Covariate-adjusted confidence interval for the intraclass correlation coefficient.
Shoukri, Mohamed M; Donner, Allan; El-Dali, Abdelmoneim
2013-09-01
A crucial step in designing a new study is to estimate the required sample size. For a design involving cluster sampling, the appropriate sample size depends on the so-called design effect, which is a function of the average cluster size and the intracluster correlation coefficient (ICC). It is well-known that under the framework of hierarchical and generalized linear models, a reduction in residual error may be achieved by including risk factors as covariates. In this paper we show that the covariate design, indicating whether the covariates are measured at the cluster level or at the within-cluster subject level affects the estimation of the ICC, and hence the design effect. Therefore, the distinction between these two types of covariates should be made at the design stage. In this paper we use the nested-bootstrap method to assess the accuracy of the estimated ICC for continuous and binary response variables under different covariate structures. The codes of two SAS macros are made available by the authors for interested readers to facilitate the construction of confidence intervals for the ICC. Moreover, using Monte Carlo simulations we evaluate the relative efficiency of the estimators and evaluate the accuracy of the coverage probabilities of a 95% confidence interval on the population ICC. The methodology is illustrated using a published data set of blood pressure measurements taken on family members.
A consistent local linear estimator of the covariate adjusted correlation coefficient.
Nguyen, Danh V; Sentürk, Damla
2009-08-01
Consider the correlation between two random variables (X, Y), both not directly observed. One only observes X̃ = φ(1)(U)X + φ(2)(U) and Ỹ = ψ(1)(U)Y + ψ(2)(U), where all four functions {φ(l)(·),ψ(l)(·), l = 1, 2} are unknown/unspecified smooth functions of an observable covariate U. We consider consistent estimation of the correlation between the unobserved variables X and Y, adjusted for the above general dual additive and multiplicative effects of U, based on the observed data (X̃, Ỹ, U).
Bayes linear covariance matrix adjustment
Wilkinson, Darren J
1995-01-01
In this thesis, a Bayes linear methodology for the adjustment of covariance matrices is presented and discussed. A geometric framework for quantifying uncertainties about covariance matrices is set up, and an inner-product for spaces of random matrices is motivated and constructed. The inner-product on this space captures aspects of our beliefs about the relationship between covariance matrices of interest to us, providing a structure rich enough for us to adjust beliefs about unknown matrices in the light of data such as sample covariance matrices, exploiting second-order exchangeability and related specifications to obtain representations allowing analysis. Adjustment is associated with orthogonal projection, and illustrated with examples of adjustments for some common problems. The problem of adjusting the covariance matrices underlying exchangeable random vectors is tackled and discussed. Learning about the covariance matrices associated with multivariate time series dynamic linear models is shown to be a...
Janes, Holly; Pepe, Margaret S
2009-06-01
Recent scientific and technological innovations have produced an abundance of potential markers that are being investigated for their use in disease screening and diagnosis. In evaluating these markers, it is often necessary to account for covariates associated with the marker of interest. Covariates may include subject characteristics, expertise of the test operator, test procedures or aspects of specimen handling. In this paper, we propose the covariate-adjusted receiver operating characteristic curve, a measure of covariate-adjusted classification accuracy. Nonparametric and semiparametric estimators are proposed, asymptotic distribution theory is provided and finite sample performance is investigated. For illustration we characterize the age-adjusted discriminatory accuracy of prostate-specific antigen as a biomarker for prostate cancer.
The covariate-adjusted frequency plot.
Holling, Heinz; Böhning, Walailuck; Böhning, Dankmar; Formann, Anton K
2016-04-01
Count data arise in numerous fields of interest. Analysis of these data frequently require distributional assumptions. Although the graphical display of a fitted model is straightforward in the univariate scenario, this becomes more complex if covariate information needs to be included into the model. Stratification is one way to proceed, but has its limitations if the covariate has many levels or the number of covariates is large. The article suggests a marginal method which works even in the case that all possible covariate combinations are different (i.e. no covariate combination occurs more than once). For each covariate combination the fitted model value is computed and then summed over the entire data set. The technique is quite general and works with all count distributional models as well as with all forms of covariate modelling. The article provides illustrations of the method for various situations and also shows that the proposed estimator as well as the empirical count frequency are consistent with respect to the same parameter.
On the Validity of Covariate Adjustment for Estimating Causal Effects
Shpitser, Ilya; Robins, James M
2012-01-01
Identifying effects of actions (treatments) on outcome variables from observational data and causal assumptions is a fundamental problem in causal inference. This identification is made difficult by the presence of confounders which can be related to both treatment and outcome variables. Confounders are often handled, both in theory and in practice, by adjusting for covariates, in other words considering outcomes conditioned on treatment and covariate values, weighed by probability of observing those covariate values. In this paper, we give a complete graphical criterion for covariate adjustment, which we term the adjustment criterion, and derive some interesting corollaries of the completeness of this criterion.
Bayes linear covariance matrix adjustment for multivariate dynamic linear models
Wilkinson, Darren J
2008-01-01
A methodology is developed for the adjustment of the covariance matrices underlying a multivariate constant time series dynamic linear model. The covariance matrices are embedded in a distribution-free inner-product space of matrix objects which facilitates such adjustment. This approach helps to make the analysis simple, tractable and robust. To illustrate the methods, a simple model is developed for a time series representing sales of certain brands of a product from a cash-and-carry depot. The covariance structure underlying the model is revised, and the benefits of this revision on first order inferences are then examined.
Covariate-adjusted measures of discrimination for survival data
DEFF Research Database (Denmark)
White, Ian R; Rapsomaniki, Eleni; Frikke-Schmidt, Ruth
2015-01-01
MOTIVATION: Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled...... by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination...
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 cova......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......), then for a deprivation index, and finally for both PM10 and deprivation. Spatial patterns of risk, disease clusters and cold and hot spots were generated using a spatial scan statistic and a Getis-Ord Gi* statistic. In all disease groups tested (except the control disease), adjustment for chronic PM10 exposure...... area to a mixed residential/industrial area, possibly introducing new environmental exposures. Researchers should be aware of the potential spatial effects inherent in adjusting for covariates when considering study design and interpreting results. © 2007 Elsevier Ltd. All rights reserved....
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.
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....
Bayesian adjustment for covariate measurement errors: a flexible parametric approach.
Hossain, Shahadut; Gustafson, Paul
2009-05-15
In most epidemiological investigations, the study units are people, the outcome variable (or the response) is a health-related event, and the explanatory variables are usually environmental and/or socio-demographic factors. The fundamental task in such investigations is to quantify the association between the explanatory variables (covariates/exposures) and the outcome variable through a suitable regression model. The accuracy of such quantification depends on how precisely the relevant covariates are measured. In many instances, we cannot measure some of the covariates accurately. Rather, we can measure noisy (mismeasured) versions of them. In statistical terminology, mismeasurement in continuous covariates is known as measurement errors or errors-in-variables. Regression analyses based on mismeasured covariates lead to biased inference about the true underlying response-covariate associations. In this paper, we suggest a flexible parametric approach for avoiding this bias when estimating the response-covariate relationship through a logistic regression model. More specifically, we consider the flexible generalized skew-normal and the flexible generalized skew-t distributions for modeling the unobserved true exposure. For inference and computational purposes, we use Bayesian Markov chain Monte Carlo techniques. We investigate the performance of the proposed flexible parametric approach in comparison with a common flexible parametric approach through extensive simulation studies. We also compare the proposed method with the competing flexible parametric method on a real-life data set. Though emphasis is put on the logistic regression model, the proposed method is unified and is applicable to the other generalized linear models, and to other types of non-linear regression models as well. (c) 2009 John Wiley & Sons, Ltd.
A new family of covariate-adjusted response adaptive designs and their properties
Institute of Scientific and Technical Information of China (English)
ZHANG Li-Xin; HU Fei-fang
2009-01-01
It is often important to incorporate covariate information in the design of clinical trials. In literature there are many designs of using stratification and covariate-adaptive randomization to balance certain known covaxiate. Recently, some covariate-adjusted response-adaptive (CARA) designs have been proposed and their asymptotic properties have been studied (Ann.Statist. 2007). However, these CARA designs usually have high variabilities. In this paper, a new family of covariate-adjusted response-adaptive (CARA) designs is presented. It is shown that the new designs have less variables and therefore are more efficient.
Trouble shooting for covariance fitting in highly correlated data
Yoon, Boram; Lee, Weonjong; Jung, Chulwoo
2011-01-01
We report a possible solution to the trouble that the covariance fitting fails when the data is highly correlated and the covariance matrix has small eigenvalues. As an example, we choose the data analysis of highly correlated $B_K$ data on the basis of the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have an accurate fitting function so that we cannot fit the highly correlated and precise data. When some eigenvalues of the covariance matrix are small, even a tiny error of fitting function can produce large chi-square and spoil the fitting procedure. We have applied a number of prescriptions available in the market such as diagonal approximation and cutoff method. In addition, we present a new method, the eigenmode shift method which fine-tunes the fitting function while keeping the covariance matrix untouched.
Covariate-adjusted measures of discrimination for survival data
White, Ian R.; Rapsomaniki, Eleni; Wannamethee, S. G.; Morris, R. W.; Willeit, J.; Willeit, P.; Santer, P.; Kiechl, S.; Wald, N.; Ebrahim, S.; Lawlor, D. A.; Gallacher, J.; Yarnell, J. W G; Ben-Shlomo, Y.; Casiglia, E.; Tikhonoff, V.; Sutherland, S. E.; Nietert, P. J.; Keil, J. E.; Bachman, D. L.; Psaty, B. M.; Cushman, M.; Nordestgaard, B. G.; Tybjærg-Hansen, A.; Frikke-Schmidt, R.; Giampaoli, S.; Palmieri, L.; Panico, S.; Pilotto, L.; Vanuzzo, D.; Simons, L. A.; Friedlander, Y.; McCallum, J.; Price, J. F.; McLachlan, S.; Taylor, J. O.; Guralnik, J. M.; Wallace, R. B.; Kohout, F. J.; Cornoni-Huntley, J. C.; Guralnik, J. M.; Blazer, D. G.; Guralnik, J. M.; Phillips, C. L.; Phillips, C. L.; Guralnik, J. M.; Wareham, N. J.; Khaw, K. T.; Brenner, H.; Schöttker, B.; Müller, H. T.; Rothenbacher, D.; Nissinen, A.; Donfrancesco, C.; Giampaoli, S.; Harald, K.; Jousilahti, P. R.; Vartiainen, E.; Salomaa, V.; D'Agostino, R. B.; Wolf, P. A.; Vasan, R. S.; Daimon, M.; Oizumi, T.; Kayama, T.; Kato, T.; Chetrit, A.; Dankner, R.; Lubin, F.; Welin, L.; Svärdsudd, K.; Eriksson, H.; Lappas, G.; Lissner, L.; Mehlig, K.; Björkelund, C.; Nagel, D.; Kiyohara, Y.; Arima, H.; Ninomiya, T.; Hata, J.; Rodriguez, B.; Dekker, J. M.; Nijpels, G.; Stehouwer, C. D A; Iso, H.; Kitamura, A.; Yamagishi, K.; Noda, H.; Goldbourt, U.; Kauhanen, J.; Salonen, J. T.; Tuomainen, T. P.; Meade, T. W.; DeStavola, B. L.; Blokstra, A.; Verschuren, W. M M; Cushman, M.; de Boer, I. H.; Folsom, A. R.; Psaty, B. M.; Koenig, W.; Meisinger, C.; Peters, A.; Verschuren, W. M M; Bueno-de-Mesquita, H. B.; Blokstra, A.; Rosengren, A.; Wilhelmsen, L.; Lappas, G.; Kuller, L. H.; Grandits, G.; Cooper, J. A.; Bauer, K. A.; Davidson, K. W.; Kirkland, S.; Shaffer, J. A.; Shimbo, D.; Kitamura, A.; Iso, H.; Sato, S.; Dullaart, R. P F; Bakker, S. J L; Gansevoort, R. T.; Ducimetiere, P.; Amouyel, P.; Arveiler, D.; Evans, A.; Ferrières, J.; Schulte, H.; Assmann, G.; Jukema, J. W.; Westendorp, R. G J; Sattar, N.; Cantin, B.; Lamarche, B.; Després, J. P.; Wingard, D. L.; Daniels, L. B.; Gudnason, V.; Aspelund, T.; Trevisan, M.; Hofman, A.; Franco, O. H.; Tunstall-Pedoe, H.; Tavendale, R.; Lowe, G. D O; Woodward, M.; Howard, W. J.; Howard, B. V.; Zhang, Y.; Best, L. G.; Umans, J.; Ben-Shlomo, Y.; Davey-Smith, G.; Onat, A.; Nakagawa, H.; Sakurai, M.; Nakamura, K.; Morikawa, Y.; Njølstad, I.; Mathiesen, E. B.; Wilsgaard, T.; Sundström, J.; Gaziano, J. M.; Ridker, P. M.; Marmot, M.; Clarke, R.; Collins, R.; Fletcher, A.; Brunner, E.; Shipley, M.; Kivimaki, M.; Ridker, P. M.; Buring, J.; Rifai, N.; Cook, N.; Ford, I.; Robertson, M.; Marín Ibañez, A.; Feskens, E. J M; Geleijnse, J. M.
2015-01-01
Motivation: Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the
Covariate-adjusted measures of discrimination for survival data
White, Ian R.; Rapsomaniki, Eleni; Wannamethee, S. G.; Morris, R. W.; Willeit, J.; Willeit, P.; Santer, P.; Kiechl, S.; Wald, N.; Ebrahim, S.; Lawlor, D. A.; Gallacher, J.; Yarnell, J. W G; Ben-Shlomo, Y.; Casiglia, E.; Tikhonoff, V.; Sutherland, S. E.; Nietert, P. J.; Keil, J. E.; Bachman, D. L.; Psaty, B. M.; Cushman, M.; Nordestgaard, B. G.; Tybjærg-Hansen, A.; Frikke-Schmidt, R.; Giampaoli, S.; Palmieri, L.; Panico, S.; Pilotto, L.; Vanuzzo, D.; Simons, L. A.; Friedlander, Y.; McCallum, J.; Price, J. F.; McLachlan, S.; Taylor, J. O.; Guralnik, J. M.; Wallace, R. B.; Kohout, F. J.; Cornoni-Huntley, J. C.; Guralnik, J. M.; Blazer, D. G.; Guralnik, J. M.; Phillips, C. L.; Phillips, C. L.; Guralnik, J. M.; Wareham, N. J.; Khaw, K. T.; Brenner, H.; Schöttker, B.; Müller, H. T.; Rothenbacher, D.; Nissinen, A.; Donfrancesco, C.; Giampaoli, S.; Harald, K.; Jousilahti, P. R.; Vartiainen, E.; Salomaa, V.; D'Agostino, R. B.; Wolf, P. A.; Vasan, R. S.; Daimon, M.; Oizumi, T.; Kayama, T.; Kato, T.; Chetrit, A.; Dankner, R.; Lubin, F.; Welin, L.; Svärdsudd, K.; Eriksson, H.; Lappas, G.; Lissner, L.; Mehlig, K.; Björkelund, C.; Nagel, D.; Kiyohara, Y.; Arima, H.; Ninomiya, T.; Hata, J.; Rodriguez, B.; Dekker, J. M.; Nijpels, G.; Stehouwer, C. D A; Iso, H.; Kitamura, A.; Yamagishi, K.; Noda, H.; Goldbourt, U.; Kauhanen, J.; Salonen, J. T.; Tuomainen, T. P.; Meade, T. W.; DeStavola, B. L.; Blokstra, A.; Verschuren, W. M M; Cushman, M.; de Boer, I. H.; Folsom, A. R.; Psaty, B. M.; Koenig, W.; Meisinger, C.; Peters, A.; Verschuren, W. M M; Bueno-de-Mesquita, H. B.; Blokstra, A.; Rosengren, A.; Wilhelmsen, L.; Lappas, G.; Kuller, L. H.; Grandits, G.; Cooper, J. A.; Bauer, K. A.; Davidson, K. W.; Kirkland, S.; Shaffer, J. A.; Shimbo, D.; Kitamura, A.; Iso, H.; Sato, S.; Dullaart, R. P F; Bakker, S. J L; Gansevoort, R. T.; Ducimetiere, P.; Amouyel, P.; Arveiler, D.; Evans, A.; Ferrières, J.; Schulte, H.; Assmann, G.; Jukema, J. W.; Westendorp, R. G J; Sattar, N.; Cantin, B.; Lamarche, B.; Després, J. P.; Wingard, D. L.; Daniels, L. B.; Gudnason, V.; Aspelund, T.; Trevisan, M.; Hofman, A.; Franco, O. H.; Tunstall-Pedoe, H.; Tavendale, R.; Lowe, G. D O; Woodward, M.; Howard, W. J.; Howard, B. V.; Zhang, Y.; Best, L. G.; Umans, J.; Ben-Shlomo, Y.; Davey-Smith, G.; Onat, A.; Nakagawa, H.; Sakurai, M.; Nakamura, K.; Morikawa, Y.; Njølstad, I.; Mathiesen, E. B.; Wilsgaard, T.; Sundström, J.; Gaziano, J. M.; Ridker, P. M.; Marmot, M.; Clarke, R.; Collins, R.; Fletcher, A.; Brunner, E.; Shipley, M.; Kivimaki, M.; Ridker, P. M.; Buring, J.; Rifai, N.; Cook, N.; Ford, I.; Robertson, M.; Marín Ibañez, A.; Feskens, E. J M; Geleijnse, J. M.
2015-01-01
Motivation: Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the
Covariance fitting of highly correlated $B_K$ data
Yoon, Boram; Jung, Chulwoo; Lee, Weonjong
2011-01-01
We present the reason why we use the diagonal approximation (uncorrelated fitting) when we perform the data analysis of highly correlated $B_K$ data on the basis of the SU(2) staggered chiral perturbation theory. Basically, the essence of the problem is that we do not have enough statistics to determine the small eigenvalues of the covariance matrix with a high precision. As a result, we have the smallest eigenvalue, which is smaller than the statistical error of the covariance matrix, corresponding to an unphysical eigenmode. We have applied a number of prescriptions available in the market such as the cutoff method and modified covariance matrix method. It turns out that the cutoff method is not a good prescription and the modified covariance matrix method is an even worse one. The diagonal approximation turns out to be a good prescription if the data points are somehow correlated and the statistics are relatively poor.
Daniel Bartz; Kerr Hatrick; Hesse, Christian W.; Klaus-Robert M\\"uller; Steven Lemm
2011-01-01
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, w...
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…
Safarkhani, Maryam; Moerbeek, Mirjam
2013-01-01
In a randomized controlled trial, a decision needs to be made about the total number of subjects for adequate statistical power. One way to increase the power of a trial is by including a predictive covariate in the model. In this article, the effects of various covariate adjustment strategies on increasing the power is studied for discrete-time…
Directory of Open Access Journals (Sweden)
Emre DEMIR
2016-10-01
Full Text Available Objective: Markers which are used for classification into two groups, such as patient / healthy, benign/malignant or prediction of optimal cut off value for diagnostic test and evaluating the performance of diagnostic tests is evaluated by Receiver Operating Characteristic (ROC curve in the diagnostic test researches. In classification accuracy research, some variables such as gender and age, commonly is not similar in groups. In these cases, covariates should be considered to estimate in the area under ROC and covariate adjustment for ROC should be performed. This study aims to introduce methods in the literature for the effect of covariate adjustment and to present an application with sample from the health field. Material and Methods: In the study, we introduced methods used in the literatüre for covariate adjustment and prediction of the area under ROC curves as well as an application with data from the field of urology. In this study, 105 PSA (prostate specific antigen measurements were taken in order to examine the covariate effect for the age variable and to assess the diagnostic performance of PSA measurements with regard to pathologic methods. Results: Covariate effect were found statistically significant with 0.733 parameter estimation of the age in ROC curves analysis with PSA data (p<0.001. According to the methods (Non-parametric (empirical, non-parametric (normal, semi-parametric (empirical, parametric (normal that estimates of the area under ROC curves which is obtained without covariate effect were found 0.708, 0.629, 0.709 and 0.628, respectively, by using PSA measurements. Area under the curve that obtained by covariate adjustment were significantly lower as compared to the traditional ROC with estimation 0.580, 0.577, 0.582 and 0.579. Conclusion: Area under the ROC curves should be estimated with adjustment according to the covariates that could affect the markers value of diagnostic tests performed in concert with matching
DEFF Research Database (Denmark)
Vansteelandt, S.; Martinussen, Torben; Tchetgen, E. J Tchetgen
2014-01-01
'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......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...
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.
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...... of the problem at hand. We develop a theory for the point process of the normalized eigenvalues of the sample covariance matrix in the case where rows and columns of the data are linearly dependent. Based on the weak convergence of this point process we derive the limit laws of various functionals...... of the eigenvalues. In the second part, we show that the largest and smallest eigenvalues of a highdimensional sample correlation matrix possess almost sure non-random limits if the truncated variance of the entry distribution is “almost slowly varying”, a condition we describe via moment properties of self...
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.
Elze, Markus C; Gregson, John; Baber, Usman; Williamson, Elizabeth; Sartori, Samantha; Mehran, Roxana; Nichols, Melissa; Stone, Gregg W; Pocock, Stuart J
2017-01-24
Propensity scores (PS) are an increasingly popular method to adjust for confounding in observational studies. Propensity score methods have theoretical advantages over conventional covariate adjustment, but their relative performance in real-word scenarios is poorly characterized. We used datasets from 4 large-scale cardiovascular observational studies (PROMETHEUS, ADAPT-DES [the Assessment of Dual AntiPlatelet Therapy with Drug-Eluting Stents], THIN [The Health Improvement Network], and CHARM [Candesartan in Heart Failure-Assessment of Reduction in Mortality and Morbidity]) to compare the performance of conventional covariate adjustment with 4 common PS methods: matching, stratification, inverse probability weighting, and use of PS as a covariate. We found that stratification performed poorly with few outcome events, and inverse probability weighting gave imprecise estimates of treatment effect and undue influence to a small number of observations when substantial confounding was present. Covariate adjustment and matching performed well in all of our examples, although matching tended to give less precise estimates in some cases. PS methods are not necessarily superior to conventional covariate adjustment, and care should be taken to select the most suitable method. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.
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.
Least-Squares Data Adjustment with Rank-Deficient Data Covariance Matrices
Energy Technology Data Exchange (ETDEWEB)
Williams, J.G. [The University of Arizona, Tucson, AZ 85721-0119 (United States)
2011-07-01
A derivation of the linear least-squares adjustment formulae is required that avoids the assumption that the covariance matrix of prior parameters can be inverted. Possible proofs are of several kinds, including: (i) extension of standard results for the linear regression formulae, and (ii) minimization by differentiation of a quadratic form of the deviations in parameters and responses. In this paper, the least-squares adjustment equations are derived in both these ways, while explicitly assuming that the covariance matrix of prior parameters is singular. It will be proved that the solutions are unique and that, contrary to statements that have appeared in the literature, the least-squares adjustment problem is not ill-posed. No modification is required to the adjustment formulae that have been used in the past in the case of a singular covariance matrix for the priors. In conclusion: The linear least-squares adjustment formula that has been used in the past is valid in the case of a singular covariance matrix for the covariance matrix of prior parameters. Furthermore, it provides a unique solution. Statements in the literature, to the effect that the problem is ill-posed are wrong. No regularization of the problem is required. This has been proved in the present paper by two methods, while explicitly assuming that the covariance matrix of prior parameters is singular: i) extension of standard results for the linear regression formulae, and (ii) minimization by differentiation of a quadratic form of the deviations in parameters and responses. No modification is needed to the adjustment formulae that have been used in the past. (author)
Two new covariate adjustment methods for non-inferiority assessment of binary clinical trials data.
