends on covariates and random effects. This allows to explore whether the covariance structure depends on the values of the higher levels and as such models heterogeneity in the variances and correlation structure of the multivariate outcome across the higher level values. The approach is applied to the three-dimensional vector of burnout measurements collected on nurses in a large European study to answer the research question whether the covariance matrix of the outcomes depends on recorded system-level features in the organization of nursing care, but also on not-recorded factors that vary with countries, hospitals, and nursing units. Simulations illustrate the performance of our modeling approach. Copyright © 2013 John Wiley & Sons, Ltd.
A method to construct covariance files in ENDF/B format for criticality safety applications
International Nuclear Information System (INIS)
Naberejnev, D.G.; Smith, D.L.
1999-01-01
Argonne National Laboratory is providing support for a criticality safety analysis project that is being performed at Oak Ridge National Laboratory. The ANL role is to provide the covariance information needed by ORNL for this project. The ENDF/B-V evaluation is being used for this particular criticality analysis. In this evaluation, covariance information for several isotopes or elements of interest to this analysis is either not given or needs to be reconsidered. For some required materials, covariance information does not exist in ENDF/B-V: 233 U, 236 U, Zr, Mg, Gd, and Hf. For others, existing covariance information may need to be re-examined in light of the newer ENDF/B-V evaluation and recent experimental data. In this category are the following materials: 235 U, 238 U, 239 Pu, 240 Pu, 241 Pu, Fe, H, C, N, O, Al, Si, and B. A reasonable estimation of the fractional errors for various evaluated neutron cross sections from ENDF/B-V can be based on the comparisons between the major more recent evaluations including ENDF/B-VI, JENDL3.2, BROND2.2, and JEF2.2, as well as a careful examination of experimental data. A reasonable method to construct correlation matrices is proposed here. Coupling both of these considerations suggests a method to construct covariances files in ENDF/B format that can be used to express uncertainties for specific ENDF/B-V cross sections
Yoneoka, Daisuke; Henmi, Masayuki
2017-06-01
Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the sets of covariates differ across models, interpretation of coefficients will differ, thereby making it difficult to synthesize them. Moreover, previous synthesis methods for regression models, such as multivariate meta-analysis, often have problems because covariance matrix of coefficients (i.e. within-study correlations) or individual patient data are not necessarily available. This study, therefore, proposes a brief explanation regarding a method to synthesize linear regression models under different covariate sets by using a generalized least squares method involving bias correction terms. Especially, we also propose an approach to recover (at most) threecorrelations of covariates, which is required for the calculation of the bias term without individual patient data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Disruption of structural covariance networks for language in autism is modulated by verbal ability.
Sharda, Megha; Khundrakpam, Budhachandra S; Evans, Alan C; Singh, Nandini C
2016-03-01
The presence of widespread speech and language deficits is a core feature of autism spectrum disorders (ASD). These impairments have often been attributed to altered connections between brain regions. Recent developments in anatomical correlation-based approaches to map structural covariance offer an effective way of studying such connections in vivo. In this study, we employed such a structural covariance network (SCN)-based approach to investigate the integrity of anatomical networks in fronto-temporal brain regions of twenty children with ASD compared to an age and gender-matched control group of twenty-two children. Our findings reflected large-scale disruption of inter and intrahemispheric covariance in left frontal SCNs in the ASD group compared to controls, but no differences in right fronto-temporal SCNs. Interhemispheric covariance in left-seeded networks was further found to be modulated by verbal ability of the participants irrespective of autism diagnosis, suggesting that language function might be related to the strength of interhemispheric structural covariance between frontal regions. Additionally, regional cortical thickening was observed in right frontal and left posterior regions, which was predicted by decreasing symptom severity and increasing verbal ability in ASD. These findings unify reports of regional differences in cortical morphology in ASD. They also suggest that reduced left hemisphere asymmetry and increased frontal growth may not only reflect neurodevelopmental aberrations but also compensatory mechanisms.
International Nuclear Information System (INIS)
Takada, Masahiro; Bridle, Sarah
2007-01-01
Several dark energy experiments are available from a single large-area imaging survey and may be combined to improve cosmological parameter constraints and/or test inherent systematics. Two promising experiments are cosmic shear power spectra and counts of galaxy clusters. However, the two experiments probe the same cosmic mass density field in large-scale structure, therefore the combination may be less powerful than first thought. We investigate the cross-covariance between the cosmic shear power spectra and the cluster counts based on the halo model approach, where the cross-covariance arises from the three-point correlations of the underlying mass density field. Fully taking into account the cross-covariance, as well as non-Gaussian errors on the lensing power spectrum covariance, we find a significant cross-correlation between the lensing power spectrum signals at multipoles l∼10 3 and the cluster counts containing halos with masses M∼>10 14 M o-dot . Including the cross-covariance for the combined measurement degrades and in some cases improves the total signal-to-noise (S/N) ratios up to ∼±20% relative to when the two are independent. For cosmological parameter determination, the cross-covariance has a smaller effect as a result of working in a multi-dimensional parameter space, implying that the two observables can be considered independent to a good approximation. We also discuss the fact that cluster count experiments using lensing-selected mass peaks could be more complementary to cosmic shear tomography than mass-selected cluster counts of the corresponding mass threshold. Using lensing selected clusters with a realistic usable detection threshold ((S/N) cluster ∼6 for a ground-based survey), the uncertainty on each dark energy parameter may be roughly halved by the combined experiments, relative to using the power spectra alone
A pilot study of cognitive insight and structural covariance in first-episode psychosis.
Kuang, Corin; Buchy, Lisa; Barbato, Mariapaola; Makowski, Carolina; MacMaster, Frank P; Bray, Signe; Deighton, Stephanie; Addington, Jean
2017-01-01
Cognitive insight is described as a balance between one's self-reflectiveness (recognition and correction of dysfunctional reasoning), and self-certainty (overconfidence). Neuroimaging studies have linked the ventrolateral prefrontal cortex (VLPFC) to cognitive insight in people with psychosis. However, the relationship between cognitive insight and structural connectivity between the VLPFC and other brain areas is unknown. Here, we investigated the modulation of cognitive insight on structural covariance networks involving the VLPFC in a first-episode psychosis sample. Fifteen patients with a first-episode psychosis provided magnetic resonance (MR) scans and completed the Beck Cognitive Insight Scale (BCIS). MR scans were also available for 15 historical controls. Seed-based analysis of structural covariance was conducted using the Mapping Anatomical Correlations Across the Cerebral Cortex (MACACC) methodology, whereby Pearson correlation coefficients were extracted between seed regions in left and right VLPFC and cortical thickness across the brain. Structural covariance maps between groups were compared at each vertex. In first-episode subjects, we evaluated the modulation of BCIS scores on cortical covariance between VLPFC and every other vertex. Findings showed no significant group difference between first-episode psychosis subjects and controls in thickness covariance seeded from left or right VLPFC. However, in first-episode psychosis subjects, a positive association with self-certainty was found in networks seeded from both left and right VLPFC with thickness in medial frontal cortex and right pars triangularis. No significant associations were found for self-reflectiveness. These results suggest that self-certainty, but not self-reflectiveness, positively modulated cortical covariance in a frontal network in patients with a first-episode psychosis. Copyright © 2016 Elsevier B.V. All rights reserved.