Hou, Yan; Ding, Victoria; Li, Kang; Zhou, Xiao-Hua
2011-01-01
In clinical trials, examining the adjusted treatment difference has become the preferred way to establish non-inferiority (NI) in cases involving a binary endpoint. However, current methods are inadequate in the area of covariate adjustment. In this paper, we introduce two new methods, nonparametric and parametric, of using the probability and probability (P-P) curve to address the issue of unadjusted categorical covariates in the traditional assessment of NI in clinical trials. We also show that the area under the P-P curve is a valid alternative for assessing NI using the adjusted treatment difference, and we compute this area using Mann-Whitney nonparametric statistics. Our simulation studies demonstrate that our proposed methods can not only control type I error at a predefined significance level but also achieve higher statistical power than those of traditional parametric and nonparametric methods that overlook covariate adjustment, especially when covariates are unbalanced in the two treatment groups. We illustrate the effectiveness of our methodology with data from clinical trials of a therapy for coronary heart disease.
Spike Triggered Covariance in Strongly Correlated Gaussian Stimuli
Aljadeff, Johnatan; Segev, Ronen; Berry, Michael J.; Sharpee, Tatyana O.
2013-01-01
Many biological systems perform computations on inputs that have very large dimensionality. Determining the relevant input combinations for a particular computation is often key to understanding its function. A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs. In systems neuroscience, the corresponding method is known as spike-triggered covariance (STC). This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems. So far, most studies used the STC method with weakly correlated Gaussian inputs. However, it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment. In such cases, the stimulus covariance matrix has one (or more) outstanding eigenvalues that cannot be easily equalized because of sampling variability. Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs. In many cases, these modes obscure the significant dimensions. We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more. This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode(s). Analyzing the responses of retinal ganglion cells probed with Gaussian noise, we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons. PMID:24039563
Spike triggered covariance in strongly correlated gaussian stimuli.
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Johnatan Aljadeff
Full Text Available Many biological systems perform computations on inputs that have very large dimensionality. Determining the relevant input combinations for a particular computation is often key to understanding its function. A common way to find the relevant input dimensions is to examine the difference in variance between the input distribution and the distribution of inputs associated with certain outputs. In systems neuroscience, the corresponding method is known as spike-triggered covariance (STC. This method has been highly successful in characterizing relevant input dimensions for neurons in a variety of sensory systems. So far, most studies used the STC method with weakly correlated Gaussian inputs. However, it is also important to use this method with inputs that have long range correlations typical of the natural sensory environment. In such cases, the stimulus covariance matrix has one (or more outstanding eigenvalues that cannot be easily equalized because of sampling variability. Such outstanding modes interfere with analyses of statistical significance of candidate input dimensions that modulate neuronal outputs. In many cases, these modes obscure the significant dimensions. We show that the sensitivity of the STC method in the regime of strongly correlated inputs can be improved by an order of magnitude or more. This can be done by evaluating the significance of dimensions in the subspace orthogonal to the outstanding mode(s. Analyzing the responses of retinal ganglion cells probed with [Formula: see text] Gaussian noise, we find that taking into account outstanding modes is crucial for recovering relevant input dimensions for these neurons.
Alton, Gillian D; Pearl, David L.; Bateman, Ken G.; McNab, Bruce; Berke, Olaf
2013-01-01
Background Abattoir condemnation data show promise as a rich source of data for syndromic surveillance of both animal and zoonotic diseases. However, inherent characteristics of abattoir condemnation data can bias results from space-time cluster detection methods for disease surveillance, and may need to be accounted for using various adjustment methods. The objective of this study was to compare the space-time scan statistics with different abilities to control for covariates and to assess t...
Spatial and temporal patterns of enzootic raccoon rabies adjusted for multiple covariates
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Kulldorff Martin
2007-04-01
Full Text Available Abstract Background With the objective of identifying spatial and temporal patterns of enzootic raccoon variant rabies, a spatial scan statistic was utilized to search for significant terrestrial rabies clusters by year in New York State in 1997–2003. Cluster analyses were unadjusted for other factors, adjusted for covariates, and adjusted for covariates and large scale geographic variation (LSGV. Adjustments were intended to identify the unusual aggregations of cases given the expected distribution based on the observed locations. Results Statistically significant clusters were identified particularly in the Albany, Finger Lakes, and South Hudson areas. The clusters were generally persistent in the Albany area, but demonstrated cyclical changes in rabies activity every few years in the other areas. Cluster adjustments allowed the discussion of possible causes for the high risk raccoon rabies areas identified. Conclusion This study analyzed raccoon variant rabies spatial and temporal patterns in New York that have not been previously described at a focal (census tract level. Comparisons across the type of spatial analysis performed with various degrees of adjustment allow consideration of the potential influence of geographical factors for raccoon rabies and possible reasons for the highest risk areas (statistically significant clusters.
DEFF Research Database (Denmark)
He, Peng; Eriksson, Frank; Scheike, Thomas H.
2016-01-01
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 cov......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...... 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...
A covariate-adjustment regression model approach to noninferiority margin definition.
Nie, Lei; Soon, Guoxing
2010-05-10
To maintain the interpretability of the effect of experimental treatment (EXP) obtained from a noninferiority trial, current statistical approaches often require the constancy assumption. This assumption typically requires that the control treatment effect in the population of the active control trial is the same as its effect presented in the population of the historical trial. To prevent constancy assumption violation, clinical trial sponsors were recommended to make sure that the design of the active control trial is as close to the design of the historical trial as possible. However, these rigorous requirements are rarely fulfilled in practice. The inevitable discrepancies between the historical trial and the active control trial have led to debates on many controversial issues. Without support from a well-developed quantitative method to determine the impact of the discrepancies on the constancy assumption violation, a correct judgment seems difficult. In this paper, we present a covariate-adjustment generalized linear regression model approach to achieve two goals: (1) to quantify the impact of population difference between the historical trial and the active control trial on the degree of constancy assumption violation and (2) to redefine the active control treatment effect in the active control trial population if the quantification suggests an unacceptable violation. Through achieving goal (1), we examine whether or not a population difference leads to an unacceptable violation. Through achieving goal (2), we redefine the noninferiority margin if the violation is unacceptable. This approach allows us to correctly determine the effect of EXP in the noninferiority trial population when constancy assumption is violated due to the population difference. We illustrate the covariate-adjustment approach through a case study.
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
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.
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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.
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...... and covariance, for which we obtain the optimal rate of convergence. We demonstrate some positive semidefinite estimators of the covariation and construct a positive semidefinite estimator of the conditional covariance matrix in the central limit theorem. Furthermore, we indicate how the assumptions on the noise...
DEFF Research Database (Denmark)
Kinnebrock, Silja; Podolskij, Mark
and covariance, for which we obtain the optimal rate of convergence. We demonstrate some positive semidefinite estimators of the covariation and construct a positive semidefinite estimator of the conditional covariance matrix in the central limit theorem. Furthermore, we indicate how the assumptions on the noise......This paper introduces a new estimator to measure the ex-post covariation between high-frequency financial time series under market microstructure noise. We provide an asymptotic limit theory (including feasible central limit theorems) for standard methods such as regression, correlation analysis...
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…
Hussey, Michael A; Koch, Gary G; Preisser, John S; Saville, Benjamin R
2016-01-01
Time-to-event or dichotomous outcomes in randomized clinical trials often have analyses using the Cox proportional hazards model or conditional logistic regression, respectively, to obtain covariate-adjusted log hazard (or odds) ratios. Nonparametric Randomization-Based Analysis of Covariance (NPANCOVA) can be applied to unadjusted log hazard (or odds) ratios estimated from a model containing treatment as the only explanatory variable. These adjusted estimates are stratified population-averaged treatment effects and only require a valid randomization to the two treatment groups and avoid key modeling assumptions (e.g., proportional hazards in the case of a Cox model) for the adjustment variables. The methodology has application in the regulatory environment where such assumptions cannot be verified a priori. Application of the methodology is illustrated through three examples on real data from two randomized trials.
Reinterpreting illusory correlation : From biased covariation to meaningful categorisation
Berndsen, M; Spears, R
1997-01-01
The illusory correlation effect has traditionally been conceived as an irrational information processing bias arising form the greater attention or weight accorded to infrequent and thus distinction co-occurrences (Hamilton & Gifford, 1976). Alternative explanations for this effect are considered
Peters, Elisabeth; Stuke, Maik
2016-01-01
In this manuscript we study the modeling of experimental data and its impact on the resulting integral experimental covariance and correlation matrices. By investigating a set of three low enriched and water moderated UO2 fuel rod arrays we found that modeling the same set of data with different, yet reasonable assumptions concerning the fuel rod composition and its geometric properties leads to significantly different covariance matrices or correlation coefficients. Following a Monte Carlo sampling approach, we show for nine different modeling assumptions the corresponding correlation coefficients and sensitivity profiles for each pair of the effective neutron multiplication factor keff. Within the 95% confidence interval the correlation coefficients vary from 0 to 1, depending on the modeling assumptions. Our findings show that the choice of modeling can have a huge impact on integral experimental covariance matrices. When the latter are used in a validation procedure to derive a bias, this procedure can be...
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.
A covariate adjusted two-stage allocation design for binary responses in randomized clinical trials.
Bandyopadhyay, Uttam; Biswas, Atanu; Bhattacharya, Rahul
2007-10-30
In the present work, we develop a two-stage allocation rule for binary response using the log-odds ratio within the Bayesian framework allowing the current allocation to depend on the covariate value of the current subject. We study, both numerically and theoretically, several exact and limiting properties of this design. The applicability of the proposed methodology is illustrated by using some data set. We compare this rule with some of the existing rules by computing various performance measures.
Schur complement inequalities for covariance matrices and monogamy of quantum correlations
Lami, Ludovico; Adesso, Gerardo; Winter, Andreas
2016-01-01
We derive fundamental constraints for the Schur complement of positive matrices, which provide an operator strengthening to recently established information inequalities for quantum covariance matrices, including strong subadditivity. This allows us to prove general results on the monogamy of entanglement and steering quantifiers in continuous variable systems with an arbitrary number of modes per party. A powerful hierarchical relation for correlation measures based on the log-determinant of covariance matrices is further established for all Gaussian states, which has no counterpart among quantities based on the conventional von Neumann entropy.
Nicholas, Katherine; Yeatts, Sharon D; Zhao, Wenle; Ciolino, Jody; Borg, Keith; Durkalski, Valerie
2015-01-01
SUMMARY The question of when to adjust for important prognostic covariates often arises in the design of clinical trials, and there remain various opinions on whether to adjust during both randomization and analysis, at randomization alone, or at analysis alone. Furthermore, little is known about the impact of covariate adjustment in the context of non-inferiority (NI) designs. The current simulation-based research explores this issue in the NI setting, as compared to the typical superiority setting, by assessing the differential impact on power, type I error, and bias in the treatment estimate as well as its standard error, in the context of logistic regression under both simple and covariate adjusted permuted block randomization algorithms. In both the superiority and NI settings, failure to adjust for covariates that influence outcome in the analysis phase, regardless of prior adjustment at randomization, results in treatment estimates that are biased toward zero, with standard errors that are deflated. However, as no treatment difference is approached under the null hypothesis in superiority and under the alternative in NI, this results in decreased power and nominal or conservative (deflated) type I error in the context of superiority, but inflated power and type I error under NI. Results from the simulation study suggest that, regardless of the use of the covariate in randomization, it is appropriate to adjust for important prognostic covariates in analysis, as this yields nearly unbiased estimates of treatment as well as nominal type I error. PMID:25641057
Sensitivity of adjustment to parameter correlations and to response-parameter correlations
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Wagschal, J.J. [Racah Inst. of Physics, Hebrew Univ. of Jerusalem, Edmond J. Safra Campus, Jerusalem, 91904 (Israel)
2011-07-01
The adjusted parameters and response, and their respective posterior uncertainties and correlations, are presented explicitly as functions of all relevant prior correlations for the two parameters, one response case. The dependence of these adjusted entities on the various prior correlations is analyzed and portrayed graphically for various valid correlation combinations on a simple criticality problem. (authors)
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C Elizabeth McCarron
Full Text Available BACKGROUND: Bayesian hierarchical models have been proposed to combine evidence from different types of study designs. However, when combining evidence from randomised and non-randomised controlled studies, imbalances in patient characteristics between study arms may bias the results. The objective of this study was to assess the performance of a proposed Bayesian approach to adjust for imbalances in patient level covariates when combining evidence from both types of study designs. METHODOLOGY/PRINCIPAL FINDINGS: Simulation techniques, in which the truth is known, were used to generate sets of data for randomised and non-randomised studies. Covariate imbalances between study arms were introduced in the non-randomised studies. The performance of the Bayesian hierarchical model adjusted for imbalances was assessed in terms of bias. The data were also modelled using three other Bayesian approaches for synthesising evidence from randomised and non-randomised studies. The simulations considered six scenarios aimed at assessing the sensitivity of the results to changes in the impact of the imbalances and the relative number and size of studies of each type. For all six scenarios considered, the Bayesian hierarchical model adjusted for differences within studies gave results that were unbiased and closest to the true value compared to the other models. CONCLUSIONS/SIGNIFICANCE: Where informed health care decision making requires the synthesis of evidence from randomised and non-randomised study designs, the proposed hierarchical Bayesian method adjusted for differences in patient characteristics between study arms may facilitate the optimal use of all available evidence leading to unbiased results compared to unadjusted analyses.
Institute of Scientific and Technical Information of China (English)
QIAN Shang-Wu; GU Zhi-Yu
2003-01-01
This article discusses the covariance correlation tensor (CCT) in quantum network theory for four Bell bases in detail. Furthermore, it gives the expression of the density operator in terms of CCT for a quantum network of three nodes, thus gives the criterion of entanglement for this case, i.e. the conditions of complete separability and partial separability for a given quantum state of three bodies. Finally it discusses the general case for the quantum network of m≥3 nodes.
Covariate-adjusted borrowing of historical control data in randomized clinical trials.
Han, Baoguang; Zhan, Jia; John Zhong, Z; Liu, Dawei; Lindborg, Stacy
2017-07-01
The borrowing of historical control data can be an efficient way to improve the treatment effect estimate of the current control group in a randomized clinical trial. When the historical and current control data are consistent, the borrowing of historical data can increase power and reduce Type I error rate. However, when these 2 sources of data are inconsistent, it may result in a combination of biased estimates, reduced power, and inflation of Type I error rate. In some situations, inconsistency between historical and current control data may be caused by a systematic variation in the measured baseline prognostic factors, which can be appropriately addressed through statistical modeling. In this paper, we propose a Bayesian hierarchical model that can incorporate patient-level baseline covariates to enhance the appropriateness of the exchangeability assumption between current and historical control data. The performance of the proposed method is shown through simulation studies, and its application to a clinical trial design for amyotrophic lateral sclerosis is described. The proposed method is developed for scenarios involving multiple imbalanced prognostic factors and thus has meaningful implications for clinical trials evaluating new treatments for heterogeneous diseases such as amyotrophic lateral sclerosis. Copyright © 2017 John Wiley & Sons, Ltd.
Neumann, Anke; Billionnet, Cécile
2016-06-01
In observational studies without random assignment of the treatment, the unadjusted comparison between treatment groups may be misleading due to confounding. One method to adjust for measured confounders is inverse probability of treatment weighting. This method can also be used in the analysis of time to event data with competing risks. Competing risks arise if for some individuals the event of interest is precluded by a different type of event occurring before, or if only the earliest of several times to event, corresponding to different event types, is observed or is of interest. In the presence of competing risks, time to event data are often characterized by cumulative incidence functions, one for each event type of interest. We describe the use of inverse probability of treatment weighting to create adjusted cumulative incidence functions. This method is equivalent to direct standardization when the weight model is saturated. No assumptions about the form of the cumulative incidence functions are required. The method allows studying associations between treatment and the different types of event under study, while focusing on the earliest event only. We present a SAS macro implementing this method and we provide a worked example.
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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.
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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
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.
Akemann, Gernot; Checinski, Tomasz; Kieburg, Mario
2016-08-01
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.
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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.
Separation of Correlated Astrophysical Sources Using Multiple-Lag Data Covariance Matrices
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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.
Pre-Processing Noise Cross-Correlations with Equalizing the Network Covariance Matrix Eigen-Spectrum
Seydoux, L.; de Rosny, J.; Shapiro, N.
2016-12-01
Theoretically, the extraction of Green functions from noise cross-correlation requires the ambient seismic wavefield to be generated by uncorrelated sources evenly distributed in the medium. Yet, this condition is often not verified. Strong events such as earthquakes often produce highly coherent transient signals. Also, the microseismic noise is generated at specific places on the Earth's surface with source regions often very localized in space. Different localized and persistent seismic sources may contaminate the cross-correlations of continuous records resulting in spurious arrivals or asymmetry and, finally, in biased travel-time measurements. Pre-processing techniques therefore must be applied to the seismic data in order to reduce the effect of noise anisotropy and the influence of strong localized events. Here we describe a pre-processing approach that uses the covariance matrix computed from signals recorded by a network of seismographs. We extend the widely used time and spectral equalization pre-processing to the equalization of the covariance matrix spectrum (i.e., its ordered eigenvalues). This approach can be considered as a spatial equalization. This method allows us to correct for the wavefield anisotropy in two ways: (1) the influence of strong directive sources is substantially attenuated, and (2) the weakly excited modes are reinforced, allowing to partially recover the conditions required for the Green's function retrieval. We also present an eigenvector-based spatial filter used to distinguish between surface and body waves. This last filter is used together with the equalization of the eigenvalue spectrum. We simulate two-dimensional wavefield in a heterogeneous medium with strongly dominating source. We show that our method greatly improves the travel-time measurements obtained from the inter-station cross-correlation functions. Also, we apply the developed method to the USArray data and pre-process the continuous records strongly influenced
Kwun, Jihye; Song, Hyo-Jong; Park, Jong-Im
2013-04-01
Background error covariance matrix is very important for variational data assimilation system, determining how the information from observed variables is spread to unobserved variables and spatial points. The full representation of the matrix is impossible because of the huge size so the matrix is constructed implicitly by means of a variable transformation. It is assumed that the forecast errors in the control variables chosen are statistically independent. We used the cubed-sphere geometry based on the spectral element method which is better for parallel application. In cubed-sphere grids, the grid points are located at Gauss-Legendre-Lobatto points on each local element of 6 faces on the sphere. The two stages of the transformation were used in this study. The first is the variable transformation from model to a set of control variables whose errors are assumed to be uncorrelated, which was developed on the cubed sphere-using Galerkin method. Winds are decomposed into rotational part and divergent part by introducing stream function and velocity potential as control variables. The dynamical constraint for balance between mass and wind were made by applying linear balance operator. The second is spectral transformation which is to remove the remaining spatial correlation. The bases for the spectral transform were generated for the cubed-sphere grid. 6-hr difference fields of shallow water equation (SWE) model run initialized by variational data assimilation system were used to obtain forecast error statistics. In the horizontal background error covariance modeling, the regression analysis of the control variables was performed to define the unbalanced variables as the difference between full and correlated part. Regression coefficient was used to remove the remaining correlations between variables.
Pre-processing ambient noise cross-correlations with equalizing the covariance matrix eigenspectrum
Seydoux, Léonard; de Rosny, Julien; Shapiro, Nikolai M.
2017-09-01
Passive imaging techniques from ambient seismic noise requires a nearly isotropic distribution of the noise sources in order to ensure reliable traveltime measurements between seismic stations. However, real ambient seismic noise often partially fulfils this condition. It is generated in preferential areas (in deep ocean or near continental shores), and some highly coherent pulse-like signals may be present in the data such as those generated by earthquakes. Several pre-processing techniques have been developed in order to attenuate the directional and deterministic behaviour of this real ambient noise. Most of them are applied to individual seismograms before cross-correlation computation. The most widely used techniques are the spectral whitening and temporal smoothing of the individual seismic traces. We here propose an additional pre-processing to be used together with the classical ones, which is based on the spatial analysis of the seismic wavefield. We compute the cross-spectra between all available stations pairs in spectral domain, leading to the data covariance matrix. We apply a one-bit normalization to the covariance matrix eigenspectrum before extracting the cross-correlations in the time domain. The efficiency of the method is shown with several numerical tests. We apply the method to the data collected by the USArray, when the M8.8 Maule earthquake occurred on 2010 February 27. The method shows a clear improvement compared with the classical equalization to attenuate the highly energetic and coherent waves incoming from the earthquake, and allows to perform reliable traveltime measurement even in the presence of the earthquake.
Energy Technology Data Exchange (ETDEWEB)
Palmiotti, Giuseppe; Salvatores, Massimo; Hursin, Mathieu; Kodeli, Ivo; Gabrielli, Fabrizio; Hummel, Andrew
2016-11-01
A critical examination of the role of uncertainty assessment, target accuracies, role of integral experiment for validation and, consequently, of data adjustments methods is underway since several years at OECD-NEA, the objective being to provide criteria and practical approaches to use effectively the results of sensitivity analyses and cross section adjustments for feedback to evaluators and experimentalists in order to improve without ambiguities the knowledge of neutron cross sections, uncertainties, and correlations to be used in a wide range of applications and to meet new requirements and constraints for innovative reactor and fuel cycle system design. An approach will be described that expands as much as possible the use in the adjustment procedure of selected integral experiments that provide information on “elementary” phenomena, on separated individual physics effects related to specific isotopes or on specific energy ranges. An application to a large experimental data base has been performed and the results are discussed in the perspective of new evaluation projects like the CIELO initiative.
Modeling the angular correlation function and its full covariance in Photometric Galaxy Surveys
Crocce, Martin; Gaztañaga, Enrique
2010-01-01
Near future cosmology will see the advent of wide area photometric galaxy surveys, like the Dark Energy Survey (DES), that extent to high redshifts (z ~ 1 - 2) but with poor radial distance resolution. In such cases splitting the data into redshift bins and using the angular correlation function $w(\\theta)$, or the $C_{\\ell}$ power spectrum, will become the standard approach to extract cosmological information or to study the nature of dark energy through the Baryon Acoustic Oscillations (BAO) probe. In this work we present a detailed model for $w(\\theta)$ at large scales as a function of redshift and bin width, including all relevant effects, namely nonlinear gravitational clustering, bias, redshift space distortions and photo-z uncertainties. We also present a model for the full covariance matrix characterizing the angular correlation measurements, that takes into account the same effects as for $w(\\theta)$ and also the possibility of a shot-noise component and partial sky coverage. Provided with a large vo...
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.
Fang, L Z; Fang, Li-Zhi; Feng, Long-Long
2000-01-01
We present a method of measuring galaxy power spectrum based on the multiresolution analysis of the discrete wavelet transformation (DWT). Since the DWT representation has strong capability of suppressing the off-diagonal components of the covariance for selfsimilar clustering, the DWT covariance for popular models of the cold dark matter cosmogony generally is diagonal, or $j$(scale)-diagonal in the scale range, in which the second scale-scale correlations are weak. In this range, the DWT covariance gives a lossless estimation of the power spectrum, which is equal to the corresponding Fourier power spectrum banded with a logarithmical scaling. In the scale range, in which the scale-scale correlation is significant, the accuracy of a power spectrum detection depends on the scale-scale or band-band correlations. This is, for a precision measurements of the power spectrum, a measurement of the scale-scale or band-band correlations is needed. We show that the DWT covariance can be employed to measuring both the ...
Correlates of Kindergarten Adjustment: Temperament and Communicative Competence.
Skarpness, Lorie R.; Carson, David K.
1987-01-01
The kindergarten adjustment of 217 Caucasian children was measured in relation to their temperament and communicative competence. Both communicative competence and various dimensions of temperament accounted for a significant proportion of the variance in kindergarten adjustment among the children. (Author/BB)
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
Huang, Lan; Tiwari, Ram C; Pickle, Linda W; Zou, Zhaohui
2010-10-15
In the field of cluster detection, a weighted normal model-based scan statistic was recently developed to analyze regional continuous data and to evaluate the clustering pattern of pre-defined cells (such as state, county, tract, school, hospital) that include many individuals. The continuous measures of interest are, for example, the survival rate, mortality rate, length of physical activity, or the obesity measure, namely, body mass index, at the cell level with an uncertainty measure for each cell. In this paper, we extend the method to search for clusters of the cells after adjusting for single/multiple categorical/continuous covariates. We apply the proposed method to 1999-2003 obesity data in the United States (US) collected by CDC's Behavioral Risk Factor Surveillance System with adjustment for age and race, and to 1999-2003 lung cancer age-adjusted mortality data by gender in the United States from the Surveillance Epidemiology and End Results (SEER Program) with adjustment for smoking and income.
Wang, Shen; Yao, Xue Feng; Su, Yun Quan; Liu, Wei
2017-02-01
In this paper, the basic principle and application of linear gray scale adjustment method are investigated in high temperature digital image correlation (DIC) technology. First, the simple linear gray scale adjustment method is proposed, which can adjust the gray scale value of the saturated pixels and diminish the correlation error caused by the saturated pixels. Then, both the simulated high temperature images and DIC correlation results before and after the gray scale adjustment are provided and analyzed to verify its effectiveness, in which the displacement error decreased from 0.1 pixels to 0.04 pixels after the linear gray scale adjustment for high temperature images. Finally, the linear gray scale adjustment method is used to extract the displacement with high accuracy in high temperature experiment of SiC specimen, and the displacement error decreased from 0.5 pixels to 0.1 pixels after the linear gray scale adjustment.
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.
Directory of Open Access Journals (Sweden)
Sheng Zhong
2016-10-01
Full Text Available We consider the problem of genetic association testing of a binary trait in a sample that contains related individuals, where we adjust for relevant covariates and allow for missing data. We propose CERAMIC, an estimating equation approach that can be viewed as a hybrid of logistic regression and linear mixed-effects model (LMM approaches. CERAMIC extends the recently proposed CARAT method to allow samples with related individuals and to incorporate partially missing data. In simulations, we show that CERAMIC outperforms existing LMM and generalized LMM approaches, maintaining high power and correct type 1 error across a wider range of scenarios. CERAMIC results in a particularly large power increase over existing methods when the sample includes related individuals with some missing data (e.g., when some individuals with phenotype and covariate information have missing genotype, because CERAMIC is able to make use of the relationship information to incorporate partially missing data in the analysis while correcting for dependence. Because CERAMIC is based on a retrospective analysis, it is robust to misspecification of the phenotype model, resulting in better control of type 1 error and higher power than that of prospective methods, such as GMMAT, when the phenotype model is misspecified. CERAMIC is computationally efficient for genomewide analysis in samples of related individuals of almost any configuration, including small families, unrelated individuals and even large, complex pedigrees. We apply CERAMIC to data on type 2 diabetes (T2D from the Framingham Heart Study. In a genome scan, 9 of the 10 smallest CERAMIC p-values occur in or near either known T2D susceptibility loci or plausible candidates, verifying that CERAMIC is able to home in on the important loci in a genome scan.
Lu, K Q; Li, Z P; Yao, J M; Meng, J
2015-01-01
We report the first global study of dynamic correlation energies (DCEs) associated with rotational motion and quadrupole shape vibrational motion in a covariant energy density functional (CEDF) for 575 even-even nuclei with proton numbers ranging from $Z=8$ to $Z=108$ by solving a five-dimensional collective Hamiltonian, the collective parameters of which are determined from triaxial relativistic mean-field plus BCS calculation using the PC-PK1 force. After taking into account these beyond mean-field DCEs, the root-mean-square (rms) deviation with respect to nuclear masses is reduced significantly down to 1.14 MeV, which is smaller than those of other successful CEDFs: NL3* (2.96 MeV), DD-ME2 (2.39 MeV), DD-ME$\\delta$ (2.29 MeV) and DD-PC1 (2.01 MeV). Moreover, the rms deviation for two-nucleon separation energies is reduced by $\\sim34\\%$ in comparison with cranking prescription.
Barrantes-Vidal, Neus; Lewandowski, Kathryn E; Kwapil, Thomas R
2010-09-01
Correlational methods, unlike cluster analyses, cannot take into account the possibility that individuals score highly on more than one symptom dimension simultaneously. This may account for some of the inconsistency found in the literature of correlates of schizotypy dimensions. This study explored the clustering of positive and negative schizotypy dimensions in nonclinical subjects and whether schizotypy clusters have meaningful patterns of adjustment in terms of psychopathology, social functioning, and personality. Positive and negative schizotypy dimensional scores were derived from the Chapman Psychosis-Proneness Scales for 6137 college students and submitted to cluster analysis. Of these, 780 completed the NEO-PI-R and Social Adjustment Scale-self report version, and a further 430 were interviewed for schizophrenia-spectrum, mood, and substance use psychopathology. Four clusters were obtained: low (nonschizotypic), high positive, high negative, and mixed (high positive and negative) schizotypy. The positive schizotypy cluster presented high rates of psychotic-like experiences, schizotypal and paranoid symptoms, had affective and substance abuse pathology, and was open to experience and extraverted. The negative schizotypy cluster had high rates of negative and schizoid symptoms, impaired social adjustment, high conscientiousness and low agreeableness. The mixed cluster was the most deviant on almost all aspects. Our cluster solution is consistent with the limited cluster analytic studies reported in schizotypy and schizophrenia, indicating that meaningful profiles of schizotypy features can be detected in nonclinical populations. The clusters identified displayed a distinct and meaningful pattern of correlates in different domains, thus providing construct validity to the schizotypy types defined. (c) 2010 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
José Segura C.
2013-11-01
Full Text Available Objective. The purpose of this study was to compare the intra-class correlation coefficients (ICC and design effects (D estimates adjusted or unadjusted for sensibility (Se and specificity (Sp of the diagnostic tests using a Bayesian procedure. Materials and methods. Sera from 232 animals from 44 randomly selected herds, to detect antibodies against parainfluenza-3 virus (PIV3 from non-vaccinated dual-purpose cattle from Colima Mexico, were used. Only 176 animals from 33 herds were used to evaluate the presence of the bovine respiratory syncytial virus (BRSV. Results. The ICC and D values adjusted and unadjusted for PIV3 were 0.33, 2.73, 0.32, and 2.71, respectively. For BRSV the values were 0.31, 2.64, 0.28 and 2.49. Conclusions. The adjusted or unadjusted ICC and D estimates were similar because of the high Se and Sp of the diagnostic tests and the relatively high prevalence of the diseases here studied.
Fan, Ya-Jing; Cao, Huai-Xin; Meng, Hui-Xian; Chen, Liang
2016-12-01
The uncertainty principle in quantum mechanics is a fundamental relation with different forms, including Heisenberg's uncertainty relation and Schrödinger's uncertainty relation. In this paper, we prove a Schrödinger-type uncertainty relation in terms of generalized metric adjusted skew information and correlation measure by using operator monotone functions, which reads, U_ρ ^{(g,f)}(A)U_ρ ^{(g,f)}(B)≥ f(0)^2l/k| Corr_ρ ^{s(g,f)}(A,B)| ^2 for some operator monotone functions f and g, all n-dimensional observables A, B and a non-singular density matrix ρ . As applications, we derive some new uncertainty relations for Wigner-Yanase skew information and Wigner-Yanase-Dyson skew information.
Fan, Ya-Jing; Cao, Huai-Xin; Meng, Hui-Xian; Chen, Liang
2016-09-01
The uncertainty principle in quantum mechanics is a fundamental relation with different forms, including Heisenberg's uncertainty relation and Schrödinger's uncertainty relation. In this paper, we prove a Schrödinger-type uncertainty relation in terms of generalized metric adjusted skew information and correlation measure by using operator monotone functions, which reads, U_ρ ^{(g,f)}(A)U_ρ ^{(g,f)}(B)≥ f(0)^2l/k| {Corr}_ρ ^{s(g,f)}(A,B)| ^2 for some operator monotone functions f and g, all n-dimensional observables A, B and a non-singular density matrix ρ . As applications, we derive some new uncertainty relations for Wigner-Yanase skew information and Wigner-Yanase-Dyson skew information.
Frasinski, Leszek J.
2016-08-01
Recent technological advances in the generation of intense femtosecond pulses have made covariance mapping an attractive analytical technique. The laser pulses available are so intense that often thousands of ionisation and Coulomb explosion events will occur within each pulse. To understand the physics of these processes the photoelectrons and photoions need to be correlated, and covariance mapping is well suited for operating at the high counting rates of these laser sources. Partial covariance is particularly useful in experiments with x-ray free electron lasers, because it is capable of suppressing pulse fluctuation effects. A variety of covariance mapping methods is described: simple, partial (single- and multi-parameter), sliced, contingent and multi-dimensional. The relationship to coincidence techniques is discussed. Covariance mapping has been used in many areas of science and technology: inner-shell excitation and Auger decay, multiphoton and multielectron ionisation, time-of-flight and angle-resolved spectrometry, infrared spectroscopy, nuclear magnetic resonance imaging, stimulated Raman scattering, directional gamma ray sensing, welding diagnostics and brain connectivity studies (connectomics). This review gives practical advice for implementing the technique and interpreting the results, including its limitations and instrumental constraints. It also summarises recent theoretical studies, highlights unsolved problems and outlines a personal view on the most promising research directions.
Covariant approximation averaging
Shintani, Eigo; Blum, Thomas; Izubuchi, Taku; Jung, Chulwoo; Lehner, Christoph
2014-01-01
We present a new class of statistical error reduction techniques for Monte-Carlo simulations. Using covariant symmetries, we show that correlation functions can be constructed from inexpensive approximations without introducing any systematic bias in the final result. We introduce a new class of covariant approximation averaging techniques, known as all-mode averaging (AMA), in which the approximation takes account of contributions of all eigenmodes through the inverse of the Dirac operator computed from the conjugate gradient method with a relaxed stopping condition. In this paper we compare the performance and computational cost of our new method with traditional methods using correlation functions and masses of the pion, nucleon, and vector meson in $N_f=2+1$ lattice QCD using domain-wall fermions. This comparison indicates that AMA significantly reduces statistical errors in Monte-Carlo calculations over conventional methods for the same cost.
Gibbons, Laura E; Crane, Paul K; Mehta, Kala M; Pedraza, Otto; Tang, Yuxiao; Manly, Jennifer J; Narasimhalu, Kaavya; Teresi, Jeanne; Jones, Richard N; Mungas, Dan
2011-04-28
Differential item functioning (DIF) occurs when a test item has different statistical properties in subgroups, controlling for the underlying ability measured by the test. DIF assessment is necessary when evaluating measurement bias in tests used across different language groups. However, other factors such as educational attainment can differ across language groups, and DIF due to these other factors may also exist. How to conduct DIF analyses in the presence of multiple, correlated factors remains largely unexplored. This study assessed DIF related to Spanish versus English language in a 44-item object naming test. Data come from a community-based sample of 1,755 Spanish- and English-speaking older adults. We compared simultaneous accounting, a new strategy for handling differences in educational attainment across language groups, with existing methods. Compared to other methods, simultaneously accounting for language- and education-related DIF yielded salient differences in some object naming scores, particularly for Spanish speakers with at least 9 years of education. Accounting for factors that vary across language groups can be important when assessing language DIF. The use of simultaneous accounting will be relevant to other cross-cultural studies in cognition and in other fields, including health-related quality of life.
Capri, M A L; Pereira, A D; Fiorentini, D; Guimaraes, M S; Mintz, B W; Palhares, L F; Sorella, S P
2016-01-01
In order to construct a gauge invariant two-point function in a Yang-Mills theory, we propose the use of the all-order gauge invariant transverse configurations A^h. Such configurations can be obtained through the minimization of the functional A^2_{min} along the gauge orbit within the BRST invariant formulation of the Gribov-Zwanziger framework recently put forward in [1,2] for the class of the linear covariant gauges. This correlator turns out to provide a characterization of non-perturbative aspects of the theory in a BRST invariant and gauge parameter independent way. In particular, it turns out that the poles of are the same as those of the transverse part of the gluon propagator, which are also formally shown to be independent of the gauge parameter entering the gauge condition through the Nielsen identities. The latter follow from the new exact BRST invariant formulation introduced before. Moreover, the correlator enables us to attach a BRST invariant meaning to the possible positivity violation of ...
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.
Biswas, Bikram K.; Alam, Mohammad S.; Chowdhury, Suparna
2016-04-01
An improved shifted phase-encoded fringe-adjusted joint transform correlation technique is proposed in this paper for face recognition which can accommodate the detrimental effects of noise, illumination, and other 3D distortions such as expression and rotation variations. This technique utilizes a third order local derivative pattern operator (LDP3) followed by a shifted phase-encoded fringe-adjusted joint transform correlation (SPFJTC) operation. The local derivative pattern operator ensures better facial feature extraction in a variable environment while the SPFJTC yields robust correlation output for the desired signals. The performance of the proposed method is determined by using the Yale Face Database, Yale Face Database B, and Georgia Institute of Technology Face Database. This technique has been found to yield better face recognition rate compared to alternate JTC based techniques.
Jordan, Cheryl; Sin, Jacqueline; Fear, Nicola T; Chalder, Trudie
2016-07-01
Inflammatory bowel disease (IBD) is a chronic long term condition which poses significant psychosocial adjustment challenges. The purpose of this review was to systematically identify psychological factors related to adjustment in adults with IBD with the aim of suggesting evidence based targets that may be modifiable though psychological intervention. Twenty five studies met inclusion criteria and were included in the systematic review and a narrative synthesis was conducted. A wide range of psychological variables were addressed covering six broad categories; personality traits, interpersonal traits, stress and coping, emotions and emotional control, IBD related cognitions and non IBD related cognitions. The most consistent relationship was found between certain emotion focused coping strategies and worse adjustment outcomes in IBD. Some evidence also hi-lighted a relationship between personality traits (such as neuroticism,) perceived stress, emotions and emotional control (such as alexithymia) and IBD related cognitions (such as illness perceptions) and negative adjustment outcomes. The results of this review suggest that interventions to improve adjustment in IBD may benefit from a focus on coping strategies, perceived stress and IBD related cognitions.
Ruan, Hang; Li, Jian; Zhang, Lei; Long, Teng
2015-08-28
For vehicle positioning with Global Navigation Satellite System (GNSS) in urban areas, open-loop tracking shows better performance because of its high sensitivity and superior robustness against multipath. However, no previous study has focused on the effects of the code search grid size on the code phase measurement accuracy of open-loop tracking. Traditional open-loop tracking methods are performed by the batch correlators with fixed correlation space. The code search grid size, which is the correlation space, is a constant empirical value and the code phase measuring accuracy will be largely degraded due to the improper grid size, especially when the signal carrier-to-noise density ratio (C/N₀) varies. In this study, the Adaptive Correlation Space Adjusted Open-Loop Tracking Approach (ACSA-OLTA) is proposed to improve the code phase measurement dependent pseudo range accuracy. In ACSA-OLTA, the correlation space is adjusted according to the signal C/N₀. The novel Equivalent Weighted Pseudo Range Error (EWPRE) is raised to obtain the optimal code search grid sizes for different C/N₀. The code phase measuring errors of different measurement calculation methods are analyzed for the first time. The measurement calculation strategy of ACSA-OLTA is derived from the analysis to further improve the accuracy but reduce the correlator consumption. Performance simulation and real tests confirm that the pseudo range and positioning accuracy of ASCA-OLTA are better than the traditional open-loop tracking methods in the usual scenarios of urban area.
The Fifth Cell: Correlation Bias in U.S. Census Adjustment.
Wachter, Kenneth W.; Freedman, David A.
2000-01-01
Presents a method for estimating the total national number of doubly missing people (missing from Census counts and adjusted counts as well) and their distribution by race and sex. Application to the 1990 U.S. Census yields an estimate of three million doubly-missing people. (SLD)
Estimating Cosmological Parameter Covariance
Taylor, Andy
2014-01-01
We investigate the bias and error in estimates of the cosmological parameter covariance matrix, due to sampling or modelling the data covariance matrix, for likelihood width and peak scatter estimators. We show that these estimators do not coincide unless the data covariance is exactly known. For sampled data covariances, with Gaussian distributed data and parameters, the parameter covariance matrix estimated from the width of the likelihood has a Wishart distribution, from which we derive the mean and covariance. This mean is biased and we propose an unbiased estimator of the parameter covariance matrix. Comparing our analytic results to a numerical Wishart sampler of the data covariance matrix we find excellent agreement. An accurate ansatz for the mean parameter covariance for the peak scatter estimator is found, and we fit its covariance to our numerical analysis. The mean is again biased and we propose an unbiased estimator for the peak parameter covariance. For sampled data covariances the width estimat...
Levy Matrices and Financial Covariances
Burda, Zdzislaw; Jurkiewicz, Jerzy; Nowak, Maciej A.; Papp, Gabor; Zahed, Ismail
2003-10-01
In a given market, financial covariances capture the intra-stock correlations and can be used to address statistically the bulk nature of the market as a complex system. We provide a statistical analysis of three SP500 covariances with evidence for raw tail distributions. We study the stability of these tails against reshuffling for the SP500 data and show that the covariance with the strongest tails is robust, with a spectral density in remarkable agreement with random Lévy matrix theory. We study the inverse participation ratio for the three covariances. The strong localization observed at both ends of the spectral density is analogous to the localization exhibited in the random Lévy matrix ensemble. We discuss two competitive mechanisms responsible for the occurrence of an extensive and delocalized eigenvalue at the edge of the spectrum: (a) the Lévy character of the entries of the correlation matrix and (b) a sort of off-diagonal order induced by underlying inter-stock correlations. (b) can be destroyed by reshuffling, while (a) cannot. We show that the stocks with the largest scattering are the least susceptible to correlations, and likely candidates for the localized states. We introduce a simple model for price fluctuations which captures behavior of the SP500 covariances. It may be of importance for assets diversification.
Directory of Open Access Journals (Sweden)
Hang Ruan
2015-08-01
Full Text Available For vehicle positioning with Global Navigation Satellite System (GNSS in urban areas, open-loop tracking shows better performance because of its high sensitivity and superior robustness against multipath. However, no previous study has focused on the effects of the code search grid size on the code phase measurement accuracy of open-loop tracking. Traditional open-loop tracking methods are performed by the batch correlators with fixed correlation space. The code search grid size, which is the correlation space, is a constant empirical value and the code phase measuring accuracy will be largely degraded due to the improper grid size, especially when the signal carrier-to-noise density ratio (C/N0 varies. In this study, the Adaptive Correlation Space Adjusted Open-Loop Tracking Approach (ACSA-OLTA is proposed to improve the code phase measurement dependent pseudo range accuracy. In ACSA-OLTA, the correlation space is adjusted according to the signal C/N0. The novel Equivalent Weighted Pseudo Range Error (EWPRE is raised to obtain the optimal code search grid sizes for different C/N0. The code phase measuring errors of different measurement calculation methods are analyzed for the first time. The measurement calculation strategy of ACSA-OLTA is derived from the analysis to further improve the accuracy but reduce the correlator consumption. Performance simulation and real tests confirm that the pseudo range and positioning accuracy of ASCA-OLTA are better than the traditional open-loop tracking methods in the usual scenarios of urban area.
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.
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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
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
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 confound
Institute of Scientific and Technical Information of China (English)
Naheed Akhtar; Bader Faiyaz Zuberi; Syed Riazul Hasan; Raj Kumar; Salahuddin Afsar
2009-01-01
AIM: To determine the correlation of Adjusted Blood Requirement Index (ABRI) with the 7th day outcome in patients presenting with acute variceal bleeding.METHODS: All patients presenting with acute variceal hemorrhage (AVH) were included. Patients with previous band ligation, sclerotherapy, gastrointestinal or hepatic malignancies were excluded. Patients were managed as per standard protocol for AVH with terlipressin and band ligation. ABRI scores were calculated using the formula outcome of alive or expired up to the 7th day after treatment. The correlation between ABRI and mortality was estimated and a receiver operative characteristic (ROC) curve was plotted.RESULTS: A total of 113 patients (76 male; 37 female) were included. On assessment, 18 were in Child's Pugh Class A, 82 in Class B and 13 were in Class C. The median number of blood units transfused ± inter-quartile range was 3.0 ± 2.0. The median ± inter-quartile range for ABRI was 1.3 ± 1.1. The ROC curve of ABRI for expiry showed a significantly large area of 0.848 ( P < 0.0001; 95% CI: 0.75-0.95). A significant correlation of log transformation of ABRI with an outcome of mortality was present ( P < 0.0001). CONCLUSION: ABRI correlates strongly with mortality.
Manifestly covariant electromagnetism
Energy Technology Data Exchange (ETDEWEB)
Hillion, P. [Institut Henri Poincare' , Le Vesinet (France)
1999-03-01
The conventional relativistic formulation of electromagnetism is covariant under the full Lorentz group. But relativity requires covariance only under the proper Lorentz group and the authors present here the formalism covariant under the complex rotation group isomorphic to the proper Lorentz group. The authors discuss successively Maxwell's equations, constitutive relations and potential functions. A comparison is made with the usual formulation.
Multivariate covariance generalized linear models
DEFF Research Database (Denmark)
Bonat, W. H.; Jørgensen, Bent
2016-01-01
We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models, designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation structures defined in terms of a covariance link...... function combined with a matrix linear predictor involving known matrices. The method is motivated by three data examples that are not easily handled by existing methods. The first example concerns multivariate count data, the second involves response variables of mixed types, combined with repeated...... are fitted by using an efficient Newton scoring algorithm based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides a unified approach to a wide variety of types of response variables and covariance structures, including multivariate extensions...
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 flexible dependence patterns for volatilities and correlations, and can be applied to covariance matrices of large dimensions. The separate modeling of volatility and correlation forecasts considerably reduces the estimation and measurement error implied by the joint estimation and modeling of covariance...... matrix dynamics. Our empirical results show that the new mixing approach provides superior forecasts compared to multivariate volatility specifications using single sources of information....
Parameter inference with estimated covariance matrices
Sellentin, Elena
2015-01-01
When inferring parameters from a Gaussian-distributed data set by computing a likelihood, a covariance matrix is needed that describes the data errors and their correlations. If the covariance matrix is not known a priori, it may be estimated and thereby becomes a random object with some intrinsic uncertainty itself. We show how to infer parameters in the presence of such an estimated covariance matrix, by marginalising over the true covariance matrix, conditioned on its estimated value. This leads to a likelihood function that is no longer Gaussian, but rather an adapted version of a multivariate $t$-distribution, which has the same numerical complexity as the multivariate Gaussian. As expected, marginalisation over the true covariance matrix improves inference when compared with Hartlap et al.'s method, which uses an unbiased estimate of the inverse covariance matrix but still assumes that the likelihood is Gaussian.
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.