Piecewise linear regression splines with hyperbolic covariates
International Nuclear Information System (INIS)
Cologne, John B.; Sposto, Richard
1992-09-01
Consider the problem of fitting a curve to data that exhibit a multiphase linear response with smooth transitions between phases. We propose substituting hyperbolas as covariates in piecewise linear regression splines to obtain curves that are smoothly joined. The method provides an intuitive and easy way to extend the two-phase linear hyperbolic response model of Griffiths and Miller and Watts and Bacon to accommodate more than two linear segments. The resulting regression spline with hyperbolic covariates may be fit by nonlinear regression methods to estimate the degree of curvature between adjoining linear segments. The added complexity of fitting nonlinear, as opposed to linear, regression models is not great. The extra effort is particularly worthwhile when investigators are unwilling to assume that the slope of the response changes abruptly at the join points. We can also estimate the join points (the values of the abscissas where the linear segments would intersect if extrapolated) if their number and approximate locations may be presumed known. An example using data on changing age at menarche in a cohort of Japanese women illustrates the use of the method for exploratory data analysis. (author)
Zhaunerchyk, V.; Frasinski, L. J.; Eland, J. H. D.; Feifel, R.
2014-05-01
Multidimensional covariance analysis and its validity for correlation of processes leading to multiple products are investigated from a theoretical point of view. The need to correct for false correlations induced by experimental parameters which fluctuate from shot to shot, such as the intensity of self-amplified spontaneous emission x-ray free-electron laser pulses, is emphasized. Threefold covariance analysis based on simple extension of the two-variable formulation is shown to be valid for variables exhibiting Poisson statistics. In this case, false correlations arising from fluctuations in an unstable experimental parameter that scale linearly with signals can be eliminated by threefold partial covariance analysis, as defined here. Fourfold covariance based on the same simple extension is found to be invalid in general. Where fluctuations in an unstable parameter induce nonlinear signal variations, a technique of contingent covariance analysis is proposed here to suppress false correlations. In this paper we also show a method to eliminate false correlations associated with fluctuations of several unstable experimental parameters.
Nuclear Data Parameter Adjustment BNL-INL
International Nuclear Information System (INIS)
Palmiotti, G.; Hoblit, S.; Herman, M.; Nobre, G.P.A.; Palumbo, A.; Hiruta, H.; Salvatores, M.
2013-01-01
This presentation reports on the consistent adjustment of nuclear data parameters performed within a BNL-INL collaboration. The main advantage compared to the classical adjustment of multigroup constants is to provide final nuclear data constrained by the nuclear reaction theory and consistent with both differential and integral measurements. The feasibility of a single-isotope assimilation was tested on a few priority materials ( 23 Na, 56 Fe, 105 Pd, 235,238 U, 239 Pu) using a selection of clean integral experiments. The multi-isotope assimilation is under study for the Big-3 ( 235,238 U, 239 Pu). This work shows that a consistent assimilation is feasible, but there are pitfalls to avoid (e.g. non-linearity, cross section fluctuations) and prerequisites (e.g. realistic covariances, good prior, realistic weighting of differential and integral experiments). Finally, only all experimental information combined with the state of the art modelling may provide a 'right' answer
Gaskins, J T; Daniels, M J
2016-01-02
The estimation of the covariance matrix is a key concern in the analysis of longitudinal data. When data consists of multiple groups, it is often assumed the covariance matrices are either equal across groups or are completely distinct. We seek methodology to allow borrowing of strength across potentially similar groups to improve estimation. To that end, we introduce a covariance partition prior which proposes a partition of the groups at each measurement time. Groups in the same set of the partition share dependence parameters for the distribution of the current measurement given the preceding ones, and the sequence of partitions is modeled as a Markov chain to encourage similar structure at nearby measurement times. This approach additionally encourages a lower-dimensional structure of the covariance matrices by shrinking the parameters of the Cholesky decomposition toward zero. We demonstrate the performance of our model through two simulation studies and the analysis of data from a depression study. This article includes Supplementary Material available online.
Repatriation Adjustment: Literature Review
Directory of Open Access Journals (Sweden)
Gamze Arman
2009-12-01
Full Text Available Expatriation is a widely studied area of research in work and organizational psychology. After expatriates accomplish their missions in host countries, they return to their countries and this process is called repatriation. Adjustment constitutes a crucial part in repatriation research. In the present literature review, research about repatriation adjustment was reviewed with the aim of defining the whole picture in this phenomenon. Present research was classified on the basis of a theoretical model of repatriation adjustment. Basic frame consisted of antecedents, adjustment, outcomes as main variables and personal characteristics/coping strategies and organizational strategies as moderating variables.
A neural circuit covarying with social hierarchy in macaques.
Noonan, MaryAnn P; Sallet, Jerome; Mars, Rogier B; Neubert, Franz X; O'Reilly, Jill X; Andersson, Jesper L; Mitchell, Anna S; Bell, Andrew H; Miller, Karla L; Rushworth, Matthew F S
2014-09-01
Despite widespread interest in social dominance, little is known of its neural correlates in primates. We hypothesized that social status in primates might be related to individual variation in subcortical brain regions implicated in other aspects of social and emotional behavior in other mammals. To examine this possibility we used magnetic resonance imaging (MRI), which affords the taking of quantitative measurements noninvasively, both of brain structure and of brain function, across many regions simultaneously. We carried out a series of tests of structural and functional MRI (fMRI) data in 25 group-living macaques. First, a deformation-based morphometric (DBM) approach was used to show that gray matter in the amygdala, brainstem in the vicinity of the raphe nucleus, and reticular formation, hypothalamus, and septum/striatum of the left hemisphere was correlated with social status. Second, similar correlations were found in the same areas in the other hemisphere. Third, similar correlations were found in a second data set acquired several months later from a subset of the same animals. Fourth, the strength of coupling between fMRI-measured activity in the same areas was correlated with social status. The network of subcortical areas, however, had no relationship with the sizes of individuals' social networks, suggesting the areas had a simple and direct relationship with social status. By contrast a second circuit in cortex, comprising the midsuperior temporal sulcus and anterior and dorsal prefrontal cortex, covaried with both individuals' social statuses and the social network sizes they experienced. This cortical circuit may be linked to the social cognitive processes that are taxed by life in more complex social networks and that must also be used if an animal is to achieve a high social status.
A neural circuit covarying with social hierarchy in macaques.