Covariant Hamiltonian field theory
Giachetta, G; Sardanashvily, G
1999-01-01
We study the relationship between the equations of first order Lagrangian field theory on fiber bundles and the covariant Hamilton equations on the finite-dimensional polysymplectic phase space of covariant Hamiltonian field theory. The main peculiarity of these Hamilton equations lies in the fact that, for degenerate systems, they contain additional gauge fixing conditions. We develop the BRST extension of the covariant Hamiltonian formalism, characterized by a Lie superalgebra of BRST and anti-BRST symmetries.
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
Representations of Inverse Covariances by Differential Operators
Institute of Scientific and Technical Information of China (English)
Qin XU
2005-01-01
In the cost function of three- or four-dimensional variational data assimilation, each term is weighted by the inverse of its associated error covariance matrix and the background error covariance matrix is usually much larger than the other covariance matrices. Although the background error covariances are traditionally normalized and parameterized by simple smooth homogeneous correlation functions, the covariance matrices constructed from these correlation functions are often too large to be inverted or even manipulated. It is thus desirable to find direct representations of the inverses of background errorcorrelations. This problem is studied in this paper. In particular, it is shown that the background term can be written into ∫ dx|Dv(x)|2, that is, a squared L2 norm of a vector differential operator D, called the D-operator, applied to the field of analysis increment v(x). For autoregressive correlation functions, the Doperators are of finite orders. For Gaussian correlation functions, the D-operators are of infinite order. For practical applications, the Gaussian D-operators must be truncated to finite orders. The truncation errors are found to be small even when the Gaussian D-operators are truncated to low orders. With a truncated D-operator, the background term can be easily constructed with neither inversion nor direct calculation of the covariance matrix. D-operators are also derived for non-Gaussian correlations and transformed into non-isotropic forms.
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.
Yang, Tao; Zhang, Feipeng; Yardimci, Galip Gurkan; Song, Fan; Hardison, Ross C; Noble, William Stafford; Yue, Feng; Li, Qunhua
2017-08-30
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. Published by Cold Spring Harbor Laboratory Press.
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
Phenotypic covariance at species’ borders
2013-01-01
Background Understanding the evolution of species limits is important in ecology, evolution, and conservation biology. Despite its likely importance in the evolution of these limits, little is known about phenotypic covariance in geographically marginal populations, and the degree to which it constrains, or facilitates, responses to selection. We investigated phenotypic covariance in morphological traits at species’ borders by comparing phenotypic covariance matrices (P), including the degree of shared structure, the distribution of strengths of pair-wise correlations between traits, the degree of morphological integration of traits, and the ranks of matricies, between central and marginal populations of three species-pairs of coral reef fishes. Results Greater structural differences in P were observed between populations close to range margins and conspecific populations toward range centres, than between pairs of conspecific populations that were both more centrally located within their ranges. Approximately 80% of all pair-wise trait correlations within populations were greater in the north, but these differences were unrelated to the position of the sampled population with respect to the geographic range of the species. Conclusions Neither the degree of morphological integration, nor ranks of P, indicated greater evolutionary constraint at range edges. Characteristics of P observed here provide no support for constraint contributing to the formation of these species’ borders, but may instead reflect structural change in P caused by selection or drift, and their potential to evolve in the future. PMID:23714580
Diallo, Thierno M O; Morin, Alexandre J S; Lu, HuiZhong
2017-03-01
This article evaluates the impact of partial or total covariate inclusion or exclusion on the class enumeration performance of growth mixture models (GMMs). Study 1 examines the effect of including an inactive covariate when the population model is specified without covariates. Study 2 examines the case in which the population model is specified with 2 covariates influencing only the class membership. Study 3 examines a population model including 2 covariates influencing the class membership and the growth factors. In all studies, we contrast the accuracy of various indicators to correctly identify the number of latent classes as a function of different design conditions (sample size, mixing ratio, invariance or noninvariance of the variance-covariance matrix, class separation, and correlations between the covariates in Studies 2 and 3) and covariate specification (exclusion, partial or total inclusion as influencing class membership, partial or total inclusion as influencing class membership, and the growth factors in a class-invariant or class-varying manner). The accuracy of the indicators shows important variation across studies, indicators, design conditions, and specification of the covariates effects. However, the results suggest that the GMM class enumeration process should be conducted without covariates, and should rely mostly on the Bayesian information criterion (BIC) and consistent Akaike information criterion (CAIC) as the most reliable indicators under conditions of high class separation (as indicated by higher entropy), versus the sample size adjusted BIC or CAIC (SBIC, SCAIC) and bootstrapped likelihood ratio test (BLRT) under conditions of low class separation (indicated by lower entropy). (PsycINFO Database Record
Bayes linear adjustment for variance matrices
Wilkinson, Darren J
2008-01-01
We examine the problem of covariance belief revision using a geometric approach. We exhibit an inner-product space where covariance matrices live naturally --- a space of random real symmetric matrices. The inner-product on this space captures aspects of our beliefs about the relationship between covariance matrices of interest to us, providing a structure rich enough for us to adjust beliefs about unknown matrices in the light of data such as sample covariance matrices, exploiting second-order exchangeability specifications.
Covariant Bardeen perturbation formalism
Vitenti, S. D. P.; Falciano, F. T.; Pinto-Neto, N.
2014-05-01
In a previous work we obtained a set of necessary conditions for the linear approximation in cosmology. Here we discuss the relations of this approach with the so-called covariant perturbations. It is often argued in the literature that one of the main advantages of the covariant approach to describe cosmological perturbations is that the Bardeen formalism is coordinate dependent. In this paper we will reformulate the Bardeen approach in a completely covariant manner. For that, we introduce the notion of pure and mixed tensors, which yields an adequate language to treat both perturbative approaches in a common framework. We then stress that in the referred covariant approach, one necessarily introduces an additional hypersurface choice to the problem. Using our mixed and pure tensors approach, we are able to construct a one-to-one map relating the usual gauge dependence of the Bardeen formalism with the hypersurface dependence inherent to the covariant approach. Finally, through the use of this map, we define full nonlinear tensors that at first order correspond to the three known gauge invariant variables Φ, Ψ and Ξ, which are simultaneously foliation and gauge invariant. We then stress that the use of the proposed mixed tensors allows one to construct simultaneously gauge and hypersurface invariant variables at any order.
Covariant canonical quantization
Energy Technology Data Exchange (ETDEWEB)
Hippel, G.M. von [University of Regina, Department of Physics, Regina, Saskatchewan (Canada); Wohlfarth, M.N.R. [Universitaet Hamburg, Institut fuer Theoretische Physik, Hamburg (Germany)
2006-09-15
We present a manifestly covariant quantization procedure based on the de Donder-Weyl Hamiltonian formulation of classical field theory. This procedure agrees with conventional canonical quantization only if the parameter space is d=1 dimensional time. In d>1 quantization requires a fundamental length scale, and any bosonic field generates a spinorial wave function, leading to the purely quantum-theoretical emergence of spinors as a byproduct. We provide a probabilistic interpretation of the wave functions for the fields, and we apply the formalism to a number of simple examples. These show that covariant canonical quantization produces both the Klein-Gordon and the Dirac equation, while also predicting the existence of discrete towers of identically charged fermions with different masses. Covariant canonical quantization can thus be understood as a ''first'' or pre-quantization within the framework of conventional QFT. (orig.)
Covariant canonical quantization
Von Hippel, G M; Hippel, Georg M. von; Wohlfarth, Mattias N.R.
2006-01-01
We present a manifestly covariant quantization procedure based on the de Donder-Weyl Hamiltonian formulation of classical field theory. Covariant canonical quantization agrees with conventional canonical quantization only if the parameter space is d=1 dimensional time. In d>1 quantization requires a fundamental length scale, and any bosonic field generates a spinorial wave function, leading to the purely quantum-theoretical emergence of spinors as a byproduct. We provide a probabilistic interpretation of the wave functions for the fields, and apply the formalism to a number of simple examples. These show that covariant canonical quantization produces both the Klein-Gordon and the Dirac equation, while also predicting the existence of discrete towers of identically charged fermions with different masses.
Covariance Applications with Kiwi
Mattoon, C. M.; Brown, D.; Elliott, J. B.
2012-05-01
The Computational Nuclear Physics group at Lawrence Livermore National Laboratory (LLNL) is developing a new tool, named `Kiwi', that is intended as an interface between the covariance data increasingly available in major nuclear reaction libraries (including ENDF and ENDL) and large-scale Uncertainty Quantification (UQ) studies. Kiwi is designed to integrate smoothly into large UQ studies, using the covariance matrix to generate multiple variations of nuclear data. The code has been tested using critical assemblies as a test case, and is being integrated into LLNL's quality assurance and benchmarking for nuclear data.
Covariance Applications with Kiwi
Directory of Open Access Journals (Sweden)
Elliott J.B.
2012-05-01
Full Text Available The Computational Nuclear Physics group at Lawrence Livermore National Laboratory (LLNL is developing a new tool, named ‘Kiwi’, that is intended as an interface between the covariance data increasingly available in major nuclear reaction libraries (including ENDF and ENDL and large-scale Uncertainty Quantification (UQ studies. Kiwi is designed to integrate smoothly into large UQ studies, using the covariance matrix to generate multiple variations of nuclear data. The code has been tested using critical assemblies as a test case, and is being integrated into LLNL's quality assurance and benchmarking for nuclear data.
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…
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
Progress on Nuclear Data Covariances: AFCI-1.2 Covariance Library
Energy Technology Data Exchange (ETDEWEB)
Oblozinsky,P.; Oblozinsky,P.; Mattoon,C.M.; Herman,M.; Mughabghab,S.F.; Pigni,M.T.; Talou,P.; Hale,G.M.; Kahler,A.C.; Kawano,T.; Little,R.C.; Young,P.G
2009-09-28
Improved neutron cross section covariances were produced for 110 materials including 12 light nuclei (coolants and moderators), 78 structural materials and fission products, and 20 actinides. Improved covariances were organized into AFCI-1.2 covariance library in 33-energy groups, from 10{sup -5} eV to 19.6 MeV. BNL contributed improved covariance data for the following materials: {sup 23}Na and {sup 55}Mn where more detailed evaluation was done; improvements in major structural materials {sup 52}Cr, {sup 56}Fe and {sup 58}Ni; improved estimates for remaining structural materials and fission products; improved covariances for 14 minor actinides, and estimates of mubar covariances for {sup 23}Na and {sup 56}Fe. LANL contributed improved covariance data for {sup 235}U and {sup 239}Pu including prompt neutron fission spectra and completely new evaluation for {sup 240}Pu. New R-matrix evaluation for {sup 16}O including mubar covariances is under completion. BNL assembled the library and performed basic testing using improved procedures including inspection of uncertainty and correlation plots for each material. The AFCI-1.2 library was released to ANL and INL in August 2009.
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.
Gaspar, M G; Dos Santos, M B F; Dos Santos, J F F; Marchini, L
2013-08-01
A number of variables may influence the outcome of complete denture therapy. The objective of this study was to verify possible correlations between previous experience with dentures, patient expectation and the number of post-delivery adjustments with patient satisfaction after treatment. One hundred patients (mean age 61·9 ± 10·3) rated their previous experiences with complete dentures and their expectations before and satisfaction after treatment on a visual analogue scale (VAS) using scores from 0 (worst results) to 10 (best results). The number of post-delivery adjustments and other patient-related clinical variables was also noted. Patient expectation scores were higher than previous experience scores and satisfaction after treatment scores. Positive and weak correlations were found between previous chewing experiences with complete dentures, with regard to chewing expectations and comfort of use. Phonetics and comfort of use in previous experiences presented a positive correlation with expectations for chewing, aesthetics, phonetics and comfort of use. Groups of patients with different levels of education presented significant differences in expectation scores regarding comfort of use as well. A negative and weak correlation was found between phonetics satisfaction and the number of post-delivery adjustments. Patients' expectations for the therapy were higher than their satisfaction after treatment. Previous experiences with complete dentures could slightly influence patients' expectations and satisfaction, whereas lower scores for previous experience with complete dentures caused lower scores for both expectation and satisfaction. Patients' educational levels and the number of post-delivery adjustments influenced negatively the expectations about comfort of use and patient satisfaction, respectively. © 2013 John Wiley & Sons Ltd.
Saltas, Ippocratis D
2016-01-01
We derive the 1-loop effective action of the cubic Galileon coupled to quantum-gravitational fluctuations in a background and gauge-independent manner, employing the covariant framework of DeWitt and Vilkovisky. Although the bare action respects shift symmetry, the coupling to gravity induces an effective mass to the scalar, of the order of the cosmological constant, as a direct result of the non-flat field-space metric, the latter ensuring the field-reparametrization invariance of the formalism. Within a gauge-invariant regularization scheme, we discover novel, gravitationally induced non-Galileon higher-derivative interactions in the effective action. These terms, previously unnoticed within standard, non-covariant frameworks, are not Planck suppressed. Unless tuned to be sub-dominant, their presence could have important implications for the classical and quantum phenomenology of the theory.
Using Analysis of Covariance (ANCOVA) with Fallible Covariates
Culpepper, Steven Andrew; Aguinis, Herman
2011-01-01
Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which is the norm, researchers must choose from among 3 inadequate courses of action: (a) know that the assumption that covariates are perfectly reliable is violated but…
Using Analysis of Covariance (ANCOVA) with Fallible Covariates
Culpepper, Steven Andrew; Aguinis, Herman
2011-01-01
Analysis of covariance (ANCOVA) is used widely in psychological research implementing nonexperimental designs. However, when covariates are fallible (i.e., measured with error), which is the norm, researchers must choose from among 3 inadequate courses of action: (a) know that the assumption that covariates are perfectly reliable is violated but…
Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data
Energy Technology Data Exchange (ETDEWEB)
Jun, Sung C [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Plis, Sergey M [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Ranken, Doug M [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Schmidt, David M [MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States)
2006-11-07
The performance of parametric magnetoencephalography (MEG) and electroencephalography (EEG) source localization approaches can be degraded by the use of poor background noise covariance estimates. In general, estimation of the noise covariance for spatiotemporal analysis is difficult mainly due to the limited noise information available. Furthermore, its estimation requires a large amount of storage and a one-time but very large (and sometimes intractable) calculation or its inverse. To overcome these difficulties, noise covariance models consisting of one pair or a sum of multi-pairs of Kronecker products of spatial covariance and temporal covariance have been proposed. However, these approaches cannot be applied when the noise information is very limited, i.e., the amount of noise information is less than the degrees of freedom of the noise covariance models. A common example of this is when only averaged noise data are available for a limited prestimulus region (typically at most a few hundred milliseconds duration). For such cases, a diagonal spatiotemporal noise covariance model consisting of sensor variances with no spatial or temporal correlation has been the common choice for spatiotemporal analysis. In this work, we propose a different noise covariance model which consists of diagonal spatial noise covariance and Toeplitz temporal noise covariance. It can easily be estimated from limited noise information, and no time-consuming optimization and data-processing are required. Thus, it can be used as an alternative choice when one-pair or multi-pair noise covariance models cannot be estimated due to lack of noise information. To verify its capability we used Bayesian inference dipole analysis and a number of simulated and empirical datasets. We compared this covariance model with other existing covariance models such as conventional diagonal covariance, one-pair and multi-pair noise covariance models, when noise information is sufficient to estimate them. We
Covariant Magnetic Connection Hypersurfaces
Pegoraro, F
2016-01-01
In the single fluid, nonrelativistic, ideal-Magnetohydrodynamic (MHD) plasma description magnetic field lines play a fundamental role by defining dynamically preserved "magnetic connections" between plasma elements. Here we show how the concept of magnetic connection needs to be generalized in the case of a relativistic MHD description where we require covariance under arbitrary Lorentz transformations. This is performed by defining 2-D {\\it magnetic connection hypersurfaces} in the 4-D Minkowski space. This generalization accounts for the loss of simultaneity between spatially separated events in different frames and is expected to provide a powerful insight into the 4-D geometry of electromagnetic fields when ${\\bf E} \\cdot {\\bf B} = 0$.
Universality of Covariance Matrices
Pillai, Natesh S
2011-01-01
We prove the universality of covariance matrices of the form $H_{N \\times N} = {1 \\over N} \\tp{X}X$ where $[X]_{M \\times N}$ is a rectangular matrix with independent real valued entries $[x_{ij}]$ satisfying $\\E \\,x_{ij} = 0$ and $\\E \\,x^2_{ij} = {1 \\over M}$, $N, M\\to \\infty$. Furthermore it is assumed that these entries have sub-exponential tails. We will study the asymptotics in the regime $N/M = d_N \\in (0,\\infty), \\lim_{N\\to \\infty}d_N \
Covariant Projective Extensions
Institute of Scientific and Technical Information of China (English)
许天周; 梁洁
2003-01-01
@@ The theory of crossed products of C*-algebras by groups of automorphisms is a well-developed area of the theory of operator algebras. Given the importance and the success ofthat theory, it is natural to attempt to extend it to a more general situation by, for example,developing a theory of crossed products of C*-algebras by semigroups of automorphisms, or evenof endomorphisms. Indeed, in recent years a number of papers have appeared that are concernedwith such non-classicaltheories of covariance algebras, see, for instance [1-3].
Earth Observing System Covariance Realism
Zaidi, Waqar H.; Hejduk, Matthew D.
2016-01-01
The purpose of covariance realism is to properly size a primary object's covariance in order to add validity to the calculation of the probability of collision. The covariance realism technique in this paper consists of three parts: collection/calculation of definitive state estimates through orbit determination, calculation of covariance realism test statistics at each covariance propagation point, and proper assessment of those test statistics. An empirical cumulative distribution function (ECDF) Goodness-of-Fit (GOF) method is employed to determine if a covariance is properly sized by comparing the empirical distribution of Mahalanobis distance calculations to the hypothesized parent 3-DoF chi-squared distribution. To realistically size a covariance for collision probability calculations, this study uses a state noise compensation algorithm that adds process noise to the definitive epoch covariance to account for uncertainty in the force model. Process noise is added until the GOF tests pass a group significance level threshold. The results of this study indicate that when outliers attributed to persistently high or extreme levels of solar activity are removed, the aforementioned covariance realism compensation method produces a tuned covariance with up to 80 to 90% of the covariance propagation timespan passing (against a 60% minimum passing threshold) the GOF tests-a quite satisfactory and useful result.
Land, M C
2001-01-01
This paper examines the Stark effect, as a first order perturbation of manifestly covariant hydrogen-like bound states. These bound states are solutions to a relativistic Schr\\"odinger equation with invariant evolution parameter, and represent mass eigenstates whose eigenvalues correspond to the well-known energy spectrum of the non-relativistic theory. In analogy to the nonrelativistic case, the off-diagonal perturbation leads to a lifting of the degeneracy in the mass spectrum. In the covariant case, not only do the spectral lines split, but they acquire an imaginary part which is lnear in the applied electric field, thus revealing induced bound state decay in first order perturbation theory. This imaginary part results from the coupling of the external field to the non-compact boost generator. In order to recover the conventional first order Stark splitting, we must include a scalar potential term. This term may be understood as a fifth gauge potential, which compensates for dependence of gauge transformat...
Hubeny, Veronika E
2014-01-01
A recently explored interesting quantity in AdS/CFT, dubbed 'residual entropy', characterizes the amount of collective ignorance associated with either boundary observers restricted to finite time duration, or bulk observers who lack access to a certain spacetime region. However, the previously-proposed expression for this quantity involving variation of boundary entanglement entropy (subsequently renamed to 'differential entropy') works only in a severely restrictive context. We explain the key limitations, arguing that in general, differential entropy does not correspond to residual entropy. Given that the concept of residual entropy as collective ignorance transcends these limitations, we identify two correspondingly robust, covariantly-defined constructs: a 'strip wedge' associated with boundary observers and a 'rim wedge' associated with bulk observers. These causal sets are well-defined in arbitrary time-dependent asymptotically AdS spacetimes in any number of dimensions. We discuss their relation, spec...
Deriving covariant holographic entanglement
Dong, Xi; Lewkowycz, Aitor; Rangamani, Mukund
2016-11-01
We provide a gravitational argument in favour of the covariant holographic entanglement entropy proposal. In general time-dependent states, the proposal asserts that the entanglement entropy of a region in the boundary field theory is given by a quarter of the area of a bulk extremal surface in Planck units. The main element of our discussion is an implementation of an appropriate Schwinger-Keldysh contour to obtain the reduced density matrix (and its powers) of a given region, as is relevant for the replica construction. We map this contour into the bulk gravitational theory, and argue that the saddle point solutions of these replica geometries lead to a consistent prescription for computing the field theory Rényi entropies. In the limiting case where the replica index is taken to unity, a local analysis suffices to show that these saddles lead to the extremal surfaces of interest. We also comment on various properties of holographic entanglement that follow from this construction.
Deriving covariant holographic entanglement
Dong, Xi; Rangamani, Mukund
2016-01-01
We provide a gravitational argument in favour of the covariant holographic entanglement entropy proposal. In general time-dependent states, the proposal asserts that the entanglement entropy of a region in the boundary field theory is given by a quarter of the area of a bulk extremal surface in Planck units. The main element of our discussion is an implementation of an appropriate Schwinger-Keldysh contour to obtain the reduced density matrix (and its powers) of a given region, as is relevant for the replica construction. We map this contour into the bulk gravitational theory, and argue that the saddle point solutions of these replica geometries lead to a consistent prescription for computing the field theory Renyi entropies. In the limiting case where the replica index is taken to unity, a local analysis suffices to show that these saddles lead to the extremal surfaces of interest. We also comment on various properties of holographic entanglement that follow from this construction.
Covariant Macroscopic Quantum Geometry
Hogan, Craig J
2012-01-01
A covariant noncommutative algebra of position operators is presented, and interpreted as the macroscopic limit of a geometry that describes a collective quantum behavior of the positions of massive bodies in a flat emergent space-time. The commutator defines a quantum-geometrical relationship between world lines that depends on their separation and relative velocity, but on no other property of the bodies, and leads to a transverse uncertainty of the geometrical wave function that increases with separation. The number of geometrical degrees of freedom in a space-time volume scales holographically, as the surface area in Planck units. Ongoing branching of the wave function causes fluctuations in transverse position, shared coherently among bodies with similar trajectories. The theory can be tested using appropriately configured Michelson interferometers.
Saltas, Ippocratis D.; Vitagliano, Vincenzo
2017-05-01
We derive the 1-loop effective action of the cubic Galileon coupled to quantum-gravitational fluctuations in a background and gauge-independent manner, employing the covariant framework of DeWitt and Vilkovisky. Although the bare action respects shift symmetry, the coupling to gravity induces an effective mass to the scalar, of the order of the cosmological constant, as a direct result of the nonflat field-space metric, the latter ensuring the field-reparametrization invariance of the formalism. Within a gauge-invariant regularization scheme, we discover novel, gravitationally induced non-Galileon higher-derivative interactions in the effective action. These terms, previously unnoticed within standard, noncovariant frameworks, are not Planck suppressed. Unless tuned to be subdominant, their presence could have important implications for the classical and quantum phenomenology of the theory.
Covariant holographic entanglement negativity
Chaturvedi, Pankaj; Sengupta, Gautam
2016-01-01
We conjecture a holographic prescription for the covariant entanglement negativity of $d$-dimensional conformal field theories dual to non static bulk $AdS_{d+1}$ gravitational configurations in the framework of the $AdS/CFT$ correspondence. Application of our conjecture to a $AdS_3/CFT_2$ scenario involving bulk rotating BTZ black holes exactly reproduces the entanglement negativity of the corresponding $(1+1)$ dimensional conformal field theories and precisely captures the distillable quantum entanglement. Interestingly our conjecture for the scenario involving dual bulk extremal rotating BTZ black holes also accurately leads to the entanglement negativity for the chiral half of the corresponding $(1+1)$ dimensional conformal field theory at zero temperature.
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 FACTORS AND ADJUSTMENT STRUCTURE
Institute of Scientific and Technical Information of China (English)
Tao Benzao
2003-01-01
In this paper, adjustment factors J and R put forward by professor Zhou Jiangwen are introduced and the nature of the adjustment factors and their role in evaluating adjustment structure is discussed and proved.
DEFF Research Database (Denmark)
M. Gaspar, Raquel; Murgoci, Agatha
2010-01-01
of particular importance to practitioners: yield convexity adjustments, forward versus futures convexity adjustments, timing and quanto convexity adjustments. We claim that the appropriate way to look into any of these adjustments is as a side effect of a measure change, as proposed by Pelsser (2003...
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.
HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.
Fan, Jianqing; Liao, Yuan; Mincheva, Martina
2011-01-01
The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.
High-dimensional covariance matrix estimation in approximate factor models
Fan, Jianqing; Mincheva, Martina; 10.1214/11-AOS944
2012-01-01
The variance--covariance matrix plays a central role in the inferential theories of high-dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu [J. Amer. Statist. Assoc. 106 (2011) 672--684], taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studi...
Covariance structure models of expectancy.
Henderson, M J; Goldman, M S; Coovert, M D; Carnevalla, N
1994-05-01
Antecedent variables under the broad categories of genetic, environmental and cultural influences have been linked to the risk for alcohol abuse. Such risk factors have not been shown to result in high correlations with alcohol consumption and leave unclear an understanding of the mechanism by which these variables lead to increased risk. This study employed covariance structure modeling to examine the mediational influence of stored information in memory about alcohol, alcohol expectancies in relation to two biologically and environmentally driven antecedent variables, family history of alcohol abuse and a sensation-seeking temperament in a college population. We also examined the effect of criterion contamination on the relationship between sensation-seeking and alcohol consumption. Results indicated that alcohol expectancy acts as a significant, partial mediator of the relationship between sensation-seeking and consumption, that family history of alcohol abuse is not related to drinking outcome and that overlap in items on sensation-seeking and alcohol consumption measures may falsely inflate their relationship.
Useful and little-known applications of the Least Square Method and some consequences of covariances
Helene, Otaviano; Mariano, Leandro; Guimarães-Filho, Zwinglio
2016-10-01
Covariances are as important as variances when dealing with experimental data and they must be considered in fitting procedures and adjustments in order to preserve the statistical properties of the adjusted quantities. In this paper, we apply the Least Square Method in matrix form to several simple problems in order to evaluate the consequences of covariances in the fitting procedure. Among the examples, we demonstrate how a measurement of a physical quantity can change the adopted value of all other covariant quantities and how a new single point (x , y) improves the parameters of a previously adjusted straight-line.
Covariant representations of subproduct systems
Viselter, Ami
2010-01-01
A celebrated theorem of Pimsner states that a covariant representation $T$ of a $C^*$-correspondence $E$ extends to a $C^*$-representation of the Toeplitz algebra of $E$ if and only if $T$ is isometric. This paper is mainly concerned with finding conditions for a covariant representation of a \\emph{subproduct system} to extend to a $C^*$-representation of the Toeplitz algebra. This framework is much more general than the former. We are able to find sufficient conditions, and show that in important special cases, they are also necessary. Further results include the universality of the tensor algebra, dilations of completely contractive covariant representations, Wold decompositions and von Neumann inequalities.
Bell, D J; Spitzer, J C; Bridges, W C; Olson, L W
1996-09-01
A retrospective analysis was conducted on data collected from 1983 through 1991, where weight and hip height were measured at start of test and every 28 d on 604 bulls completing a 224-d forage-based gain test. Scrotal circumference (SC) was measured at start of test, and at either end of test or end of the weigh period after individual bulls reached 365 d of age. Over 3 yr of this study, SC was additionally measured every 28 d. Bulls were representatives of 5 breed groups: Angus, Santa Gertrudis, Simmental, Continental (predominantly Charolais), and Zebu (predominantly Simbrah). Adjusted 365-d SC and adjusted 452-d SC were calculated by regression analysis and from formulas based on SC growth of individuals to 140 and 224 d on test, respectively. Breed group differences were observed for age of dam, birth weight, hip height, weight per day of age, average daily gain and SC at start of test, 140 d, and end of test (224 d). Scrotal circumference was positively correlated with all growth traits. Scrotal circumference was related to breed group, age, weight, hip height, average daily gain, weight per day of age, age by year, and age-by-breed group (P<0.05), as determined by regression analysis. However, omitting weight, hip height, average daily gain, and weight per day of age from the regression model did not significantly affect R2 value. Scrotal circumference growth was linear to 140 d on test; however, SC growth to 224 d on test was curvilinear. The 365-d SC predicted from the formula and from regression analysis differed for Simmental and Zebu by 0.3 and 0.4 cm, respectively (P<0.05). The 452-d SC differed for Santa Gertrudis and Zebu by 0.5 and 0.6 cm, respectively (P<0.05). Formulas based on SC growth of individuals are reasonably accurate predictors of SC at 365 and 452 d of age, when compared with more complex regression analysis. Basing SC adjustments on individual growth appears to account for variables known to affect yearling SC.
On the use of fully populated matrices in GPS least-squares adjustment
Kermarrec, Gael; Schön, Steffen
2016-04-01
The mathematical model for GNSS positioning is well described. However, the stochastic model is said to remain improvable. Indeed, heteroscedastic is mainly assumed, i.e. the variance of the observations is having an elevation dependency, typically based on 1/sin elevation models, on SNR or CN0 based values as well as elevation-based exponential models. However, correlations between satellites observations remain ignored. Over the last years, covariance functions that try to model GNSS correlations have been proposed and tested, such as the empirical exponential model or double integration of turbulence based functions. In this contribution, we will present a way to take atmospheric correlations into account based on the turbulence theory, which is a simplification of the Schön and Brunner model (2008). As a result, fully populated covariance matrices based on physically plausible results can be easily computed and integrated in least-squares adjustment. Moreover, the use of the flexible Matern covariance family allow put both to model other kind of correlations (stronger or lower) by adapting the smoothness and the correlation length factor of the covariance function. Thus the influence of fully populated matrices versus diagonal matrices on the parameter domain can be tested. By means of simulations where the covariance matrices are exactly known, it is shown that the rms-improvement of the parameters to estimate by taking correlations into account is mainly limited to submm domain, particularly for double-differenced data. The dependency of the estimates differences with the sample length and the correlation structure will be investigated. Finally, we will show that the fully populated matrices can be approximated by an equivalent diagonal kernel that facilitates taking correlations into account.
General covariance in computational electrodynamics
DEFF Research Database (Denmark)
Shyroki, Dzmitry; Lægsgaard, Jesper; Bang, Ole;
2007-01-01
We advocate the generally covariant formulation of Maxwell equations as underpinning some recent advances in computational electrodynamics—in the dimensionality reduction for separable structures; in mesh truncation for finite-difference computations; and in adaptive coordinate mapping as opposed...
Computational protein design quantifies structural constraints on amino acid covariation.
Directory of Open Access Journals (Sweden)
Noah Ollikainen
Full Text Available Amino acid covariation, where the identities of amino acids at different sequence positions are correlated, is a hallmark of naturally occurring proteins. This covariation can arise from multiple factors, including selective pressures for maintaining protein structure, requirements imposed by a specific function, or from phylogenetic sampling bias. Here we employed flexible backbone computational protein design to quantify the extent to which protein structure has constrained amino acid covariation for 40 diverse protein domains. We find significant similarities between the amino acid covariation in alignments of natural protein sequences and sequences optimized for their structures by computational protein design methods. These results indicate that the structural constraints imposed by protein architecture play a dominant role in shaping amino acid covariation and that computational protein design methods can capture these effects. We also find that the similarity between natural and designed covariation is sensitive to the magnitude and mechanism of backbone flexibility used in computational protein design. Our results thus highlight the necessity of including backbone flexibility to correctly model precise details of correlated amino acid changes and give insights into the pressures underlying these correlations.
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).
[Clinical research XIX. From clinical judgment to analysis of covariance].
Pérez-Rodríguez, Marcela; Palacios-Cruz, Lino; Moreno, Jorge; Rivas-Ruiz, Rodolfo; Talavera, Juan O
2014-01-01
The analysis of covariance (ANCOVA) is based on the general linear models. This technique involves a regression model, often multiple, in which the outcome is presented as a continuous variable, the independent variables are qualitative or are introduced into the model as dummy or dichotomous variables, and factors for which adjustment is required (covariates) can be in any measurement level (i.e. nominal, ordinal or continuous). The maneuvers can be entered into the model as 1) fixed effects, or 2) random effects. The difference between fixed effects and random effects depends on the type of information we want from the analysis of the effects. ANCOVA effect separates the independent variables from the effect of co-variables, i.e., corrects the dependent variable eliminating the influence of covariates, given that these variables change in conjunction with maneuvers or treatments, affecting the outcome variable. ANCOVA should be done only if it meets three assumptions: 1) the relationship between the covariate and the outcome is linear, 2) there is homogeneity of slopes, and 3) the covariate and the independent variable are independent from each other.
Calcul Stochastique Covariant à Sauts & Calcul Stochastique à Sauts Covariants
Maillard-Teyssier, Laurence
2003-01-01
We propose a stochastic covariant calculus forcàdlàg semimartingales in the tangent bundle $TM$ over a manifold $M$. A connection on $M$ allows us to define an intrinsic derivative ofa $C^1$ curve $(Y_t)$ in $TM$, the covariantderivative. More precisely, it is the derivative of$(Y_t)$ seen in a frame moving parallelly along its projection curve$(x_t)$ on $M$. With the transfer principle, Norris defined thestochastic covariant integration along a continuous semimartingale in$TM$. We describe t...
Covariate-free and Covariate-dependent Reliability.
Bentler, Peter M
2016-12-01
Classical test theory reliability coefficients are said to be population specific. Reliability generalization, a meta-analysis method, is the main procedure for evaluating the stability of reliability coefficients across populations. A new approach is developed to evaluate the degree of invariance of reliability coefficients to population characteristics. Factor or common variance of a reliability measure is partitioned into parts that are, and are not, influenced by control variables, resulting in a partition of reliability into a covariate-dependent and a covariate-free part. The approach can be implemented in a single sample and can be applied to a variety of reliability coefficients.
The bispectrum covariance beyond Gaussianity: A log-normal approach
Martin, Sandra; Simon, Patrick
2011-01-01
To investigate and specify the statistical properties of cosmological fields with particular attention to possible non-Gaussian features, accurate formulae for the bispectrum and the bispectrum covariance are required. The bispectrum is the lowest-order statistic providing an estimate for non-Gaussianities of a distribution, and the bispectrum covariance depicts the errors of the bispectrum measurement and their correlation on different scales. Currently, there do exist fitting formulae for the bispectrum and an analytical expression for the bispectrum covariance, but the former is not very accurate and the latter contains several intricate terms and only one of them can be readily evaluated from the power spectrum of the studied field. Neglecting all higher-order terms results in the Gaussian approximation of the bispectrum covariance. We study the range of validity of this Gaussian approximation for two-dimensional non-Gaussian random fields. For this purpose, we simulate Gaussian and non-Gaussian random fi...
Szekeres models: a covariant approach
Apostolopoulos, Pantelis S
2016-01-01
We exploit the 1+1+2 formalism to covariantly describe the inhomogeneous and anisotropic Szekeres models. It is shown that an \\emph{average scale length} can be defined \\emph{covariantly} which satisfies a 2d equation of motion driven from the \\emph{effective gravitational mass} (EGM) contained in the dust cloud. The contributions to the EGM are encoded to the energy density of the dust fluid and the free gravitational field $E_{ab}$. In addition the notions of the Apparent and Absolute Apparent Horizons are briefly discussed and we give an alternative gauge-invariant form to define them in terms of the kinematical variables of the spacelike congruences. We argue that the proposed program can be used in order to express the Sachs optical equations in a covariant form and analyze the confrontation of a spatially inhomogeneous irrotational overdense fluid model with the observational data.
Covariance evaluation work at LANL
Energy Technology Data Exchange (ETDEWEB)
Kawano, Toshihiko [Los Alamos National Laboratory; Talou, Patrick [Los Alamos National Laboratory; Young, Phillip [Los Alamos National Laboratory; Hale, Gerald [Los Alamos National Laboratory; Chadwick, M B [Los Alamos National Laboratory; Little, R C [Los Alamos National Laboratory
2008-01-01
Los Alamos evaluates covariances for nuclear data library, mainly for actinides above the resonance regions and light elements in the enUre energy range. We also develop techniques to evaluate the covariance data, like Bayesian and least-squares fitting methods, which are important to explore the uncertainty information on different types of physical quantities such as elastic scattering angular distribution, or prompt neutron fission spectra. This paper summarizes our current activities of the covariance evaluation work at LANL, including the actinide and light element data mainly for the criticality safety study and transmutation technology. The Bayesian method based on the Kalman filter technique, which combines uncertainties in the theoretical model and experimental data, is discussed.
Marital, reproductive, and educational behaviors covary with life expectancy.
Krupp, Daniel Brian
2012-12-01
Theories of "life history evolution" suggest that individuals might adjust the timing of marriage and reproduction, as well as their propensity to terminate a marriage or pregnancy and invest in skill development, in response to indicators of the locally prevailing level of life expectancy. In particular, such theories generate the hypothesis that foreshortened time horizons lead to hastened reproduction and marriage whereas lengthier time horizons increase the likelihood of reproductive and marital termination and lead to greater investment in education. Here, I show that the scheduling and occurrence of marital and reproductive behavior (including both initiation and termination), as well as levels of educational attainment and investment, covary with life expectancy, even after controlling for the effects of affluence. In analyses of variation in marital, reproductive, and educational behaviors at two jurisdictional levels in Canada, life expectancy was positively correlated with patterns of age-specific fertility, age at first marriage, divorce, abortion, conferral of high school and higher education degrees (with the exception of the trades) and mean number of years of schooling. The large and highly consistent relationships observed between life expectancy and the behaviors under investigation suggest that these associations may be mediated by individual "perceptions" of life expectancy, though more research is needed before conclusions can be firmly reached.
Cosmic Censorship Conjecture revisited: Covariantly
Hamid, Aymen I M; Maharaj, Sunil D
2014-01-01
In this paper we study the dynamics of the trapped region using a frame independent semi-tetrad covariant formalism for general Locally Rotationally Symmetric (LRS) class II spacetimes. We covariantly prove some important geometrical results for the apparent horizon, and state the necessary and sufficient conditions for a singularity to be locally naked. These conditions bring out, for the first time in a quantitative and transparent manner, the importance of the Weyl curvature in deforming and delaying the trapped region during continual gravitational collapse, making the central singularity locally visible.
On the Estimation of Integrated Covariance Matrices of High Dimensional Diffusion Processes
Zheng, Xinghua
2010-01-01
We consider the estimation of integrated covariance matrices of high dimensional diffusion processes by using high frequency data. We start by studying the most commonly used estimator, the realized covariance matrix (RCV). We show that in the high dimensional case when the dimension p and the observation frequency n grow in the same rate, the limiting empirical spectral distribution of RCV depends on the covolatility processes not only through the underlying integrated covariance matrix Sigma, but also on how the covolatility processes vary in time. In particular, for two high dimensional diffusion processes with the same integrated covariance matrix, the empirical spectral distributions of their RCVs can be very different. Hence in terms of making inference about the spectrum of the integrated covariance matrix, the RCV is in general \\emph{not} a good proxy to rely on in the high dimensional case. We then propose an alternative estimator, the time-variation adjusted realized covariance matrix (TVARCV), for ...
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.
... syndrome) A certain type of stroke (vertebral artery dissection) after neck manipulation Don't seek chiropractic adjustment ... Chiropractic treatment. Rochester, Minn.: Mayo Foundation for Medical Education and Research; 2015. Shekelle P, et al. Spinal ...
Institute of Scientific and Technical Information of China (English)
Shun-long Luo; You-feng Luo
2003-01-01
In quantum mechanics, it is long recognized that there exist correlations between observables which are much stronger than the classical ones. These correlations are usually called entanglement, and cannot be accounted for by classical theory. In this paper, we will study correlations between observables in terms of covariance and the Wigner-Yanase correlation, and compare their merits in characterizing entanglement. We will show that the Wigner-Yanase correlation has some advantages over the conventional covariance.
Covariant description of isothermic surfaces
Tafel, Jacek
2014-01-01
We present a covariant formulation of the Gauss-Weingarten equations and the Gauss-Mainardi-Codazzi equations for surfaces in 3-dimensional curved spaces. We derive a coordinate invariant condition on the first and second fundamental form which is necessary and sufficient for the surface to be isothermic.
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
Covariation Neglect among Novice Investors
Hedesstrom, Ted Martin; Svedsater, Henrik; Garling, Tommy
2006-01-01
In 4 experiments, undergraduates made hypothetical investment choices. In Experiment 1, participants paid more attention to the volatility of individual assets than to the volatility of aggregated portfolios. The results of Experiment 2 show that most participants diversified even when this increased risk because of covariation between the returns…
Toth, Georgina Zsofia; Racz, Adel; Tarnoki, Adam Domonkos; Tarnoki, David Laszlo; Szekelyhidi, Zita; Littvay, Levente; Suveges, Ildiko; Nemeth, Janos; Nagy, Zoltan Zsolt
2014-10-01
Few, and inconsistent, studies have showed high heritability of some parameters of the anterior segment of the eye; however, no heritability of anterior chamber volume (ACV) has been reported, and no study has been performed to investigate the correlation between the ACV and central corneal thickness (CCT). Anterior segment measurements (Pentacam, Oculus) were obtained from 220 eyes of 110 adult Hungarian twins (41 monozygotic and 14 same-sex dizygotic pairs; 80% women; age 48.6 ± 15.5 years) obtained from the Hungarian Twin Registry. Age- and sex-adjusted heritability of ACV was 85% (bootstrapped 95% confidence interval; CI: 69% to 93%), and 88% for CCT (CI: 79% to 95%). Common environmental effects had no influence, and unshared environmental factors were responsible for 12% and 15% of the variance, respectively. The correlation between ACV and CCT was negative and significant (r ph = -0.35, p covariance significantly (0.934; CI: 0.418, 1.061) based on the bivariate Cholesky decomposition model. These findings support the high heritability of ACV and central corneal thickness, and a strong genetic covariance between them, which underscores the importance of identification of the specific genetic factors and the family risk-based screening of disorders related to these variables, such as open-angle and also angle closure glaucoma and corneal endothelial alterations.
Covariant Formulations of Superstring Theories.
Mikovic, Aleksandar Radomir
1990-01-01
Chapter 1 contains a brief introduction to the subject of string theory, and tries to motivate the study of superstrings and covariant formulations. Chapter 2 describes the Green-Schwarz formulation of the superstrings. The Hamiltonian and BRST structure of the theory is analysed in the case of the superparticle. Implications for the superstring case are discussed. Chapter 3 describes the Siegel's formulation of the superstring, which contains only the first class constraints. It is shown that the physical spectrum coincides with that of the Green-Schwarz formulation. In chapter 4 we analyse the BRST structure of the Siegel's formulation. We show that the BRST charge has the wrong cohomology, and propose a modification, called first ilk, which gives the right cohomology. We also propose another superparticle model, called second ilk, which has infinitely many coordinates and constraints. We construct the complete BRST charge for it, and show that it gives the correct cohomology. In chapter 5 we analyse the properties of the covariant vertex operators and the corresponding S-matrix elements by using the Siegel's formulation. We conclude that the knowledge of the ghosts is necessary, even at the tree level, in order to obtain the correct S-matrix. In chapter 6 we attempt to calculate the superstring loops, in a covariant gauge. We calculate the vacuum-to -vacuum amplitude, which is also the cosmological constant. We show that it vanishes to all loop orders, under the assumption that the free covariant gauge-fixed action exists. In chapter 7 we present our conclusions, and briefly discuss the random lattice approach to the string theory, as a possible way of resolving the problem of the covariant quantization and the nonperturbative definition of the superstrings.
Variance and covariance of accumulated displacement estimates.
Bayer, Matthew; Hall, Timothy J
2013-04-01
Tracking large deformations in tissue using ultrasound can enable the reconstruction of nonlinear elastic parameters, but poses a challenge to displacement estimation algorithms. Such large deformations have to be broken up into steps, each of which contributes an estimation error to the final accumulated displacement map. The work reported here measured the error variance for single-step and accumulated displacement estimates using one-dimensional numerical simulations of ultrasound echo signals, subjected to tissue strain and electronic noise. The covariance between accumulation steps was also computed. These simulations show that errors due to electronic noise are negatively correlated between steps, and therefore accumulate slowly, whereas errors due to tissue deformation are positively correlated and accumulate quickly. For reasonably low electronic noise levels, the error variance in the accumulated displacement estimates is remarkably constant as a function of step size, but increases with the length of the tracking kernel.
Full covariance of CMB and lensing reconstruction power spectra
Peloton, Julien; Lewis, Antony; Carron, Julien; Zahn, Oliver
2016-01-01
CMB and lensing reconstruction power spectra are powerful probes of cosmology. However they are correlated, since the CMB power spectra are lensed and the lensing reconstruction is constructed using CMB multipoles. We perform a full analysis of the auto- and cross-covariances, including polarization power spectra and minimum variance lensing estimators, and compare with simulations of idealized future CMB-S4 observations. Covariances sourced by fluctuations in the unlensed CMB and instrumental noise can largely be removed by using a realization-dependent subtraction of lensing reconstruction noise, leaving a relatively simple covariance model that is dominated by lensing-induced terms and well described by a small number of principal components. The correlations between the CMB and lensing power spectra will be detectable at the level of $\\sim 5\\sigma$ for a CMB-S4 mission, and neglecting those could underestimate some parameter error bars by several tens of percent. However we found that the inclusion of ext...
Galaxy-galaxy lensing estimators and their covariance properties
Singh, Sukhdeep; Seljak, Uroš; Slosar, Anže; Gonzalez, Jose Vazquez
2016-01-01
We study the covariance properties of real space correlation function estimators -- primarily galaxy-shear correlations, or galaxy-galaxy lensing -- using SDSS data for both shear catalogs and lenses (specifically the BOSS LOWZ sample). Using mock catalogs of lenses and sources, we disentangle the various contributions to the covariance matrix and compare them with a simple analytical model. We show that not subtracting the lensing measurement around random points from the measurement around the lens sample is equivalent to performing the measurement using the density field instead of the over-density field, and that this leads to a significant error increase due to an additional term in the covariance. Therefore, this subtraction should be performed regardless of its beneficial effects on systematics. Comparing the error estimates from data and mocks for estimators that involve the over-density, we find that the errors are dominated by the shape noise and lens clustering, that empirically estimated covarianc...
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.
Estimating the generalized concordance correlation coefficient through variance components.
Carrasco, Josep L; Jover, Lluís
2003-12-01
The intraclass correlation coefficient (ICC) and the concordance correlation coefficient (CCC) are two of the most popular measures of agreement for variables measured on a continuous scale. Here, we demonstrate that ICC and CCC are the same measure of agreement estimated in two ways: by the variance components procedure and by the moment method. We propose estimating the CCC using variance components of a mixed effects model, instead of the common method of moments. With the variance components approach, the CCC can easily be extended to more than two observers, and adjusted using confounding covariates, by incorporating them in the mixed model. A simulation study is carried out to compare the variance components approach with the moment method. The importance of adjusting by confounding covariates is illustrated with a case example.
Structural covariance of the neostriatum with regional gray matter volumes.