Directory of Open Access Journals (Sweden)
MaryAnn P Noonan
2014-09-01
Full Text Available Despite widespread interest in social dominance, little is known of its neural correlates in primates. We hypothesized that social status in primates might be related to individual variation in subcortical brain regions implicated in other aspects of social and emotional behavior in other mammals. To examine this possibility we used magnetic resonance imaging (MRI, which affords the taking of quantitative measurements noninvasively, both of brain structure and of brain function, across many regions simultaneously. We carried out a series of tests of structural and functional MRI (fMRI data in 25 group-living macaques. First, a deformation-based morphometric (DBM approach was used to show that gray matter in the amygdala, brainstem in the vicinity of the raphe nucleus, and reticular formation, hypothalamus, and septum/striatum of the left hemisphere was correlated with social status. Second, similar correlations were found in the same areas in the other hemisphere. Third, similar correlations were found in a second data set acquired several months later from a subset of the same animals. Fourth, the strength of coupling between fMRI-measured activity in the same areas was correlated with social status. The network of subcortical areas, however, had no relationship with the sizes of individuals' social networks, suggesting the areas had a simple and direct relationship with social status. By contrast a second circuit in cortex, comprising the midsuperior temporal sulcus and anterior and dorsal prefrontal cortex, covaried with both individuals' social statuses and the social network sizes they experienced. This cortical circuit may be linked to the social cognitive processes that are taxed by life in more complex social networks and that must also be used if an animal is to achieve a high social status.
A Neural Circuit Covarying with Social Hierarchy in Macaques
Neubert, Franz X.; O'Reilly, Jill X.; Andersson, Jesper L.; Mitchell, Anna S.; Bell, Andrew H.; Miller, Karla L.; Rushworth, Matthew F. S.
2014-01-01
Despite widespread interest in social dominance, little is known of its neural correlates in primates. We hypothesized that social status in primates might be related to individual variation in subcortical brain regions implicated in other aspects of social and emotional behavior in other mammals. To examine this possibility we used magnetic resonance imaging (MRI), which affords the taking of quantitative measurements noninvasively, both of brain structure and of brain function, across many regions simultaneously. We carried out a series of tests of structural and functional MRI (fMRI) data in 25 group-living macaques. First, a deformation-based morphometric (DBM) approach was used to show that gray matter in the amygdala, brainstem in the vicinity of the raphe nucleus, and reticular formation, hypothalamus, and septum/striatum of the left hemisphere was correlated with social status. Second, similar correlations were found in the same areas in the other hemisphere. Third, similar correlations were found in a second data set acquired several months later from a subset of the same animals. Fourth, the strength of coupling between fMRI-measured activity in the same areas was correlated with social status. The network of subcortical areas, however, had no relationship with the sizes of individuals' social networks, suggesting the areas had a simple and direct relationship with social status. By contrast a second circuit in cortex, comprising the midsuperior temporal sulcus and anterior and dorsal prefrontal cortex, covaried with both individuals' social statuses and the social network sizes they experienced. This cortical circuit may be linked to the social cognitive processes that are taxed by life in more complex social networks and that must also be used if an animal is to achieve a high social status. PMID:25180883
NParCov3: A SAS/IML Macro for Nonparametric Randomization-Based Analysis of Covariance
Directory of Open Access Journals (Sweden)
Richard C. Zink
2012-07-01
Full Text Available Analysis of covariance serves two important purposes in a randomized clinical trial. First, there is a reduction of variance for the treatment effect which provides more powerful statistical tests and more precise confidence intervals. Second, it provides estimates of the treatment effect which are adjusted for random imbalances of covariates between the treatment groups. The nonparametric analysis of covariance method of Koch, Tangen, Jung, and Amara (1998 defines a very general methodology using weighted least-squares to generate covariate-adjusted treatment effects with minimal assumptions. This methodology is general in its applicability to a variety of outcomes, whether continuous, binary, ordinal, incidence density or time-to-event. Further, its use has been illustrated in many clinical trial settings, such as multi-center, dose-response and non-inferiority trials.NParCov3 is a SAS/IML macro written to conduct the nonparametric randomization-based covariance analyses of Koch et al. (1998. The software can analyze a variety of outcomes and can account for stratification. Data from multiple clinical trials will be used for illustration.
Noisy covariance matrices and portfolio optimization II
Pafka, Szilárd; Kondor, Imre
2003-03-01
Recent studies inspired by results from random matrix theory (Galluccio et al.: Physica A 259 (1998) 449; Laloux et al.: Phys. Rev. Lett. 83 (1999) 1467; Risk 12 (3) (1999) 69; Plerou et al.: Phys. Rev. Lett. 83 (1999) 1471) found that covariance matrices determined from empirical financial time series appear to contain such a high amount of noise that their structure can essentially be regarded as random. This seems, however, to be in contradiction with the fundamental role played by covariance matrices in finance, which constitute the pillars of modern investment theory and have also gained industry-wide applications in risk management. Our paper is an attempt to resolve this embarrassing paradox. The key observation is that the effect of noise strongly depends on the ratio r= n/ T, where n is the size of the portfolio and T the length of the available time series. On the basis of numerical experiments and analytic results for some toy portfolio models we show that for relatively large values of r (e.g. 0.6) noise does, indeed, have the pronounced effect suggested by Galluccio et al. (1998), Laloux et al. (1999) and Plerou et al. (1999) and illustrated later by Laloux et al. (Int. J. Theor. Appl. Finance 3 (2000) 391), Plerou et al. (Phys. Rev. E, e-print cond-mat/0108023) and Rosenow et al. (Europhys. Lett., e-print cond-mat/0111537) in a portfolio optimization context, while for smaller r (around 0.2 or below), the error due to noise drops to acceptable levels. Since the length of available time series is for obvious reasons limited in any practical application, any bound imposed on the noise-induced error translates into a bound on the size of the portfolio. In a related set of experiments we find that the effect of noise depends also on whether the problem arises in asset allocation or in a risk measurement context: if covariance matrices are used simply for measuring the risk of portfolios with a fixed composition rather than as inputs to optimization, the
Meier, Timothy B; Wildenberg, Joseph C; Liu, Jingyu; Chen, Jiayu; Calhoun, Vince D; Biswal, Bharat B; Meyerand, Mary E; Birn, Rasmus M; Prabhakaran, Vivek
2012-01-01
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.
Wu, Huawang; Sun, Hui; Wang, Chao; Yu, Lin; Li, Yilan; Peng, Hongjun; Lu, Xiaobing; Hu, Qingmao; Ning, Yuping; Jiang, Tianzi; Xu, Jinping; Wang, Jiaojian
2017-01-01
Major depressive disorder (MDD) is a common psychiatric disorder that is characterized by cognitive deficits and affective symptoms. To date, an increasing number of neuroimaging studies have focused on emotion regulation and have consistently shown that emotion dysregulation is one of the central features and underlying mechanisms of MDD. Although gray matter morphological abnormalities in regions within emotion regulation networks have been identified in MDD, the interactions and relationships between these gray matter structures remain largely unknown. Thus, in this study, we adopted a structural covariance method based on gray matter volume to investigate the brain morphological abnormalities within the emotion regulation networks in a large cohort of 65 MDD patients and 65 age- and gender-matched healthy controls. A permutation test with p covariance connectivity strengths between MDD patients and healthy controls. The structural covariance analysis revealed an increased correlation strength of gray matter volume between the left angular gyrus and the left amygdala and between the right angular gyrus and the right amygdala, as well as a decreased correlation strength of the gray matter volume between the right angular gyrus and the posterior cingulate cortex in MDD. Our findings support the notion that emotion dysregulation is an underlying mechanism of MDD by revealing disrupted structural covariance patterns in the emotion regulation network. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Computing more proper covariances of energy dependent nuclear data
International Nuclear Information System (INIS)
Vanhanen, R.
2016-01-01
Highlights: • We present conditions for covariances of energy dependent nuclear data to be proper. • We provide methods to detect non-positive and inconsistent covariances in ENDF-6 format. • We propose methods to find nearby more proper covariances. • The methods can be used as a part of a quality assurance program. - Abstract: We present conditions for covariances of energy dependent nuclear data to be proper in the sense that the covariances are positive, i.e., its eigenvalues are non-negative, and consistent with respect to the sum rules of nuclear data. For the ENDF-6 format covariances we present methods to detect non-positive and inconsistent covariances. These methods would be useful as a part of a quality assurance program. We also propose methods that can be used to find nearby more proper energy dependent covariances. These methods can be used to remove unphysical components, while preserving most of the physical components. We consider several different senses in which the nearness can be measured. These methods could be useful if a re-evaluation of improper covariances is not feasible. Two practical examples are processed and analyzed. These demonstrate some of the properties of the methods. We also demonstrate that the ENDF-6 format covariances of linearly dependent nuclear data should usually be encoded with the derivation rules.
Impact of the 235U Covariance Data in Benchmark Calculations
International Nuclear Information System (INIS)
Leal, Luiz C.; Mueller, D.; Arbanas, G.; Wiarda, D.; Derrien, H.
2008-01-01
The error estimation for calculated quantities relies on nuclear data uncertainty information available in the basic nuclear data libraries such as the U.S. Evaluated Nuclear Data File (ENDF/B). The uncertainty files (covariance matrices) in the ENDF/B library are generally obtained from analysis of experimental data. In the resonance region, the computer code SAMMY is used for analyses of experimental data and generation of resonance parameters. In addition to resonance parameters evaluation, SAMMY also generates resonance parameter covariance matrices (RPCM). SAMMY uses the generalized least-squares formalism (Bayes method) together with the resonance formalism (R-matrix theory) for analysis of experimental data. Two approaches are available for creation of resonance-parameter covariance data. (1) During the data-evaluation process, SAMMY generates both a set of resonance parameters that fit the experimental data and the associated resonance-parameter covariance matrix. (2) For existing resonance-parameter evaluations for which no resonance-parameter covariance data are available, SAMMY can retroactively create a resonance-parameter covariance matrix. The retroactive method was used to generate covariance data for 235U. The resulting 235U covariance matrix was then used as input to the PUFF-IV code, which processed the covariance data into multigroup form, and to the TSUNAMI code, which calculated the uncertainty in the multiplication factor due to uncertainty in the experimental cross sections. The objective of this work is to demonstrate the use of the 235U covariance data in calculations of critical benchmark systems
Development of covariance date for fast reactor cores. 3
International Nuclear Information System (INIS)
Shibata, Keiichi; Hasegawa, Akira
1999-03-01
Covariances have been estimated for nuclear data contained in JENDL-3.2. As for Cr and Ni, the physical quantities for which covariances are deduced are cross sections and the first order Legendre-polynomial coefficient for the angular distribution of elastically scattered neutrons. The covariances were estimated by using the same methodology that had been used in the JENDL-3.2 evaluation in order to keep a consistency between mean values and their covariances. In a case where evaluated data were based on experimental data, the covariances were estimated from the same experimental data. For cross section that had been evaluated by nuclear model calculations, the same model was applied to generate the covariances. The covariances obtained were compiled into ENDF-6 format files. The covariances, which had been prepared by the previous fiscal year, were re-examined, and some improvements were performed. Parts of Fe and 235 U covariances were updated. Covariances of nu-p and nu-d for 241 Pu and of fission neutron spectra for 233,235,238 U and 239,240 Pu were newly added to data files. (author)
Managing distance and covariate information with point-based clustering
Directory of Open Access Journals (Sweden)
Peter A. Whigham
2016-09-01
Full Text Available Abstract Background Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures. An approach, based on Ripley’s K and applied to the problem of clustering with deliberate self-harm (DSH, is presented. Methods Point-based Monte-Carlo simulation of Ripley’s K, accounting for socio-economic deprivation and sources of distance measurement bias, was developed to estimate clustering of DSH at a range of spatial scales. A rotated Minkowski L1 distance metric allowed variation in physical distance and clustering to be assessed. Self-harm data was derived from an audit of 2 years’ emergency hospital presentations (n = 136 in a New Zealand town (population ~50,000. Study area was defined by residential (housing land parcels representing a finite set of possible point addresses. Results Area-based deprivation was spatially correlated. Accounting for deprivation and distance bias showed evidence for clustering of DSH for spatial scales up to 500 m with a one-sided 95 % CI, suggesting that social contagion may be present for this urban cohort. Conclusions Many problems involve finite locations in geographic space that require estimates of distance-based clustering at many scales. A Monte-Carlo approach to Ripley’s K, incorporating covariates and models for distance bias, are crucial when assessing health-related clustering. The case study showed that social network structure defined at the neighbourhood level may account for aspects of neighbourhood clustering of DSH. Accounting for
Data Fusion of Gridded Snow Products Enhanced with Terrain Covariates and a Simple Snow Model
Snauffer, A. M.; Hsieh, W. W.; Cannon, A. J.