Soriano-Mas, C; Harrison, B J; Pujol, J; López-Solà, M; Hernández-Ribas, R; Alonso, P; Contreras-Rodríguez, O; Giménez, M; Blanco-Hinojo, L; Ortiz, H; Deus, J; Menchón, J M; Cardoner, N
2013-05-01
The caudate and putamen nuclei have been traditionally divided into dorsal and ventral territories based on their segregated patterns of functional and anatomical connectivity with distributed cortical regions. Activity-dependent structural plasticity may potentially lead to the development of regional volume correlations, or structural covariance, between the different components of each cortico-striatal circuit. Here, we studied the whole-brain structural covariance patterns of four neostriatal regions belonging to distinct cortico-striatal circuits. We also assessed the potential modulating influence of laterality, age and gender. T1-weighted three-dimensional magnetic resonance images were obtained from ninety healthy participants (50 females). Following data pre-processing, the mean signal value per hemisphere was calculated for the 'seed' regions of interest, located in the dorsal and ventral caudate and the dorsal-caudal and ventral-rostral putamen. Statistical parametric mapping was used to estimate whole-brain voxel-wise structural covariance patterns for each striatal region, controlling for the shared anatomical variance between regions in order to obtain maximally specific structural covariance patterns. As predicted, segregated covariance patterns were observed. Age was found to be a relevant modulator of the covariance patterns of the right caudate regions, while laterality effects were observed for the dorsal-caudal putamen. Gender effects were only observed via an interaction with age. The different patterns of structural covariance are discussed in detail, as well as their similarities with the functional and anatomical connectivity patterns reported for the same striatal regions in other studies. Finally, the potential mechanisms underpinning the phenomenon of volume correlations between distant cortico-striatal structures are also discussed.
Covariation of spectral and nonlinear EEG measures with alpha biofeedback.
Fell, J.; Elfadil, H.; Klaver, P.; Roschke, J.; Elger, C.E.; Fernandez, G.S.E.
2002-01-01
This study investigated how different spectral and nonlinear EEG measures covaried with alpha power during auditory alpha biofeedback training, performed by 13 healthy subjects. We found a significant positive correlation of alpha power with the largest Lyapunov-exponent, pointing to an increased
Discrete Symmetries in Covariant LQG
Rovelli, Carlo
2012-01-01
We study time-reversal and parity ---on the physical manifold and in internal space--- in covariant loop gravity. We consider a minor modification of the Holst action which makes it transform coherently under such transformations. The classical theory is not affected but the quantum theory is slightly different. In particular, the simplicity constraints are slightly modified and this restricts orientation flips in a spinfoam to occur only across degenerate regions, thus reducing the sources of potential divergences.
Murray, Christopher; Zvoch, Keith
2011-01-01
This investigation examines teacher-student relationships among African American youth from low-income backgrounds (N = 193). Students and their teachers completed measures of teacher-student relationship quality and measures pertaining to emotional, behavioral, and school-related adjustment. Results indicated that African American youth who fell…
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...
Neutron Cross Section Covariances for Structural Materials and Fission Products
Hoblit, S.; Cho, Y.-S.; Herman, M.; Mattoon, C. M.; Mughabghab, S. F.; Obložinský, P.; Pigni, M. T.; Sonzogni, A. A.
2011-12-01
We describe neutron cross section covariances for 78 structural materials and fission products produced for the new US evaluated nuclear reaction library ENDF/B-VII.1. Neutron incident energies cover full range from 10 eV to 20 MeV and covariances are primarily provided for capture, elastic and inelastic scattering as well as (n,2n). The list of materials follows priorities defined by the Advanced Fuel Cycle Initiative, the major application being data adjustment for advanced fast reactor systems. Thus, in addition to 28 structural materials and 49 fission products, the list includes also 23Na which is important fast reactor coolant. Due to extensive amount of materials, we adopted a variety of methodologies depending on the priority of a specific material. In the resolved resonance region we primarily used resonance parameter uncertainties given in Atlas of Neutron Resonances and either applied the kernel approximation to propagate these uncertainties into cross section uncertainties or resorted to simplified estimates based on integral quantities. For several priority materials we adopted MF32 covariances produced by SAMMY at ORNL, modified by us by adding MF33 covariances to account for systematic uncertainties. In the fast neutron region we resorted to three methods. The most sophisticated was EMPIRE-KALMAN method which combines experimental data from EXFOR library with nuclear reaction modeling and least-squares fitting. The two other methods used simplified estimates, either based on the propagation of nuclear reaction model parameter uncertainties or on a dispersion analysis of central cross section values in recent evaluated data files. All covariances were subject to quality assurance procedures adopted recently by CSEWG. In addition, tools were developed to allow inspection of processed covariances and computed integral quantities, and for comparing these values to data from the Atlas and the astrophysics database KADoNiS.
Neutron Cross Section Covariances for Structural Materials and Fission Products
Energy Technology Data Exchange (ETDEWEB)
Hoblit, S.; Hoblit,S.; Cho,Y.-S.; Herman,M.; Mattoon,C.M.; Mughabghab,S.F.; Oblozinsky,P.; Pigni,M.T.; Sonzogni,A.A.
2011-12-01
We describe neutron cross section covariances for 78 structural materials and fission products produced for the new US evaluated nuclear reaction library ENDF/B-VII.1. Neutron incident energies cover full range from 10{sup -5} eV to 20 MeV and covariances are primarily provided for capture, elastic and inelastic scattering as well as (n,2n). The list of materials follows priorities defined by the Advanced Fuel Cycle Initiative, the major application being data adjustment for advanced fast reactor systems. Thus, in addition to 28 structural materials and 49 fission products, the list includes also {sup 23}Na which is important fast reactor coolant. Due to extensive amount of materials, we adopted a variety of methodologies depending on the priority of a specific material. In the resolved resonance region we primarily used resonance parameter uncertainties given in Atlas of Neutron Resonances and either applied the kernel approximation to propagate these uncertainties into cross section uncertainties or resorted to simplified estimates based on integral quantities. For several priority materials we adopted MF32 covariances produced by SAMMY at ORNL, modified by us by adding MF33 covariances to account for systematic uncertainties. In the fast neutron region we resorted to three methods. The most sophisticated was EMPIRE-KALMAN method which combines experimental data from EXFOR library with nuclear reaction modeling and least-squares fitting. The two other methods used simplified estimates, either based on the propagation of nuclear reaction model parameter uncertainties or on a dispersion analysis of central cross section values in recent evaluated data files. All covariances were subject to quality assurance procedures adopted recently by CSEWG. In addition, tools were developed to allow inspection of processed covariances and computed integral quantities, and for comparing these values to data from the Atlas and the astrophysics database KADoNiS.
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
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
Afanasjev, A V
2015-01-01
The assessment of the global performance of the state-of-the-art covariant energy density functionals and related theoretical uncertainties in the description of ground state observables has recently been performed. Based on these results, the correlations between global description of binding energies and nuclear matter properties of covariant energy density functionals have been studied in this contribution.
Spatiotemporal noise covariance model for MEG/EEG data source analysis
Plis, S M; Jun, S C; Pare-Blagoev, J; Ranken, D M; Schmidt, D M; Wood, C C
2005-01-01
A new method for approximating spatiotemporal noise covariance for use in MEG/EEG source analysis is proposed. Our proposed approach extends a parameterized one pair approximation consisting of a Kronecker product of a temporal covariance and a spatial covariance into 1) an unparameterized one pair approximation and then 2) into a multi-pair approximation. These models are motivated by the need to better describe correlated background and make estimation of these models more efficient. The effects of these different noise covariance models are compared using a multi-dipole inverse algorithm and simulated data consisting of empirical MEG background data as noise and simulated dipole sources.
EMPIRE ULTIMATE EXPANSION: RESONANCES AND COVARIANCES.
Energy Technology Data Exchange (ETDEWEB)
HERMAN,M.; MUGHABGHAB, S.F.; OBLOZINSKY, P.; ROCHMAN, D.; PIGNI, M.T.; KAWANO, T.; CAPOTE, R.; ZERKIN, V.; TRKOV, A.; SIN, M.; CARSON, B.V.; WIENKE, H. CHO, Y.-S.
2007-04-22
The EMPIRE code system is being extended to cover the resolved and unresolved resonance region employing proven methodology used for the production of new evaluations in the recent Atlas of Neutron Resonances. Another directions of Empire expansion are uncertainties and correlations among them. These include covariances for cross sections as well as for model parameters. In this presentation we concentrate on the KALMAN method that has been applied in EMPIRE to the fast neutron range as well as to the resonance region. We also summarize role of the EMPIRE code in the ENDF/B-VII.0 development. Finally, large scale calculations and their impact on nuclear model parameters are discussed along with the exciting perspectives offered by the parallel supercomputing.
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.
Residual noise covariance for Planck low-resolution data analysis
Keskitalo, R; Cabella, P; Kisner, T; Poutanen, T; Stompor, R; Bartlett, J G; Borrill, J; Cantalupo, C; De Gasperis, G; De Rosa, A; de Troia, G; Eriksen, H K; Finelli, F; Górski, K M; Gruppuso, A; Hivon, E; Jaffe, A; Keihanen, E; Kurki-Suonio, H; Lawrence, C R; Natoli, P; Paci, F; Polenta, G; Rocha, G
2009-01-01
Aims: Develop and validate tools to estimate residual noise covariance in Planck frequency maps. Quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derive analytical estimates of covariance of the residual noise contained in low-resolution maps produced using a number of map-making approaches. We test these analytical predictions using Monte Carlo simulations and their impact on angular power spectrum estimation. We use simulations to quantify the level of signal errors incurred in different resolution downgrading schemes considered in this work. Results: We find an excellent agreement between the optimal residual noise covariance matrices and Monte Carlo noise maps. For destriping map-makers, the extent of agreement is dictated by the knee frequency of the correlated noise component and the chosen baseline offset length. The significance of signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that...
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.
Institute of Scientific and Technical Information of China (English)
ZHENG Xiaogu; WU Guocan; ZHANG Shupeng; LIANG Xiao; DAI Yongjiu; LI Yong
2013-01-01
Correctly estimating the forecast error covariance matrix is a key step in any data assimilation scheme.If it is not correctly estimated,the assimilated states could be far from the true states.A popular method to address this problem is error covariance matrix inflation.That is,to multiply the forecast error covariance matrix by an appropriate factor.In this paper,analysis states are used to construct the forecast error covariance matrix and an adaptive estimation procedure associated with the error covariance matrix inflation technique is developed.The proposed assimilation scheme was tested on the Lorenz-96 model and 2D Shallow Water Equation model,both of which are associated with spatially correlated observational systems.The experiments showed that by introducing the proposed structure of the forecast error covariance matrix and applying its adaptive estimation procedure,the assimilation results were further improved.
Covariance matrices for use in criticality safety predictability studies
Energy Technology Data Exchange (ETDEWEB)
Derrien, H.; Larson, N.M.; Leal, L.C.
1997-09-01
Criticality predictability applications require as input the best available information on fissile and other nuclides. In recent years important work has been performed in the analysis of neutron transmission and cross-section data for fissile nuclei in the resonance region by using the computer code SAMMY. The code uses Bayes method (a form of generalized least squares) for sequential analyses of several sets of experimental data. Values for Reich-Moore resonance parameters, their covariances, and the derivatives with respect to the adjusted parameters (data sensitivities) are obtained. In general, the parameter file contains several thousand values and the dimension of the covariance matrices is correspondingly large. These matrices are not reported in the current evaluated data files due to their large dimensions and to the inadequacy of the file formats. The present work has two goals: the first is to calculate the covariances of group-averaged cross sections from the covariance files generated by SAMMY, because these can be more readily utilized in criticality predictability calculations. The second goal is to propose a more practical interface between SAMMY and the evaluated files. Examples are given for {sup 235}U in the popular 199- and 238-group structures, using the latest ORNL evaluation of the {sup 235}U resonance parameters.
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
Covariances for Gamma Spectrometer Efficiency Calibrations
Directory of Open Access Journals (Sweden)
Williams John G.
2016-01-01
Full Text Available An essential part of the efficiency calibration of gamma spectrometers is the determination of uncertainties on the results. Although this is routinely done, it often does not include the correlations between efficiencies at different energies. These can be important in the subsequent use of the detectors to obtain activities for a set of dosimetry reactions. If those values are not mutually independent, then obviously that fact could impact the validity of adjustments or of other conclusions resulting from the analysis. Examples are given of detector calibrations in which the correlations are calculated and propagated through an analysis of measured activities.
Meta-Analysis With a Continuous Covariate That Is Differentially Categorized Across Studies.
Perin, Jamie; Fischer Walker, Christa L; Black, Robert E; Aryee, Martin J
2016-03-01
We propose taking advantage of methodology for missing data to estimate relationships and adjust outcomes in a meta-analysis where a continuous covariate is differentially categorized across studies. The proposed method incorporates all available data in an implementation of the expectation-maximization algorithm. We use simulations to demonstrate that the proposed method eliminates bias that would arise by ignoring a covariate and generalizes the meta-analytical approach for incorporating covariates that are not uniformly categorized. The proposed method is illustrated in an application for estimating diarrhea incidence in children aged ≤59 months.
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.
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.; Busatto, Geraldo F.; Cath, Danielle C.; Denys, Damiaan; Fukui, Kenji; Fouche, Jean Paul; Jang, Joon Hwan; Kim, Sung Nyun; Miguel, Euripides C.; Nishida, Seiji; Phillips, Mary L.; Remijnse, Peter L.; Sakai, Yuki; Schweren, Lizanne; Shin, Na Young; Yamada, Kei; Menchón, José M.; Van Den Heuvel, Odile A.; Soriano-Mas, Carles
2016-01-01
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
Directory of Open Access Journals (Sweden)
Aline Magri
2007-12-01
Full Text Available OBJETIVO: avaliar os correlatos perceptivo-auditivos (ajustes supraglóticos e acústicos (formantes da qualidade vocal de indivíduos disfônicos com alterações glóticas, atendidos em ambulatório de fonoaudiologia de uma instituição hospitalar da cidade de São Paulo. MÉTODOS: o grupo estudado foi representado por amostras de voz de 20 indivíduos disfônicos com idades variadas entre 30 e 65 anos do sexo feminino (atendidos em um hospital da cidade de São Paulo e julgamentos perceptivo-auditivos da qualidade vocal por amostras avaliadas previamente por um grupo de juízes em atividade clínica. As amostras foram exploradas quanto à freqüência dos três primeiros formantes (F1, F2 e F3. Os valores foram considerados de forma qualitativa (comparados aos dados da análise perceptivo-auditiva e quantitativa (teste Qui-quadrado. RESULTADOS: os ajustes de qualidade vocal mais freqüentes foram laringe baixa, mandíbula fechada, lábios arredondados, corpo de língua abaixado, corpo de língua retraído, labiodentalização. Diferenças estatisticamente significantes foram encontradas para os valores de freqüência de F1 para os vocábulos "cata" (864 Hz e "gata" (814 Hz, p=0 e F3 para os vocábulos "cata" (2598 Hz e "gata" (2660 Hz, p=0,17 dos indivíduos do grupo estudado em relação aos valores de referência para o Português-Brasileiro. CONCLUSÃO: os ajustes de qualidade vocal identificados encontraram correspondência com a diminuição dos valores de F1 e F3 indicando tendências de ajustes do trato vocal.PURPOSE: to evaluate auditory perception (supraglottic adjustments and acoustic (formants of vocal quality in dysphonic individuals with glotic disorders, attended in a clinic a hospital in the city of São Paulo. METHODS: the studied was represented by voice samples taken form from 20 dysphonic people aged between 30 and 65 of the female gender (attended in a hospital in the city of Sao Paulo and the auditory perception
Covariant diagrams for one-loop matching
Zhang, Zhengkang
2016-01-01
We present a diagrammatic formulation of recently-revived covariant functional approaches to one-loop matching from an ultraviolet (UV) theory to a low-energy effective field theory. Various terms following from a covariant derivative expansion (CDE) are represented by diagrams which, unlike conventional Feynman diagrams, involve gauge-covariant quantities and are thus dubbed "covariant diagrams." The use of covariant diagrams helps organize and simplify one-loop matching calculations, which we illustrate with examples. Of particular interest is the derivation of UV model-independent universal results, which reduce matching calculations of specific UV models to applications of master formulas. We show how such derivation can be done in a more concise manner than the previous literature, and discuss how additional structures that are not directly captured by existing universal results, including mixed heavy-light loops, open covariant derivatives, and mixed statistics, can be easily accounted for.
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.
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.
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 are obtai......The linear regression model is widely used in empirical work in Economics. Researchers often include many covariates in their linear model specification in an attempt to control for confounders. We give inference methods that allow for many covariates and heteroskedasticity. Our results...... then propose a new heteroskedasticity consistent standard error formula that is fully automatic and robust to both (conditional) heteroskedasticity of unknown form and the inclusion of possibly many covariates. We apply our findings to three settings: (i) parametric linear models with many covariates, (ii...
A synthetic covariance matrix for monitoring by terrestrial laser scanning
Kauker, Stephanie; Schwieger, Volker
2017-06-01
Modelling correlations within laser scanning point clouds can be achieved by using synthetic covariance matrices. These are based on the elementary error model which contains different groups of correlations: non-correlating, functional correlating and stochastic correlating. By applying the elementary error model on terrestrial laser scanning several groups of error sources should be considered: instrumental, atmospheric and object based. This contribution presents calculations for the Leica HDS 7000. The determined variances and the spatial correlations of the points are estimated and discussed. Hereby, the mean standard deviation of the point cloud is up to 0.6 mm and the mean correlation is about 0.6 with respect to 5 m scanning range. The change of these numerical values compared to previous publications as Kauker and Schwieger [17] is mainly caused by the complete consideration of the object related error sources.
Energy Technology Data Exchange (ETDEWEB)
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.
Eigenvalue variance bounds for covariance matrices
Dallaporta, Sandrine
2013-01-01
This work is concerned with finite range bounds on the variance of individual eigenvalues of random covariance matrices, both in the bulk and at the edge of the spectrum. In a preceding paper, the author established analogous results for Wigner matrices and stated the results for covariance matrices. They are proved in the present paper. Relying on the LUE example, which needs to be investigated first, the main bounds are extended to complex covariance matrices by means of the Tao, Vu and Wan...
CMB lens sample covariance and consistency relations
Motloch, Pavel; Hu, Wayne; Benoit-Lévy, Aurélien
2017-02-01
Gravitational lensing information from the two and higher point statistics of the cosmic microwave background (CMB) temperature and polarization fields are intrinsically correlated because they are lensed by the same realization of structure between last scattering and observation. Using an analytic model for lens sample covariance, we show that there is one mode, separately measurable in the lensed CMB power spectra and lensing reconstruction, that carries most of this correlation. Once these measurements become lens sample variance dominated, this mode should provide a useful consistency check between the observables that is largely free of sampling and cosmological parameter errors. Violations of consistency could indicate systematic errors in the data and lens reconstruction or new physics at last scattering, any of which could bias cosmological inferences and delensing for gravitational waves. A second mode provides a weaker consistency check for a spatially flat universe. Our analysis isolates the additional information supplied by lensing in a model-independent manner but is also useful for understanding and forecasting CMB cosmological parameter errors in the extended Λ cold dark matter parameter space of dark energy, curvature, and massive neutrinos. We introduce and test a simple but accurate forecasting technique for this purpose that neither double counts lensing information nor neglects lensing in the observables.
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.
Multigroup covariance matrices for fast-reactor studies
Energy Technology Data Exchange (ETDEWEB)
Smith, J.D. III; Broadhead, B.L.
1981-04-01
This report presents the multigroup covariance matrices based on the ENDF/B-V nuclear data evaluations. The materials and reactions have been chosen according to the specifications of ORNL-5517. Several cross section covariances, other than those specified by that report, are included due to the derived nature of the uncertainty files in ENDF/B-V. The materials represented are Ni, Cr, /sup 16/O, /sup 12/C, Fe, Na, /sup 235/U, /sup 238/U, /sup 239/Pu, /sup 240/Pu, /sup 241/Pu, and /sup 10/B (present due to its correlation to /sup 238/U). The data have been originally processed into a 52-group energy structure by PUFF-II and subsequently collapsed to smaller subgroup strutures. The results are illustrated in 52-group correlation matrix plots and tabulated into thirteen groups for convenience.
Residual noise covariance for Planck low-resolution data analysis
Keskitalo, R.; Ashdown, M. A. J.; Cabella, P.; Kisner, T.; Poutanen, T.; Stompor, R.; Bartlett, J. G.; Borrill, J.; Cantalupo, C.; de Gasperis, G.; de Rosa, A.; de Troia, G.; Eriksen, H. K.; Finelli, F.; Górski, K. M.; Gruppuso, A.; Hivon, E.; Jaffe, A.; Keihänen, E.; Kurki-Suonio, H.; Lawrence, C. R.; Natoli, P.; Paci, F.; Polenta, G.; Rocha, G.
2010-11-01
Aims: We develop and validate tools for estimating residual noise covariance in Planck frequency maps, we also quantify signal error effects and compare different techniques to produce low-resolution maps. Methods: We derived analytical estimates of covariance of the residual noise contained in low-resolution maps produced using a number of mapmaking approaches. We tested these analytical predictions using both Monte Carlo simulations and by applying them to angular power spectrum estimation. We used simulations to quantify the level of signal errors incurred in the different resolution downgrading schemes considered in this work. Results: We find excellent agreement between the optimal residual noise covariance matrices and Monte Carlo noise maps. For destriping mapmakers, the extent of agreement is dictated by the knee frequency of the correlated noise component and the chosen baseline offset length. Signal striping is shown to be insignificant when properly dealt with. In map resolution downgrading, we find that a carefully selected window function is required to reduce aliasing to the subpercent level at multipoles, ℓ > 2Nside, where Nside is the HEALPix resolution parameter. We show that, for a polarization measurement, reliable characterization of the residual noise is required to draw reliable constraints on large-scale anisotropy. Conclusions: Methods presented and tested in this paper allow for production of low-resolution maps with both controlled sky signal error level and a reliable estimate of covariance of the residual noise. We have also presented a method for smoothing the residual noise covariance matrices to describe the noise correlations in smoothed, bandwidth-limited maps.
Institute of Scientific and Technical Information of China (English)
2015-01-01
针对经典高分辨波达方位(DOA)估计方法在低信噪比下分辨性能较差的问题，该文提出一种适用于主动探测系统的基于互相关矩阵的改进多重信号分类(MUSIC)高分辨方位估计方法(I-MUSIC)。该方法首先利用主动声呐发射信号已知的特性，将发射信号与阵元接收信号进行互相关，利用互相关序列形成新的空域协方差矩阵，再进行特征分解。理论分析表明，互相关处理在抑制噪声的同时保留了阵元之间的相位信息，可以得到比MUSIC方法更准确的子空间划分，进而提高低信噪比方位估计性能。在此基础上，提出一种基于相关时间门限的改进MUSIC高分辨方位估计(T-MUSIC)方法，通过对互相关序列设置时间门限进一步提高方位估计信噪比。仿真结果表明，与MUSIC方法相比，I-MUSIC与T-MUSIC可以分别使低信噪比时的估计性能提高3 dB和6 dB，相应平均估计误差分别为原方法的77%和53%。在阵元间接收噪声存在相关性时，T-MUSIC与I-MUSIC方法相比可获得8 dB的估计增益，估计性能更优。I-MUSIC 与 T-MUSIC 应用于多目标主动探测，可大幅提高探测系统在低信噪比下的方位估计性能。%In view of the poor performance of traditional Direction of Arrival (DOA) methods at low signal-to-noise ratios, an improved MUltiple SIgnal Classification (MUSIC) algorithm for DOA estimation applied to active detection system based on covariance matrix decomposition of cross-correlation (I-MUSIC) is proposed. Exploiting the transmission feature of active sonar, cross-correlation sequence between the transmitted signal and the array output is formulated. The spatial covariance matrix is then constructed from the sequence. Then matrix decomposition is implemented over the new spatial covariance matrix to estimate the DOA. It is proved that cross-correlation can suppress noise while preserving the phase information between array
Treatment of Nuclear Data Covariance Information in Sample Generation.
Energy Technology Data Exchange (ETDEWEB)
Swiler, Laura Painton; Adams, Brian M.; Wieselquist, William (ORNL)
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.
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...
Adjustment Criteria in Causal Diagrams: An Algorithmic Perspective
Textor, Johannes
2012-01-01
Identifying and controlling bias is a key problem in empirical sciences. Causal diagram theory provides graphical criteria for deciding whether and how causal effects can be identified from observed (nonexperimental) data by covariate adjustment. Here we prove equivalences between existing as well as new criteria for adjustment and we provide a new simplified but still equivalent notion of d-separation. These lead to efficient algorithms for two important tasks in causal diagram analysis: (1) listing minimal covariate adjustments (with polynomial delay); and (2) identifying the subdiagram involved in biasing paths (in linear time). Our results improve upon existing exponential-time solutions for these problems, enabling users to assess the effects of covariate adjustment on diagrams with tens to hundreds of variables interactively in real time.
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`
Full covariance of CMB and lensing reconstruction power spectra
Peloton, Julien; Schmittfull, Marcel; Lewis, Antony; Carron, Julien; Zahn, Oliver
2017-02-01
CMB and lensing reconstruction power spectra are powerful probes of cosmology. However, they are correlated, since the CMB power spectra are lensed, and the lensing reconstruction is constructed using CMB multipoles. We perform a full analysis of the auto- and cross-covariances, including polarization power spectra and minimum-variance lensing estimators, and compare with simulations of idealized future CMB-S4 observations. Covariances sourced by fluctuations in the unlensed CMB and instrumental noise can largely be removed by using a realization-dependent subtraction of lensing reconstruction noise, leaving a relatively simple covariance model that is dominated by lensing-induced terms and well described by a small number of principal components. The correlations between the CMB and lensing power spectra will be detectable at the level of ˜5 σ for a CMB-S4 mission, and neglecting them could underestimate some parameter error bars by several tens of percent. However, we found that the inclusion of external priors or data sets to estimate parameter error bars can make the impact of the correlations almost negligible.
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.
Institute of Scientific and Technical Information of China (English)
邓桂英; 王文兰; 欧阳结颜; 关纪红
2014-01-01
目的：探讨不孕不育症患者婚姻调适状况及其与人格特征的相关性。方法采用Locke-Wollance婚姻调适测定量表和艾森克人格问卷（Eysenck personality questionnaire，EPQ），对156例不孕不育症已婚患者进行问卷调查。了解患者婚姻调适状况及其与人格特征的相关性。结果156例不孕不育症患者婚姻调适总分为（100.7±15.5）分，其中婚姻调适良好为51.3%，婚姻失调为48.7%；婚龄≤5年组较婚龄＞5年组患者婚姻调适好（P＜0.01）。在人格特征中精神质（P）、神经质（N）维度得分为倾向型，内外向（E）和掩饰性（L）维度得分为中间型；婚姻调适良好组与婚姻失调组、婚龄≤5年组与婚龄＞5年组患者人格特征在精神质（P）、内外向（E）和神经质（N）维度得分比较，差异具有统计学意义（均P＜0.01）；患者婚姻调适与精神质（P）、神经质（N）维度呈负相关，与内外向（E）维度呈正相关；患者婚龄与精神质（P）、神经质（N）则呈正相关，与内外向（E）、掩饰性（L）维度呈负相关。结论不孕不育症患者家庭婚姻失调较多，婚姻调适与婚龄影响不孕不育症患者人格特征。提示不孕不育症患者影响其身心健康，应早期对其进行心理干预，特别是对于婚姻调适不良及婚龄＞5年患者。%Objective To study the correlation between marital adjustment and personality characteristics in infertile patients. Method The Locke-Wollance marital adjustment measurement scale and Eysenck personality questionnaire(EPQ)were used among 156 patients with infertility to investigate the correlation between marital adjustment and personality characteristics in infertile patients. Results The total score on the marital adjustment was(100.7±15.5). The rate of good marital adjustment was 51.3%and the rate of marital maladjustment was 48.7%. Those with a marital time of shorter than 5
On the Origin of Gravitational Lorentz Covariance
Khoury, Justin; Tolley, Andrew J
2013-01-01
We provide evidence that general relativity is the unique spatially covariant effective field theory of the transverse, traceless graviton degrees of freedom. The Lorentz covariance of general relativity, having not been assumed in our analysis, is thus plausibly interpreted as an accidental or emergent symmetry of the gravitational sector.
COVARIATION BIAS AND THE RETURN OF FEAR
de Jong, Peter; VANDENHOUT, MA; MERCKELBACH, H
1995-01-01
Several studies have indicated that phobic fear is accompanied by a covariation bias, i.e. that phobic Ss tend to overassociate fear relevant stimuli and aversive outcomes. Such a covariation bias seems to be a fairly direct and powerful way to confirm danger expectations and enhance fear. Therefore
Covariant derivative of fermions and all that
Shapiro, Ilya L
2016-01-01
We present detailed pedagogical derivation of covariant derivative of fermions and some related expressions, including commutator of covariant derivatives and energy-momentum tensor of a free Dirac field. The text represents a part of the initial chapter of a one-semester course on semiclassical gravity.
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.
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.
Into the Bulk: A Covariant Approach
Engelhardt, Netta
2016-01-01
I propose a general, covariant way of defining when one region is "deeper in the bulk" than another. This definition is formulated outside of an event horizon (or in the absence thereof) in generic geometries; it may be applied to both points and surfaces, and may be used to compare the depth of bulk points or surfaces relative to a particular boundary subregion or relative to the entire boundary. Using the recently proposed "lightcone cut" formalism, the comparative depth between two bulk points can be determined from the singularity structure of Lorentzian correlators in the dual field theory. I prove that, by this definition, causal wedges of progressively larger regions probe monotonically deeper in the bulk. The definition furthermore matches expectations in pure AdS and in static AdS black holes with isotropic spatial slices, where a well-defined holographic coordinate exists. In terms of holographic RG flow, this new definition of bulk depth makes contact with coarse-graining over both large distances ...
Exploring Eddy-Covariance Measurements Using a Spatial Approach: The Eddy Matrix
Engelmann, Christian; Bernhofer, Christian
2016-10-01
Taylor's frozen turbulence hypothesis states that "standard" eddy-covariance measurements of fluxes at a fixed location can replace a spatial ensemble of instantaneous values at multiple locations. For testing this hypothesis, a unique turbulence measurement set-up was used for two measurement campaigns over desert (Namibia) and grassland (Germany) in 2012. This "Eddy Matrix" combined nine ultrasonic anemometer-thermometers and 17 thermocouples in a 10 m × 10 m regular grid with 2.5-m grid distance. The instantaneous buoyancy flux derived from the spatial eddy covariance of the Eddy Matrix was highly variable in time (from -0.3 to 1 m K s^{-1}). However, the 10-min average reflected 83 % of the reference eddy-covariance flux with a good correlation. By introducing a combined eddy-covariance method (the spatial eddy covariance plus the additional flux of the temporal eddy covariance of the spatial mean values), the mean flux increases by 9 % relative to the eddy-covariance reference. Considering the typical underestimation of fluxes by the standard eddy-covariance method, this is seen as an improvement. Within the limits of the Eddy Matrix, Taylor's hypothesis is supported by the results.
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.
Covariance biplot analysis of trace element concentrations in urinary stones.
Wandt, M A; Underhill, L G
1988-06-01
The covariance biplot, a relatively new technique for displaying multivariate data, was applied to trace element contents and compound concentrations of urinary stones. The biplot is demonstrated to give a compact graphical representation of the multivariate data with interpretations in terms of familiar statistical concepts such as correlations and standard deviations. It displays strong correlations between various trace elements like Zn and Sr, and Sr and Na. The biplot also suggests concentration relationships which could play a hitherto unknown role in the genesis of calculi. It is shown to help in the interpretation of analytical results as well as in exposing erroneous or incomplete analyses.
Resting-state brain organization revealed by functional covariance networks.
Directory of Open Access Journals (Sweden)
Zhiqiang Zhang
Full Text Available BACKGROUND: Brain network studies using techniques of intrinsic connectivity network based on fMRI time series (TS-ICN and structural covariance network (SCN have mapped out functional and structural organization of human brain at respective time scales. However, there lacks a meso-time-scale network to bridge the ICN and SCN and get insights of brain functional organization. METHODOLOGY AND PRINCIPAL FINDINGS: We proposed a functional covariance network (FCN method by measuring the covariance of amplitude of low-frequency fluctuations (ALFF in BOLD signals across subjects, and compared the patterns of ALFF-FCNs with the TS-ICNs and SCNs by mapping the brain networks of default network, task-positive network and sensory networks. We demonstrated large overlap among FCNs, ICNs and SCNs and modular nature in FCNs and ICNs by using conjunctional analysis. Most interestingly, FCN analysis showed a network dichotomy consisting of anti-correlated high-level cognitive system and low-level perceptive system, which is a novel finding different from the ICN dichotomy consisting of the default-mode network and the task-positive network. CONCLUSION: The current study proposed an ALFF-FCN approach to measure the interregional correlation of brain activity responding to short periods of state, and revealed novel organization patterns of resting-state brain activity from an intermediate time scale.
Noise Covariance Properties in Dual-Tree Wavelet Decompositions
Chaux, Caroline; Duval, Laurent; 10.1109/TIT.2007.909104
2011-01-01
Dual-tree wavelet decompositions have recently gained much popularity, mainly due to their ability to provide an accurate directional analysis of images combined with a reduced redundancy. When the decomposition of a random process is performed -- which occurs in particular when an additive noise is corrupting the signal to be analyzed -- it is useful to characterize the statistical properties of the dual-tree wavelet coefficients of this process. As dual-tree decompositions constitute overcomplete frame expansions, correlation structures are introduced among the coefficients, even when a white noise is analyzed. In this paper, we show that it is possible to provide an accurate description of the covariance properties of the dual-tree coefficients of a wide-sense stationary process. The expressions of the (cross-)covariance sequences of the coefficients are derived in the one and two-dimensional cases. Asymptotic results are also provided, allowing to predict the behaviour of the second-order moments for larg...
Estimation of Low-Rank Covariance Function
Koltchinskii, Vladimir; Lounici, Karim; Tsybakov, Alexander B.
2015-01-01
We consider the problem of estimating a low rank covariance function $K(t,u)$ of a Gaussian process $S(t), t\\in [0,1]$ based on $n$ i.i.d. copies of $S$ observed in a white noise. We suggest a new estimation procedure adapting simultaneously to the low rank structure and the smoothness of the covariance function. The new procedure is based on nuclear norm penalization and exhibits superior performances as compared to the sample covariance function by a polynomial factor in the sample size $n$...
Ocean Data Assimilation with Background Error Covariance Derived from OGCM Outputs
Institute of Scientific and Technical Information of China (English)
符伟伟; 周广庆; 王会军
2004-01-01
The background error covariance plays an important role in modern data assimilation and analysis systems by determining the spatial spreading of information in the data. A novel method based on model output is proposed to estimate background error covariance for use in Optimum Interpolation. At every model level, anisotropic correlation scales are obtained that give a more detailed description of the spatial correlation structure. Furthermore, the impact of the background field itself is included in the background error covariance. The methodology of the estimation is presented and the structure of the covariance is examined. The results of 20-year assimilation experiments are compared with observations from TOGATAO (The Tropical Ocean-Global Atmosphere-Tropical Atmosphere Ocean) array and other analysis data.
Kim, Daniel Seung; Li, Yatong K; Bell, Griffith A; Burt, Amber A; Vaisar, Tomas; Hutchins, Patrick M; Furlong, Clement E; Otvos, James D; Polak, Joseph F; Arnan, Martinson Kweku; Kaufman, Joel D; McClelland, Robyn L; Longstreth, W T; Jarvik, Gail P
2016-05-20
Recent studies have failed to establish a causal relationship between high-density lipoprotein cholesterol levels (HDL-C) and cardiovascular disease (CVD), shifting focus to other HDL measures. We previously reported that smaller/denser HDL levels are protective against cerebrovascular disease. This study sought to determine which of small+medium HDL particle concentration (HDL-P) or large HDL-P was more strongly associated with carotid intima-media thickening (cIMT) in an ethnically diverse cohort. In cross-sectional analyses of participants from the Multi Ethnic Study of Atherosclerosis (MESA), we evaluated the associations of nuclear magnetic resonance spectroscopy-measured small+medium versus large HDL-P with cIMT measured in the common and internal carotid arteries, through linear regression. After adjustment for CVD confounders, low-density lipoprotein cholesterol (LDL-C), HDL-C, and small+medium HDL-P remained significantly and inversely associated with common (coefficient=-1.46 μm; P=0.00037; n=6512) and internal cIMT (coefficient=-3.82 μm; P=0.0051; n=6418) after Bonferroni correction for 4 independent tests (threshold for significance=0.0125; α=0.05/4). Large HDL-P was significantly and inversely associated with both cIMT outcomes before HDL-C adjustment; however, after adjustment for HDL-C, the association of large HDL-P with both common (coefficient=1.55 μm; P=0.30; n=6512) and internal cIMT (coefficient=4.84 μm; P=0.33; n=6418) was attenuated. In a separate sample of 126 men, small/medium HDL-P was more strongly correlated with paraoxonase 1 activity (rp=0.32; P=0.00023) as compared to both total HDL-P (rp=0.27; P=0.0024) and large HDL-P (rp=0.02; P=0.41) measures. Small+medium HDL-P is significantly and inversely correlated with cIMT measurements. Correlation of small+medium HDL-P with cardioprotective paraoxonase 1 activity may reflect a functional aspect of HDL responsible for this finding. © 2016 The Authors. Published on behalf of the
COVARIANCE CORRECTION FOR ESTIMATING GROUNDWATER ...
African Journals Online (AJOL)
2015-01-15
Jan 15, 2015 ... and V, which is known as observation noise, is a Gaussian process vector with ... where Kalman gain matrix (K ) which is the weighting matrix for ... The most widely used correlation function is compactly supported 5th order ...
On covariances for fusing laser rangers and vision with sensors onboard a moving robot
Wernersson, Åke; Nygårds, Jonas
1998-01-01
Consider a robot to measure or operate on man made objects randomly located in the workspace. The optronic sensing onboard the robot are a scanning range measuring time-of-flight laser and a CCD camera. The goal of the paper is to give explicit covariance matrices for the extracted geometric primitives in the surrounding workspace. Emphasis is on correlation properties of the stochastic error models during motion. Topics studied include: (i) covariance of Radon/Hough peaks for plane surfaces;...
Asymptotic behavior of the likelihood function of covariance matrices of spatial Gaussian processes
DEFF Research Database (Denmark)
Zimmermann, Ralf
2010-01-01
The covariance structure of spatial Gaussian predictors (aka Kriging predictors) is generally modeled by parameterized covariance functions; the associated hyperparameters in turn are estimated via the method of maximum likelihood. In this work, the asymptotic behavior of the maximum likelihood......: optimally trained nondegenerate spatial Gaussian processes cannot feature arbitrary ill-conditioned correlation matrices. The implication of this theorem on Kriging hyperparameter optimization is exposed. A nonartificial example is presented, where maximum likelihood-based Kriging model training...
Gosho, Masahiko; Hirakawa, Akihiro; Noma, Hisashi; Maruo, Kazushi; Sato, Yasunori
2015-08-11
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
Covariance NMR spectroscopy by singular value decomposition.
Trbovic, Nikola; Smirnov, Serge; Zhang, Fengli; Brüschweiler, Rafael
2004-12-01
Covariance NMR is demonstrated for homonuclear 2D NMR data collected using the hypercomplex and TPPI methods. Absorption mode 2D spectra are obtained by application of the square-root operation to the covariance matrices. The resulting spectra closely resemble the 2D Fourier transformation spectra, except that they are fully symmetric with the spectral resolution along both dimensions determined by the favorable resolution achievable along omega2. An efficient method is introduced for the calculation of the square root of the covariance spectrum by applying a singular value decomposition (SVD) directly to the mixed time-frequency domain data matrix. Applications are shown for 2D NOESY and 2QF-COSY data sets and computational benchmarks are given for data matrix dimensions typically encountered in practice. The SVD implementation makes covariance NMR amenable to routine applications.
Earth Observing System Covariance Realism Updates
Ojeda Romero, Juan A.; Miguel, Fred
2017-01-01
This presentation will be given at the International Earth Science Constellation Mission Operations Working Group meetings June 13-15, 2017 to discuss the Earth Observing System Covariance Realism updates.
Covariant Quantization with Extended BRST Symmetry
Geyer, B; Lavrov, P M
1999-01-01
A short rewiev of covariant quantization methods based on BRST-antiBRST symmetry is given. In particular problems of correct definition of Sp(2) symmetric quantization scheme known as triplectic quantization are considered.
Conformally covariant parametrizations for relativistic initial data
Delay, Erwann
2017-01-01
We revisit the Lichnerowicz-York method, and an alternative method of York, in order to obtain some conformally covariant systems. This type of parametrization is certainly more natural for non constant mean curvature initial data.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-07
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(n log n). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and optimal design
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-01-05
We approximate large non-structured covariance matrices in the H-matrix format with a log-linear computational cost and storage O(nlogn). We compute inverse, Cholesky decomposition and determinant in H-format. As an example we consider the class of Matern covariance functions, which are very popular in spatial statistics, geostatistics, machine learning and image analysis. Applications are: kriging and op- timal design.
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.
Covariant action for type IIB supergravity
Sen, Ashoke
2016-07-01
Taking clues from the recent construction of the covariant action for type II and heterotic string field theories, we construct a manifestly Lorentz covariant action for type IIB supergravity, and discuss its gauge fixing maintaining manifest Lorentz invariance. The action contains a (non-gravitating) free 4-form field besides the usual fields of type IIB supergravity. This free field, being completely decoupled from the interacting sector, has no physical consequence.
Functional CLT for sample covariance matrices
Bai, Zhidong; Zhou, Wang; 10.3150/10-BEJ250
2010-01-01
Using Bernstein polynomial approximations, we prove the central limit theorem for linear spectral statistics of sample covariance matrices, indexed by a set of functions with continuous fourth order derivatives on an open interval including $[(1-\\sqrt{y})^2,(1+\\sqrt{y})^2]$, the support of the Mar\\u{c}enko--Pastur law. We also derive the explicit expressions for asymptotic mean and covariance functions.
On the covariance of residual lives
Directory of Open Access Journals (Sweden)
N. Unnikrishnan Nair
2007-10-01
Full Text Available Various properties of residual life such as mean, median, percentiles, variance etc have been discussed in literature on reliability and survival analysis. However a detailed study on covariance between residual lives in a two component system does not seem to have been undertaken. The present paper discusses various properties of product moment and covariance of residual lives. Relationships the product moment has with mean residual life and failure rate are studied and some characterizations are established.
Covariant Hamilton equations for field theory
Energy Technology Data Exchange (ETDEWEB)
Giachetta, Giovanni [Department of Mathematics and Physics, University of Camerino, Camerino (Italy); Mangiarotti, Luigi [Department of Mathematics and Physics, University of Camerino, Camerino (Italy)]. E-mail: mangiaro@camserv.unicam.it; Sardanashvily, Gennadi [Department of Theoretical Physics, Physics Faculty, Moscow State University, Moscow (Russian Federation)]. E-mail: sard@grav.phys.msu.su
1999-09-24
We study the relations between the equations of first-order Lagrangian field theory on fibre bundles and the covariant Hamilton equations on the finite-dimensional polysymplectic phase space of covariant Hamiltonian field theory. If a Lagrangian is hyperregular, these equations are equivalent. A degenerate Lagrangian requires a set of associated Hamiltonian forms in order to exhaust all solutions of the Euler-Lagrange equations. The case of quadratic degenerate Lagrangians is studied in detail. (author)
Economical Phase-Covariant Cloning of Qudits
Buscemi, F; Macchiavello, C; Buscemi, Francesco; Ariano, Giacomo Mauro D'; Macchiavello, Chiara
2004-01-01
We derive the optimal $N\\to M$ phase-covariant quantum cloning for equatorial states in dimension $d$ with $M=kd+N$, $k$ integer. The cloning maps are optimal for both global and single-qudit fidelity. The map is achieved by an ``economical'' cloning machine, which works without ancilla. The connection between optimal phase-covariant cloning and optimal multi-phase estimation is finally established.
Covariance-Adaptive Slice Sampling
Thompson, Madeleine; Neal, Radford M.
2010-01-01
We describe two slice sampling methods for taking multivariate steps using the crumb framework. These methods use the gradients at rejected proposals to adapt to the local curvature of the log-density surface, a technique that can produce much better proposals when parameters are highly correlated. We evaluate our methods on four distributions and compare their performance to that of a non-adaptive slice sampling method and a Metropolis method. The adaptive methods perform favorably on low-di...
Sex hormones adjust "sex-specific" reactive and diurnal cortisol profiles.
Juster, Robert-Paul; Raymond, Catherine; Desrochers, Alexandra Bisson; Bourdon, Olivier; Durand, Nadia; Wan, Nathalie; Pruessner, Jens C; Lupien, Sonia J
2016-01-01
Sex differences in stress hormone functions are presumed to depend on sex hormones. And yet, surprisingly few psychoneuroendocrine studies actually assess within-sex variations of testosterone, estradiol, and progesterone when investigating sex-specific activities of the hypothalamic-pituitary-adrenal axis. In this methodological study of 204 healthy adults (60 men), we assessed whether cortisol profiles would differ between the sexes when unadjusted or adjusted for basal sex hormones among both sexes. Reactive cortisol was sampled using 6 saliva samples measured every 10-min as part of the Trier Social Stress Test that generally activates cortisol among men more than women. Diurnal cortisol was sampled over two days at (1) awakening, (2) 30-min thereafter, (3) 1400 h, (4) 1600 h, and (5) bedtime. Sex hormones were collected at baseline before the psychosocial stressor and on two occasions during diurnal cortisol assessment. Repeated-measures analysis of covariance controlled for key covariates in analyses unadjusted or adjusted for sex hormones. Results revealed that men had higher reactive cortisol than women in unadjusted analysis, but this sex difference was attenuated when adjusting for sex hormones. While diurnal cortisol showed no sex differences in unadjusted models, adjusting for sex hormones revealed that women have higher morning cortisol. Correlations using area under the curve formulae revealed intriguing sex-specific associations with progesterone in men and testosterone in women that we propose have implications for social and affective neuroscience. In summary, our results reveal that adjusting for sex hormones alters "sex-specific" reactive and diurnal cortisol profiles.
Covariant density functional theory: Reexamining the structure of superheavy nuclei
Agbemava, S E; Nakatsukasa, T; Ring, P
2015-01-01
A systematic investigation of even-even superheavy elements in the region of proton numbers $100 \\leq Z \\leq 130$ and in the region of neutron numbers from the proton-drip line up to neutron number $N=196$ is presented. For this study we use five most up-to-date covariant energy density functionals of different types, with a non-linear meson coupling, with density dependent meson couplings, and with density-dependent zero-range interactions. Pairing correlations are treated within relativistic Hartree-Bogoliubov (RHB) theory based on an effective separable particle-particle interaction of finite range and deformation effects are taken into account. This allows us to assess the spread of theoretical predictions within the present covariant models for the binding energies, deformation parameters, shell structures and $\\alpha$-decay half-lives. Contrary to the previous studies in covariant density functional theory, it was found that the impact of $N=172$ spherical shell gap on the structure of superheavy elemen...