2017-12-01
Hydrologic planning requires accurate estimates of regional snow water equivalent (SWE), particularly areas with hydrologic regimes dominated by spring melt. While numerous gridded data products provide such estimates, accurate representations are particularly challenging under conditions of mountainous terrain, heavy forest cover and large snow accumulations, contexts which in many ways define the province of British Columbia (BC), Canada. One promising avenue of improving SWE estimates is a data fusion approach which combines field observations with gridded SWE products and relevant covariates. A base artificial neural network (ANN) was constructed using three of the best performing gridded SWE products over BC (ERA-Interim/Land, MERRA and GLDAS-2) and simple location and time covariates. This base ANN was then enhanced to include terrain covariates (slope, aspect and Terrain Roughness Index, TRI) as well as a simple 1-layer energy balance snow model driven by gridded bias-corrected ANUSPLIN temperature and precipitation values. The ANN enhanced with all aforementioned covariates performed better than the base ANN, but most of the skill improvement was attributable to the snow model with very little contribution from the terrain covariates. The enhanced ANN improved station mean absolute error (MAE) by an average of 53% relative to the composing gridded products over the province. Interannual peak SWE correlation coefficient was found to be 0.78, an improvement of 0.05 to 0.18 over the composing products. This nonlinear approach outperformed a comparable multiple linear regression (MLR) model by 22% in MAE and 0.04 in interannual correlation. The enhanced ANN has also been shown to estimate better than the Variable Infiltration Capacity (VIC) hydrologic model calibrated and run for four BC watersheds, improving MAE by 22% and correlation by 0.05. The performance improvements of the enhanced ANN are statistically significant at the 5% level across the province and
Anomalous current from the covariant Wigner function
Prokhorov, George; Teryaev, Oleg
2018-04-01
We consider accelerated and rotating media of weakly interacting fermions in local thermodynamic equilibrium on the basis of kinetic approach. Kinetic properties of such media can be described by covariant Wigner function incorporating the relativistic distribution functions of particles with spin. We obtain the formulae for axial current by summation of the terms of all orders of thermal vorticity tensor, chemical potential, both for massive and massless particles. In the massless limit all the terms of fourth and higher orders of vorticity and third order of chemical potential and temperature equal zero. It is shown, that axial current gets a topological component along the 4-acceleration vector. The similarity between different approaches to baryon polarization is established.
Covariant entropy bound and loop quantum cosmology
International Nuclear Information System (INIS)
Ashtekar, Abhay; Wilson-Ewing, Edward
2008-01-01
We examine Bousso's covariant entropy bound conjecture in the context of radiation filled, spatially flat, Friedmann-Robertson-Walker models. The bound is violated near the big bang. However, the hope has been that quantum gravity effects would intervene and protect it. Loop quantum cosmology provides a near ideal setting for investigating this issue. For, on the one hand, quantum geometry effects resolve the singularity and, on the other hand, the wave function is sharply peaked at a quantum corrected but smooth geometry, which can supply the structure needed to test the bound. We find that the bound is respected. We suggest that the bound need not be an essential ingredient for a quantum gravity theory but may emerge from it under suitable circumstances.
Generation of phase-covariant quantum cloning
International Nuclear Information System (INIS)
Karimipour, V.; Rezakhani, A.T.
2002-01-01
It is known that in phase-covariant quantum cloning, the equatorial states on the Bloch sphere can be cloned with a fidelity higher than the optimal bound established for universal quantum cloning. We generalize this concept to include other states on the Bloch sphere with a definite z component of spin. It is shown that once we know the z component, we can always clone a state with a fidelity higher than the universal value and that of equatorial states. We also make a detailed study of the entanglement properties of the output copies and show that the equatorial states are the only states that give rise to a separable density matrix for the outputs
Covariant formulation of scalar-torsion gravity
Hohmann, Manuel; Järv, Laur; Ualikhanova, Ulbossyn
2018-05-01
We consider a generalized teleparallel theory of gravitation, where the action contains an arbitrary function of the torsion scalar and a scalar field, f (T ,ϕ ) , thus encompassing the cases of f (T ) gravity and a nonminimally coupled scalar field as subclasses. The action is manifestly Lorentz invariant when besides the tetrad one allows for a flat but nontrivial spin connection. We derive the field equations and demonstrate how the antisymmetric part of the tetrad equations is automatically satisfied when the spin connection equation holds. The spin connection equation is a vital part of the covariant formulation, since it determines the spin connection associated with a given tetrad. We discuss how the spin connection equation can be solved in general and provide the cosmological and spherically symmetric examples. Finally, we generalize the theory to an arbitrary number of scalar fields.
DEFF Research Database (Denmark)
2009-01-01
An adjustable microchip holder for holding a microchip is provided having a plurality of displaceable interconnection pads for connecting the connection holes of a microchip with one or more external devices or equipment. The adjustable microchip holder can fit different sizes of microchips...
Energy Technology Data Exchange (ETDEWEB)
Studnicki, M.; Mądry, W.; Noras, K.; Wójcik-Gront, E.; Gacek, E.
2016-11-01
The main objectives of multi-environmental trials (METs) are to assess cultivar adaptation patterns under different environmental conditions and to investigate genotype by environment (G×E) interactions. Linear mixed models (LMMs) with more complex variance-covariance structures have become recognized and widely used for analyzing METs data. Best practice in METs analysis is to carry out a comparison of competing models with different variance-covariance structures. Improperly chosen variance-covariance structures may lead to biased estimation of means resulting in incorrect conclusions. In this work we focused on adaptive response of cultivars on the environments modeled by the LMMs with different variance-covariance structures. We identified possible limitations of inference when using an inadequate variance-covariance structure. In the presented study we used the dataset on grain yield for 63 winter wheat cultivars, evaluated across 18 locations, during three growing seasons (2008/2009-2010/2011) from the Polish Post-registration Variety Testing System. For the evaluation of variance-covariance structures and the description of cultivars adaptation to environments, we calculated adjusted means for the combination of cultivar and location in models with different variance-covariance structures. We concluded that in order to fully describe cultivars adaptive patterns modelers should use the unrestricted variance-covariance structure. The restricted compound symmetry structure may interfere with proper interpretation of cultivars adaptive patterns. We found, that the factor-analytic structure is also a good tool to describe cultivars reaction on environments, and it can be successfully used in METs data after determining the optimal component number for each dataset. (Author)
Measuring and testing dependence by correlation of distances
Székely, Gábor J.; Rizzo, Maria L.; Bakirov, Nail K.
2007-01-01
Distance correlation is a new measure of dependence between random vectors. Distance covariance and distance correlation are analogous to product-moment covariance and correlation, but unlike the classical definition of correlation, distance correlation is zero only if the random vectors are independent. The empirical distance dependence measures are based on certain Euclidean distances between sample elements rather than sample moments, yet have a compact representation analogous to the clas...
Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates
DEFF Research Database (Denmark)
Han, Heejoon; Kristensen, Dennis
as captured by its long-memory parameter dx; in particular, we allow for both stationary and non-stationary covariates. We show that the QMLE'’s of the regression coefficients entering the volatility equation are consistent and normally distributed in large samples independently of the degree of persistence....... This implies that standard inferential tools, such as t-statistics, do not have to be adjusted to the level of persistence. On the other hand, the intercept in the volatility equation is not identifi…ed when the covariate is non-stationary which is akin to the results of Jensen and Rahbek (2004, Econometric...
Covariance structure in the skull of Catarrhini: a case of pattern stasis and magnitude evolution.
de Oliveira, Felipe Bandoni; Porto, Arthur; Marroig, Gabriel
2009-04-01
The study of the genetic variance/covariance matrix (G-matrix) is a recent and fruitful approach in evolutionary biology, providing a window of investigating for the evolution of complex characters. Although G-matrix studies were originally conducted for microevolutionary timescales, they could be extrapolated to macroevolution as long as the G-matrix remains relatively constant, or proportional, along the period of interest. A promising approach to investigating the constancy of G-matrices is to compare their phenotypic counterparts (P-matrices) in a large group of related species; if significant similarity is found among several taxa, it is very likely that the underlying G-matrices are also equivalent. Here we study the similarity of covariance and correlation structure in a broad sample of Old World monkeys and apes (Catarrhini). We made phylogenetically structured comparisons of correlation and covariance matrices derived from 39 skull traits, ranging from between species to the superfamily level. We also compared the overall magnitude of integration between skull traits (r2) for all Catarrhini genera. Our results show that P-matrices were not strictly constant among catarrhines, but the amount of divergence observed among taxa was generally low. There was significant and positive correlation between the amount of divergence in correlation and covariance patterns among the 30 genera and their phylogenetic distances derived from a recently proposed phylogenetic hypothesis. Our data demonstrate that the P-matrices remained relatively similar along the evolutionary history of catarrhines, and comparisons with the G-matrix available for a New World monkey genus (Saguinus) suggests that the same holds for all anthropoids. The magnitude of integration, in contrast, varied considerably among genera, indicating that evolution of the magnitude, rather than the pattern of inter-trait correlations, might have played an important role in the diversification of the
Selecting a separable parametric spatiotemporal covariance structure for longitudinal imaging data.
George, Brandon; Aban, Inmaculada
2015-01-15
Longitudinal imaging studies allow great insight into how the structure and function of a subject's internal anatomy changes over time. Unfortunately, the analysis of longitudinal imaging data is complicated by inherent spatial and temporal correlation: the temporal from the repeated measures and the spatial from the outcomes of interest being observed at multiple points in a patient's body. We propose the use of a linear model with a separable parametric spatiotemporal error structure for the analysis of repeated imaging data. The model makes use of spatial (exponential, spherical, and Matérn) and temporal (compound symmetric, autoregressive-1, Toeplitz, and unstructured) parametric correlation functions. A simulation study, inspired by a longitudinal cardiac imaging study on mitral regurgitation patients, compared different information criteria for selecting a particular separable parametric spatiotemporal correlation structure as well as the effects on types I and II error rates for inference on fixed effects when the specified model is incorrect. Information criteria were found to be highly accurate at choosing between separable parametric spatiotemporal correlation structures. Misspecification of the covariance structure was found to have the ability to inflate the type I error or have an overly conservative test size, which corresponded to decreased power. An example with clinical data is given illustrating how the covariance structure procedure can be performed in practice, as well as how covariance structure choice can change inferences about fixed effects. Copyright © 2014 John Wiley & Sons, Ltd.
Predicting deep percolation with eddy covariance under mulch drip irrigation
Ming, Guanghui; Tian, Fuqiang; Hu, Hongchang
2016-04-01
Water is essential for the agricultural development and ecological sustainability of the arid and semi-arid oasis with rare precipitation input and high evaporation demand. Deep percolation (DP) defined as excess irrigation water percolating below the plant root zone will reduce irrigation water use efficiency (WUE). But the DP was often ignored in mulch drip irrigation (MDI) which has reached the area of 1.6 million hectares in Xinjiang, the northwest of China. In this study DP experiments were conducted at an agricultural experiment station located within an irrigation district in the Tarim River Basin for four cotton growing periods. First it was detected the irrigation water infiltrated into the soil layers below 100cm and the groundwater level responded to the irrigation events well. Then DP below 100cm soil layers was calculated using the soil water balance method with the aid of eddy covariance (with the energy balance closure of 0.72). The negative DP (groundwater contribution to the crop-water use through capillary rising) at the seedling and harvesting stages can reach 77mm and has a good negative correlation with the groundwater level and positive correlation with potential evaporation. During the drip irrigation stage approximately 45% of the irrigation became DP and resulted in the low irrigation WUE of 0.6. The DP can be 164mm to 270mm per year which was positive linearly correlated to irrigation depth and negative linear correlated to irrigation interval. It is better to establish the irrigation schedule with small irrigation depth and given frequently to reduce deep percolation and meet crop needs.
Introduction to covariant formulation of superstring (field) theory
International Nuclear Information System (INIS)
Anon.
1987-01-01
The author discusses covariant formulation of superstring theories based on BRS invariance. New formulation of superstring was constructed by Green and Schwarz in the light-cone gauge first and then a covariant action was discovered. The covariant action has some interesting geometrical interpretation, however, covariant quantizations are difficult to perform because of existence of local supersymmetries. Introducing extra variables into the action, a modified action has been proposed. However, it would be difficult to prescribe constraints to define a physical subspace, or to reproduce the correct physical spectrum. Hence the old formulation, i.e., the Neveu-Schwarz-Ramond (NSR) model for covariant quantization is used. The author begins by quantizing the NSR model in a covariant way using BRS charges. Then the author discusses the field theory of (free) superstring
The method of covariant symbols in curved space-time
International Nuclear Information System (INIS)
Salcedo, L.L.
2007-01-01
Diagonal matrix elements of pseudodifferential operators are needed in order to compute effective Lagrangians and currents. For this purpose the method of symbols is often used, which however lacks manifest covariance. In this work the method of covariant symbols, introduced by Pletnev and Banin, is extended to curved space-time with arbitrary gauge and coordinate connections. For the Riemannian connection we compute the covariant symbols corresponding to external fields, the covariant derivative and the Laplacian, to fourth order in a covariant derivative expansion. This allows one to obtain the covariant symbol of general operators to the same order. The procedure is illustrated by computing the diagonal matrix element of a nontrivial operator to second order. Applications of the method are discussed. (orig.)
Physical properties of the Schur complement of local covariance matrices
International Nuclear Information System (INIS)
Haruna, L F; Oliveira, M C de
2007-01-01
General properties of global covariance matrices representing bipartite Gaussian states can be decomposed into properties of local covariance matrices and their Schur complements. We demonstrate that given a bipartite Gaussian state ρ 12 described by a 4 x 4 covariance matrix V, the Schur complement of a local covariance submatrix V 1 of it can be interpreted as a new covariance matrix representing a Gaussian operator of party 1 conditioned to local parity measurements on party 2. The connection with a partial parity measurement over a bipartite quantum state and the determination of the reduced Wigner function is given and an operational process of parity measurement is developed. Generalization of this procedure to an n-partite Gaussian state is given, and it is demonstrated that the n - 1 system state conditioned to a partial parity projection is given by a covariance matrix such that its 2 x 2 block elements are Schur complements of special local matrices
PUFF-IV, Code System to Generate Multigroup Covariance Matrices from ENDF/B-VI Uncertainty Files
International Nuclear Information System (INIS)
2007-01-01
1 - Description of program or function: The PUFF-IV code system processes ENDF/B-VI formatted nuclear cross section covariance data into multigroup covariance matrices. PUFF-IV is the newest release in this series of codes used to process ENDF uncertainty information and to generate the desired multi-group correlation matrix for the evaluation of interest. This version includes corrections and enhancements over previous versions. It is written in Fortran 90 and allows for a more modular design, thus facilitating future upgrades. PUFF-IV enhances support for resonance parameter covariance formats described in the ENDF standard and now handles almost all resonance parameter covariance information in the resolved region, with the exception of the long range covariance sub-subsections. PUFF-IV is normally used in conjunction with an AMPX master library containing group averaged cross section data. Two utility modules are included in this package to facilitate the data interface. The module SMILER allows one to use NJOY generated GENDF files containing group averaged cross section data in conjunction with PUFF-IV. The module COVCOMP allows one to compare two files written in COVERX format. 2 - Methods: Cross section and flux values on a 'super energy grid,' consisting of the union of the required energy group structure and the energy data points in the ENDF/B-V file, are interpolated from the input cross sections and fluxes. Covariance matrices are calculated for this grid and then collapsed to the required group structure. 3 - Restrictions on the complexity of the problem: PUFF-IV cannot process covariance information for energy and angular distributions of secondary particles. PUFF-IV does not process covariance information in Files 34 and 35; nor does it process covariance information in File 40. These new formats will be addressed in a future version of PUFF
Structural Covariance of Sensory Networks, the Cerebellum, and Amygdala in Autism Spectrum Disorder
Directory of Open Access Journals (Sweden)
Garrett J. Cardon
2017-11-01
Full Text Available Sensory dysfunction is a core symptom of autism spectrum disorder (ASD, and abnormalities with sensory responsivity and processing can be extremely debilitating to ASD patients and their families. However, relatively little is known about the underlying neuroanatomical and neurophysiological factors that lead to sensory abnormalities in ASD. Investigation into these aspects of ASD could lead to significant advancements in our general knowledge about ASD, as well as provide targets for treatment and inform diagnostic procedures. Thus, the current study aimed to measure the covariation of volumes of brain structures (i.e., structural magnetic resonance imaging that may be involved in abnormal sensory processing, in order to infer connectivity of these brain regions. Specifically, we quantified the structural covariation of sensory-related cerebral cortical structures, in addition to the cerebellum and amygdala by computing partial correlations between the structural volumes of these structures. These analyses were performed in participants with ASD (n = 36, as well as typically developing peers (n = 32. Results showed decreased structural covariation between sensory-related cortical structures, especially between the left and right cerebral hemispheres, in participants with ASD. In contrast, these same participants presented with increased structural covariation of structures in the right cerebral hemisphere. Additionally, sensory-related cerebral structures exhibited decreased structural covariation with functionally identified cerebellar networks. Also, the left amygdala showed significantly increased structural covariation with cerebral structures related to visual processing. Taken together, these results may suggest several patterns of altered connectivity both within and between cerebral cortices and other brain structures that may be related to sensory processing.
Huang, Jingfeng; Hsu, N. Christina; Tsay, Si-Chee; Zhang, Chidong; Jeong, Myeong Jae; Gautam, Ritesh; Bettenhausen, Corey; Sayer, Andrew M.; Hansell, Richard A.; Liu, Xiaohong;
2012-01-01
One of the seven scientific areas of interests of the 7-SEAS field campaign is to evaluate the impact of aerosol on cloud and precipitation (http://7-seas.gsfc.nasa.gov). However, large-scale covariability between aerosol, cloud and precipitation is complicated not only by ambient environment and a variety of aerosol effects, but also by effects from rain washout and climate factors. This study characterizes large-scale aerosol-cloud-precipitation covariability through synergy of long-term multi ]sensor satellite observations with model simulations over the 7-SEAS region [10S-30N, 95E-130E]. Results show that climate factors such as ENSO significantly modulate aerosol and precipitation over the region simultaneously. After removal of climate factor effects, aerosol and precipitation are significantly anti-correlated over the southern part of the region, where high aerosols loading is associated with overall reduced total precipitation with intensified rain rates and decreased rain frequency, decreased tropospheric latent heating, suppressed cloud top height and increased outgoing longwave radiation, enhanced clear-sky shortwave TOA flux but reduced all-sky shortwave TOA flux in deep convective regimes; but such covariability becomes less notable over the northern counterpart of the region where low ]level stratus are found. Using CO as a proxy of biomass burning aerosols to minimize the washout effect, large-scale covariability between CO and precipitation was also investigated and similar large-scale covariability observed. Model simulations with NCAR CAM5 were found to show similar effects to observations in the spatio-temporal patterns. Results from both observations and simulations are valuable for improving our understanding of this region's meteorological system and the roles of aerosol within it. Key words: aerosol; precipitation; large-scale covariability; aerosol effects; washout; climate factors; 7- SEAS; CO; CAM5
Structural Covariance of the Prefrontal-Amygdala Pathways Associated with Heart Rate Variability.
Wei, Luqing; Chen, Hong; Wu, Guo-Rong
2018-01-01
The neurovisceral integration model has shown a key role of the amygdala in neural circuits underlying heart rate variability (HRV) modulation, and suggested that reciprocal connections from amygdala to brain regions centered on the central autonomic network (CAN) are associated with HRV. To provide neuroanatomical evidence for these theoretical perspectives, the current study used covariance analysis of MRI-based gray matter volume (GMV) to map structural covariance network of the amygdala, and then determined whether the interregional structural correlations related to individual differences in HRV. The results showed that covariance patterns of the amygdala encompassed large portions of cortical (e.g., prefrontal, cingulate, and insula) and subcortical (e.g., striatum, hippocampus, and midbrain) regions, lending evidence from structural covariance analysis to the notion that the amygdala was a pivotal node in neural pathways for HRV modulation. Importantly, participants with higher resting HRV showed increased covariance of amygdala to dorsal medial prefrontal cortex and anterior cingulate cortex (dmPFC/dACC) extending into adjacent medial motor regions [i.e., pre-supplementary motor area (pre-SMA)/SMA], demonstrating structural covariance of the prefrontal-amygdala pathways implicated in HRV, and also implying that resting HRV may reflect the function of neural circuits underlying cognitive regulation of emotion as well as facilitation of adaptive behaviors to emotion. Our results, thus, provide anatomical substrates for the neurovisceral integration model that resting HRV may index an integrative neural network which effectively organizes emotional, cognitive, physiological and behavioral responses in the service of goal-directed behavior and adaptability.
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
2016-03-01
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. 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. 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. 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. 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 covariance contributes to fully characterizing brain
Fermionic covariant prolongation structure theory for supernonlinear evolution equation
International Nuclear Information System (INIS)
Cheng Jipeng; Wang Shikun; Wu Ke; Zhao Weizhong
2010-01-01
We investigate the superprincipal bundle and its associated superbundle. The super(nonlinear)connection on the superfiber bundle is constructed. Then by means of the connection theory, we establish the fermionic covariant prolongation structure theory of the supernonlinear evolution equation. In this geometry theory, the fermionic covariant fundamental equations determining the prolongation structure are presented. As an example, the supernonlinear Schroedinger equation is analyzed in the framework of this fermionic covariant prolongation structure theory. We obtain its Lax pairs and Baecklund transformation.
Bayesian hierarchical model for large-scale covariance matrix estimation.
Zhu, Dongxiao; Hero, Alfred O
2007-12-01
Many bioinformatics problems implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy due to "overfitting." We cast the large-scale covariance matrix estimation problem into the Bayesian hierarchical model framework, and introduce dependency between covariance parameters. We demonstrate the advantages of our approaches over the traditional approaches using simulations and OMICS data analysis.
Some remarks on general covariance of quantum theory
International Nuclear Information System (INIS)
Schmutzer, E.
1977-01-01
If one accepts Einstein's general principle of relativity (covariance principle) also for the sphere of microphysics (quantum, mechanics, quantum field theory, theory of elemtary particles), one has to ask how far the fundamental laws of traditional quantum physics fulfil this principle. Attention is here drawn to a series of papers that have appeared during the last years, in which the author criticized the usual scheme of quantum theory (Heisenberg picture, Schroedinger picture etc.) and presented a new foundation of the basic laws of quantum physics, obeying the 'principle of fundamental covariance' (Einstein's covariance principle in space-time and covariance principle in Hilbert space of quantum operators and states). (author)
Summary report of technical meeting on neutron cross section covariances
International Nuclear Information System (INIS)
Trkov, A.; Smith, D.L.; Capote Noy, R.
2011-01-01
A summary is given of the Technical Meeting on Neutron Cross Section Covariances. The meeting goal was to assess covariance data needs and recommend appropriate methodologies to address those needs. Discussions on covariance data focused on three general topics: 1) Resonance and unresolved resonance regions; 2) Fast neutron region; and 3) Users' perspective: benchmarks' uncertainty and reactor dosimetry. A number of recommendations for further work were generated and the important work that remains to be done in the field of covariances was identified. (author)
Formalism for neutron cross section covariances in the resonance region using kernel approximation
Energy Technology Data Exchange (ETDEWEB)
Oblozinsky, P.; Cho,Y-S.; Matoon,C.M.; Mughabghab,S.F.
2010-04-09
We describe analytical formalism for estimating neutron radiative capture and elastic scattering cross section covariances in the resolved resonance region. We use capture and scattering kernels as the starting point and show how to get average cross sections in broader energy bins, derive analytical expressions for cross section sensitivities, and deduce cross section covariances from the resonance parameter uncertainties in the recently published Atlas of Neutron Resonances. The formalism elucidates the role of resonance parameter correlations which become important if several strong resonances are located in one energy group. Importance of potential scattering uncertainty as well as correlation between potential scattering and resonance scattering is also examined. Practical application of the formalism is illustrated on {sup 55}Mn(n,{gamma}) and {sup 55}Mn(n,el).
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
ESTIMATION OF FUNCTIONALS OF SPARSE COVARIANCE MATRICES.
Fan, Jianqing; Rigollet, Philippe; Wang, Weichen
High-dimensional statistical tests often ignore correlations to gain simplicity and stability leading to null distributions that depend on functionals of correlation matrices such as their Frobenius norm and other ℓ r norms. Motivated by the computation of critical values of such tests, we investigate the difficulty of estimation the functionals of sparse correlation matrices. Specifically, we show that simple plug-in procedures based on thresholded estimators of correlation matrices are sparsity-adaptive and minimax optimal over a large class of correlation matrices. Akin to previous results on functional estimation, the minimax rates exhibit an elbow phenomenon. Our results are further illustrated in simulated data as well as an empirical study of data arising in financial econometrics.
Performance of penalized maximum likelihood in estimation of genetic covariances matrices
Directory of Open Access Journals (Sweden)
Meyer Karin
2011-11-01
Full Text Available Abstract Background Estimation of genetic covariance matrices for multivariate problems comprising more than a few traits is inherently problematic, since sampling variation increases dramatically with the number of traits. This paper investigates the efficacy of regularized estimation of covariance components in a maximum likelihood framework, imposing a penalty on the likelihood designed to reduce sampling variation. In particular, penalties that "borrow strength" from the phenotypic covariance matrix are considered. Methods An extensive simulation study was carried out to investigate the reduction in average 'loss', i.e. the deviation in estimated matrices from the population values, and the accompanying bias for a range of parameter values and sample sizes. A number of penalties are examined, penalizing either the canonical eigenvalues or the genetic covariance or correlation matrices. In addition, several strategies to determine the amount of penalization to be applied, i.e. to estimate the appropriate tuning factor, are explored. Results It is shown that substantial reductions in loss for estimates of genetic covariance can be achieved for small to moderate sample sizes. While no penalty performed best overall, penalizing the variance among the estimated canonical eigenvalues on the logarithmic scale or shrinking the genetic towards the phenotypic correlation matrix appeared most advantageous. Estimating the tuning factor using cross-validation resulted in a loss reduction 10 to 15% less than that obtained if population values were known. Applying a mild penalty, chosen so that the deviation in likelihood from the maximum was non-significant, performed as well if not better than cross-validation and can be recommended as a pragmatic strategy. Conclusions Penalized maximum likelihood estimation provides the means to 'make the most' of limited and precious data and facilitates more stable estimation for multi-dimensional analyses. It should
Parcellation of the human orbitofrontal cortex based on gray matter volume covariance.
Liu, Huaigui; Qin, Wen; Qi, Haotian; Jiang, Tianzi; Yu, Chunshui
2015-02-01
The human orbitofrontal cortex (OFC) is an enigmatic brain region that cannot be parcellated reliably using diffusional and functional magnetic resonance imaging (fMRI) because there is signal dropout that results from an inherent defect in imaging techniques. We hypothesise that the OFC can be reliably parcellated into subregions based on gray matter volume (GMV) covariance patterns that are derived from artefact-free structural images. A total of 321 healthy young subjects were examined by high-resolution structural MRI. The OFC was parcellated into subregions-based GMV covariance patterns; and then sex and laterality differences in GMV covariance pattern of each OFC subregion were compared. The human OFC was parcellated into the anterior (OFCa), medial (OFCm), posterior (OFCp), intermediate (OFCi), and lateral (OFCl) subregions. This parcellation scheme was validated by the same analyses of the left OFC and the bilateral OFCs in male and female subjects. Both visual observation and quantitative comparisons indicated a unique GMV covariance pattern for each OFC subregion. These OFC subregions mainly covaried with the prefrontal and temporal cortices, cingulate cortex and amygdala. In addition, GMV correlations of most OFC subregions were similar across sex and laterality except for significant laterality difference in the OFCl. The right OFCl had stronger GMV correlation with the right inferior frontal cortex. Using high-resolution structural images, we established a reliable parcellation scheme for the human OFC, which may provide an in vivo guide for subregion-level studies of this region and improve our understanding of the human OFC at subregional levels. © 2014 Wiley Periodicals, Inc.