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.
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.
Wishart distributions for decomposable covariance graph models
Khare, Kshitij; 10.1214/10-AOS841
2011-01-01
Gaussian covariance graph models encode marginal independence among the components of a multivariate random vector by means of a graph $G$. These models are distinctly different from the traditional concentration graph models (often also referred to as Gaussian graphical models or covariance selection models) since the zeros in the parameter are now reflected in the covariance matrix $\\Sigma$, as compared to the concentration matrix $\\Omega =\\Sigma^{-1}$. The parameter space of interest for covariance graph models is the cone $P_G$ of positive definite matrices with fixed zeros corresponding to the missing edges of $G$. As in Letac and Massam [Ann. Statist. 35 (2007) 1278--1323], we consider the case where $G$ is decomposable. In this paper, we construct on the cone $P_G$ a family of Wishart distributions which serve a similar purpose in the covariance graph setting as those constructed by Letac and Massam [Ann. Statist. 35 (2007) 1278--1323] and Dawid and Lauritzen [Ann. Statist. 21 (1993) 1272--1317] do in ...
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.
Lorentz covariance of loop quantum gravity
Rovelli, Carlo
2010-01-01
The kinematics of loop gravity can be given a manifestly Lorentz-covariant formulation: the conventional SU(2)-spin-network Hilbert space can be mapped to a space K of SL(2,C) functions, where Lorentz covariance is manifest. K can be described in terms of a certain subset of the "projected" spin networks studied by Livine, Alexandrov and Dupuis. It is formed by SL(2,C) functions completely determined by their restriction on SU(2). These are square-integrable in the SU(2) scalar product, but not in the SL(2,C) one. Thus, SU(2)-spin-network states can be represented by Lorentz-covariant SL(2,C) functions, as two-component photons can be described in the Lorentz-covariant Gupta-Bleuler formalism. As shown by Wolfgang Wieland in a related paper, this manifestly Lorentz-covariant formulation can also be directly obtained from canonical quantization. We show that the spinfoam dynamics of loop quantum gravity is locally SL(2,C)-invariant in the bulk, and yields states that are preciseley in K on the boundary. This c...
Accurate covariance estimation of galaxy-galaxy weak lensing: limitations of jackknife covariance
Shirasaki, Masato; Miyatake, Hironao; Takahashi, Ryuichi; Hamana, Takashi; Nishimichi, Takahiro; Murata, Ryoma
2016-01-01
We develop a method to simulate galaxy-galaxy weak lensing by utilizing all-sky, light-cone simulations. We populate a real catalog of source galaxies into a light-cone simulation realization, simulate the lensing effect on each galaxy, and then identify lensing halos that are considered to host galaxies or clusters of interest. We use the mock catalog to study the error covariance matrix of galaxy-galaxy weak lensing and find that the super-sample covariance (SSC), which arises from density fluctuations with length scales comparable with or greater than a size of survey area, gives a dominant source of the sample variance. We then compare the full covariance with the jackknife (JK) covariance, the method that estimates the covariance from the resamples of the data itself. We show that, although the JK method gives an unbiased estimator of the covariance in the shot noise or Gaussian regime, it always over-estimates the true covariance in the sample variance regime, because the JK covariance turns out to be a...
Covariant Lyapunov vectors for rigid disk systems.
Bosetti, Hadrien; Posch, Harald A
2010-10-05
We carry out extensive computer simulations to study the Lyapunov instability of a two-dimensional hard-disk system in a rectangular box with periodic boundary conditions. The system is large enough to allow the formation of Lyapunov modes parallel to the x-axis of the box. The Oseledec splitting into covariant subspaces of the tangent space is considered by computing the full set of covariant perturbation vectors co-moving with the flow in tangent space. These vectors are shown to be transversal, but generally not orthogonal to each other. Only the angle between covariant vectors associated with immediate adjacent Lyapunov exponents in the Lyapunov spectrum may become small, but the probability of this angle to vanish approaches zero. The stable and unstable manifolds are transverse to each other and the system is hyperbolic.
Manifest Covariant Hamiltonian Theory of General Relativity
Cremaschini, Claudio
2016-01-01
The problem of formulating a manifest covariant Hamiltonian theory of General Relativity in the presence of source fields is addressed, by extending the so-called "DeDonder-Weyl" formalism to the treatment of classical fields in curved space-time. The theory is based on a synchronous variational principle for the Einstein equation, formulated in terms of superabundant variables. The technique permits one to determine the continuum covariant Hamiltonian structure associated with the Einstein equation. The corresponding continuum Poisson bracket representation is also determined. The theory relies on first-principles, in the sense that the conclusions are reached in the framework of a non-perturbative covariant approach, which allows one to preserve both the 4-scalar nature of Lagrangian and Hamiltonian densities as well as the gauge invariance property of the theory.
Hui, Yi; Law, Siu Seong; Ku, Chiu Jen
2017-02-01
Covariance of the auto/cross-covariance matrix based method is studied for the damage identification of a structure with illustrations on its advantages and limitations. The original method is extended for structures under direct white noise excitations. The auto/cross-covariance function of the measured acceleration and its corresponding derivatives are formulated analytically, and the method is modified in two new strategies to enable successful identification with much fewer sensors. Numerical examples are adopted to illustrate the improved method, and the effects of sampling frequency and sampling duration are discussed. Results show that the covariance of covariance calculated from responses of higher order modes of a structure play an important role to the accurate identification of local damage in a structure.
Activities on covariance estimation in Japanese Nuclear Data Committee
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)
An adjustable contracted CI method
Institute of Scientific and Technical Information of China (English)
王育彬; 甘正汀; 苏克和; 文振翼
1999-01-01
A new contracted CI scheme——adjustable contracted CI scheme——is presented and programed. The efficiency of this scheme is tested by some example calculations. The result shows that the application of the new scheme is flexible and the correlation energy loss is lower than that of the original externally contracted CI method.
Notes on Cosmic Censorship Conjecture revisited: Covariantly
Hamid, Aymen I M; Maharaj, Sunil D
2016-01-01
In this paper we study the dynamics of the trapped region using a frame independent semi-tetrad covariant formalism for general Locally Rotationally Symmetric (LRS) class II spacetimes. We covariantly prove some important geometrical results for the apparent horizon, and state the necessary and sufficient conditions for a singularity to be locally naked. These conditions bring out, for the first time in a quantitative and transparent manner, the importance of the Weyl curvature in deforming and delaying the trapped region during continual gravitational collapse, making the central singularity locally visible.
A covariant formulation of classical spinning particle
Cho, J H; Kim, J K; Jin-Ho Cho; Seungjoon Hyun; Jae-Kwan Kim
1994-01-01
Covariantly we reformulate the description of a spinning particle in terms of the which entails all possible constraints explicitly; all constraints can be obtained just from the Lagrangian. Furthermore, in this covariant reformulation, the Lorentz element is to be considered to evolve the momentum or spin component from an arbitrary fixed frame and not just from the particle rest frame. In distinction with the usual formulation, our system is directly comparable with the pseudo-classical formulation. We get a peculiar symmetry which resembles the supersymmetry of the pseudo-classical formulation.
A violation of the covariant entropy bound?
Masoumi, Ali
2014-01-01
Several arguments suggest that the entropy density at high energy density $\\rho$ should be given by the expression $s=K\\sqrt{\\rho/G}$, where $K$ is a constant of order unity. On the other hand the covariant entropy bound requires that the entropy on a light sheet be bounded by $A/4G$, where $A$ is the area of the boundary of the sheet. We find that in a suitably chosen cosmological geometry, the above expression for $s$ violates the covariant entropy bound. We consider different possible explanations for this fact; in particular the possibility that entropy bounds should be defined in terms of volumes of regions rather than areas of surfaces.
The Massless Spectrum of Covariant Superstrings
Grassi, P A; van Nieuwenhuizen, P
2002-01-01
We obtain the correct cohomology at any ghost number for the open and closed covariant superstring, quantized by an approach which we recently developed. We define physical states by the usual condition of BRST invariance and a new condition involving a new current which is related to a grading of the underlying affine Lie algebra.
EQUIVALENT MODELS IN COVARIANCE STRUCTURE-ANALYSIS
LUIJBEN, TCW
1991-01-01
Defining equivalent models as those that reproduce the same set of covariance matrices, necessary and sufficient conditions are stated for the local equivalence of two expanded identified models M1 and M2 when fitting the more restricted model M0. Assuming several regularity conditions, the rank def
Optimal covariate designs theory and applications
Das, Premadhis; Mandal, Nripes Kumar; Sinha, Bikas Kumar
2015-01-01
This book primarily addresses the optimality aspects of covariate designs. A covariate model is a combination of ANOVA and regression models. Optimal estimation of the parameters of the model using a suitable choice of designs is of great importance; as such choices allow experimenters to extract maximum information for the unknown model parameters. The main emphasis of this monograph is to start with an assumed covariate model in combination with some standard ANOVA set-ups such as CRD, RBD, BIBD, GDD, BTIBD, BPEBD, cross-over, multi-factor, split-plot and strip-plot designs, treatment control designs, etc. and discuss the nature and availability of optimal covariate designs. In some situations, optimal estimations of both ANOVA and the regression parameters are provided. Global optimality and D-optimality criteria are mainly used in selecting the design. The standard optimality results of both discrete and continuous set-ups have been adapted, and several novel combinatorial techniques have been applied for...
Covariant formulation of pion-nucleon scattering
Lahiff, A. D.; Afnan, I. R.
A covariant model of elastic pion-nucleon scattering based on the Bethe-Salpeter equation is presented. The kernel consists of s- and u-channel nucleon and delta poles, along with rho and sigma exchange in the t-channel. A good fit is obtained to the s- and p-wave phase shifts up to the two-pion production threshold.
Approximate methods for derivation of covariance data
Energy Technology Data Exchange (ETDEWEB)
Tagesen, S. [Vienna Univ. (Austria). Inst. fuer Radiumforschung und Kernphysik; Larson, D.C. [Oak Ridge National Lab., TN (United States)
1992-12-31
Several approaches for the derivation of covariance information for evaluated nuclear data files (EFF2 and ENDF/B-VI) have been developed and used at IRK and ORNL respectively. Considerations, governing the choice of a distinct method depending on the quantity and quality of available data are presented, advantages/disadvantages are discussed and examples of results are given.
Covariance of noncommutative Grassmann star product
Daoud, M.
2004-01-01
Using the Coherent states of many fermionic degrees of freedom labeled by Gra\\ss mann variables, we introduce the noncommutative (precisely non anticommutative) Gra\\ss mann star product. The covariance of star product under unitary transformations, particularly canonical ones, is studied. The super star product, based on supercoherent states of supersymmetric harmonic oscillator, is also considered.
Covariance of the selfdual vector model
2004-01-01
The Poisson algebra between the fields involved in the vectorial selfdual action is obtained by means of the reduced action. The conserved charges associated with the invariance under the inhomogeneous Lorentz group are obtained and its action on the fields. The covariance of the theory is proved using the Schwinger-Dirac algebra. The spin of the excitations is discussed.
Hierarchical matrix approximation of large covariance matrices
Litvinenko, Alexander
2015-11-30
We approximate large non-structured Matérn covariance matrices of size n×n in the H-matrix format with a log-linear computational cost and storage O(kn log n), where rank k ≪ n is a small integer. Applications are: spatial statistics, machine learning and image analysis, kriging and optimal design.
Linear transformations of variance/covariance matrices
Parois, P.J.A.; Lutz, M.
2011-01-01
Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance
Covariant Photon Quantization in the SME
Colladay, Don
2013-01-01
The Gupta Bleuler quantization procedure is applied to the SME photon sector. A direct application of the method to the massless case fails due to an unavoidable incompleteness in the polarization states. A mass term can be included into the photon lagrangian to rescue the quantization procedure and maintain covariance.
Covariant derivative expansion of the heat kernel
Energy Technology Data Exchange (ETDEWEB)
Salcedo, L.L. [Universidad de Granada, Departamento de Fisica Moderna, Granada (Spain)
2004-11-01
Using the technique of labeled operators, compact explicit expressions are given for all traced heat kernel coefficients containing zero, two, four and six covariant derivatives, and for diagonal coefficients with zero, two and four derivatives. The results apply to boundaryless flat space-times and arbitrary non-Abelian scalar and gauge background fields. (orig.)
Correlates of Depressive Symptoms in Older Adults with Diabetes
Directory of Open Access Journals (Sweden)
LaRita C. Jones
2016-01-01
Full Text Available Investigators examined correlates of depressive symptoms within a sample of older adults with diabetes. Participants completed a structured telephone interview with measures including depressive symptoms, health conditions, cognitive function, and diabetes distress. Correlations and hierarchical linear regression models were utilized to examine bivariate and covariate-adjusted correlates of depressive symptoms. The sample included 246 community-dwelling adults with diabetes (≥65 years old. In bivariate analyses, African Americans, individuals with specific health issues (neuropathy, stroke, respiratory issues, arthritis, and cardiac issues, and those with higher levels of diabetes distress reported more depressive symptoms. Older age, higher education, more income, and better cognitive function were inversely associated with depressive symptoms. In the final covariate-adjusted regression model, stroke (B = .22, p<.001, cognitive function (B = −.14, p<.01, and higher levels of diabetes-related distress (B = .49, p<.001 each were uniquely associated with more depressive symptoms. Diabetes distress partially mediated the associations between cardiac issues and depressive symptoms and between cognitive function and depressive symptoms. Findings suggest that interventions targeted at helping older adults manage their diabetes-related distress and reducing the likelihood of experiencing additional health complications may reduce depressive symptoms within this population.
Correlates of Depressive Symptoms in Older Adults with Diabetes.
Jones, LaRita C; Clay, Olivio J; Ovalle, Fernando; Cherrington, Andrea; Crowe, Michael
2016-01-01
Investigators examined correlates of depressive symptoms within a sample of older adults with diabetes. Participants completed a structured telephone interview with measures including depressive symptoms, health conditions, cognitive function, and diabetes distress. Correlations and hierarchical linear regression models were utilized to examine bivariate and covariate-adjusted correlates of depressive symptoms. The sample included 246 community-dwelling adults with diabetes (≥ 65 years old). In bivariate analyses, African Americans, individuals with specific health issues (neuropathy, stroke, respiratory issues, arthritis, and cardiac issues), and those with higher levels of diabetes distress reported more depressive symptoms. Older age, higher education, more income, and better cognitive function were inversely associated with depressive symptoms. In the final covariate-adjusted regression model, stroke (B = .22, p < .001), cognitive function (B = -.14, p < .01), and higher levels of diabetes-related distress (B = .49, p < .001) each were uniquely associated with more depressive symptoms. Diabetes distress partially mediated the associations between cardiac issues and depressive symptoms and between cognitive function and depressive symptoms. Findings suggest that interventions targeted at helping older adults manage their diabetes-related distress and reducing the likelihood of experiencing additional health complications may reduce depressive symptoms within this population.
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
Unravelling Lorentz Covariance and the Spacetime Formalism
Directory of Open Access Journals (Sweden)
Cahill R. T.
2008-10-01
Full Text Available We report the discovery of an exact mapping from Galilean time and space coordinates to Minkowski spacetime coordinates, showing that Lorentz covariance and the space-time construct are consistent with the existence of a dynamical 3-space, and absolute motion. We illustrate this mapping first with the standard theory of sound, as vibrations of a medium, which itself may be undergoing fluid motion, and which is covariant under Galilean coordinate transformations. By introducing a different non-physical class of space and time coordinates it may be cast into a form that is covariant under Lorentz transformations wherein the speed of sound is now the invariant speed. If this latter formalism were taken as fundamental and complete we would be lead to the introduction of a pseudo-Riemannian spacetime description of sound, with a metric characterised by an invariant speed of sound. This analysis is an allegory for the development of 20th century physics, but where the Lorentz covariant Maxwell equations were constructed first, and the Galilean form was later constructed by Hertz, but ignored. It is shown that the Lorentz covariance of the Maxwell equations only occurs because of the use of non-physical space and time coordinates. The use of this class of coordinates has confounded 20th century physics, and resulted in the existence of a allowing dynamical 3-space being overlooked. The discovery of the dynamics of this 3-space has lead to the derivation of an extended gravity theory as a quantum effect, and confirmed by numerous experiments and observations
Unravelling Lorentz Covariance and the Spacetime Formalism
Directory of Open Access Journals (Sweden)
Cahill R. T.
2008-10-01
Full Text Available We report the discovery of an exact mapping from Galilean time and space coordinates to Minkowski spacetime coordinates, showing that Lorentz covariance and the space- time construct are consistent with the existence of a dynamical 3-space, and “absolute motion”. We illustrate this mapping first with the standard theory of sound, as vibra- tions of a medium, which itself may be undergoing fluid motion, and which is covari- ant under Galilean coordinate transformations. By introducing a different non-physical class of space and time coordinates it may be cast into a form that is covariant under “Lorentz transformations” wherein the speed of sound is now the “invariant speed”. If this latter formalism were taken as fundamental and complete we would be lead to the introduction of a pseudo-Riemannian “spacetime” description of sound, with a metric characterised by an “invariant speed of sound”. This analysis is an allegory for the development of 20th century physics, but where the Lorentz covariant Maxwell equa- tions were constructed first, and the Galilean form was later constructed by Hertz, but ignored. It is shown that the Lorentz covariance of the Maxwell equations only occurs because of the use of non-physical space and time coordinates. The use of this class of coordinates has confounded 20th century physics, and resulted in the existence of a “flowing” dynamical 3-space being overlooked. The discovery of the dynamics of this 3-space has lead to the derivation of an extended gravity theory as a quantum effect, and confirmed by numerous experiments and observations
Institute of Scientific and Technical Information of China (English)
曾凡文; 王永利; 刘冬梅
2011-01-01
无线传感器网络( WSN)节点能量与带宽均非常有限,难以适应大量数据长时间传输的需求,所以非常有必要对原始采集的数据进行聚合或压缩处理.利用传感数据间存在的时间相关性,提出分段常量近似与Haar小波压缩相结合的二级压缩算法,在误差可调的情况下压缩该类时间相关的传感数据.通过真实数据集上的实验,分析该算法的数据重构误差、数据压缩比与压缩耗时情况,并与其他压缩算法进行对比.实验结果表明,该算法能够有效地利用传感数据中存在的时间相关性,显著减少冗余数据,有较高的压缩比并保证数据精度.%Wireless sensor network (WSN) lacks both node energy and bandwidth, so that it hardly meets the long time transmission needs; hence it is essential to aggregate or compress originally gathered data. The thesis utilizes time correlations among sensor data to propose a two level compression algorithm that is a combination of piecewise constant approximation and Haar wavelet compression so that under adjustable error conditions the time correlation sensor data are compressed. Then through experiments on real data sets, the reconstruction error, data compression ratio and consumed compression time of the algorithm are analyzed and compared with that of other algorithms. Experiment results demonstrate that the algorithm can efficiently take advantage of time correlations that exist among sensor data, significantly reduce redundant data, boasts for higher compression ration and promises data precision.
Schmitt, J Eric; Lenroot, Rhoshel K; Ordaz, Sarah E; Wallace, Gregory L; Lerch, Jason P; Evans, Alan C; Prom, Elizabeth C; Kendler, Kenneth S; Neale, Michael C; Giedd, Jay N
2009-08-01
The role of genetics in driving intracortical relationships is an important question that has rarely been studied in humans. In particular, there are no extant high-resolution imaging studies on genetic covariance. In this article, we describe a novel method that combines classical quantitative genetic methodologies for variance decomposition with recently developed semi-multivariate algorithms for high-resolution measurement of phenotypic covariance. Using these tools, we produced correlational maps of genetic and environmental (i.e. nongenetic) relationships between several regions of interest and the cortical surface in a large pediatric sample of 600 twins, siblings, and singletons. These analyses demonstrated high, fairly uniform, statistically significant genetic correlations between the entire cortex and global mean cortical thickness. In agreement with prior reports on phenotypic covariance using similar methods, we found that mean cortical thickness was most strongly correlated with association cortices. However, the present study suggests that genetics plays a large role in global brain patterning of cortical thickness in this manner. Further, using specific gyri with known high heritabilities as seed regions, we found a consistent pattern of high bilateral genetic correlations between structural homologues, with environmental correlations more restricted to the same hemisphere as the seed region, suggesting that interhemispheric covariance is largely genetically mediated. These findings are consistent with the limited existing knowledge on the genetics of cortical variability as well as our prior multivariate studies on cortical gyri.
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.
Chi, Zhiyi
2010-01-01
Two extensions of generalized linear models are considered. In the first one, response variables depend on multiple linear combinations of covariates. In the second one, only response variables are observed while the linear covariates are missing. We derive stochastic Lipschitz continuity results for the loss functions involved in the regression problems and apply them to get bounds on estimation error for Lasso. Multivariate comparison results on Rademacher complexity are obtained as tools to establish the stochastic Lipschitz continuity results.
Institute of Scientific and Technical Information of China (English)
ZHANG Wei-min; CAO Xiao-qun; XIAO Qin-nong; SONG Jun-qiang; ZHU Xiao-qian; WANG Shu-chang
2010-01-01
Background error covariance plays an important role in any variational data assimilation system,because it determines how information from observations is spread in model space and between different model variables.In this paper,the use of orthogonal wavelets in representation of background error covariance over a limited area is studied.Based on the WRF model and its 3D-VAR system,an algorithm using orthogonal wavelets to model background error covariance is developed.Because each wavelet function contains information on both position and scale,using a diagonal correlation matrix in wavelet space gives the possibility to represent some anisotropic and inhomogeneous characteristics of background error covariance.The experiments show that local correlation functions are better modeled than spectral methods.The formulation of wavelet background error covariance is tested with the typhoon Kaemi (2006).The results of experiments indicate that the subsequent forecasts of typhoon Kaemi's track and intensity are significantly improved by the new method.
Li, Xiujin; Lund, Mogens Sandø; Janss, Luc; Wang, Chonglong; Ding, Xiangdong; Zhang, Qin; Su, Guosheng
2017-03-15
With the development of SNP chips, SNP information provides an efficient approach to further disentangle different patterns of genomic variances and covariances across the genome for traits of interest. Due to the interaction between genotype and environment as well as possible differences in genetic background, it is reasonable to treat the performances of a biological trait in different populations as different but genetic correlated traits. In the present study, we performed an investigation on the patterns of region-specific genomic variances, covariances and correlations between Chinese and Nordic Holstein populations for three milk production traits. Variances and covariances between Chinese and Nordic Holstein populations were estimated for genomic regions at three different levels of genome region (all SNP as one region, each chromosome as one region and every 100 SNP as one region) using a novel multi-trait random regression model which uses latent variables to model heterogeneous variance and covariance. In the scenario of the whole genome as one region, the genomic variances, covariances and correlations obtained from the new multi-trait Bayesian method were comparable to those obtained from a multi-trait GBLUP for all the three milk production traits. In the scenario of each chromosome as one region, BTA 14 and BTA 5 accounted for very large genomic variance, covariance and correlation for milk yield and fat yield, whereas no specific chromosome showed very large genomic variance, covariance and correlation for protein yield. In the scenario of every 100 SNP as one region, most regions explained variance and covariance for milk yield and fat yield, and explained variance and covariance. Although overall correlations between two populations for the three traits were positive and high, a few regions still showed weakly positive or highly negative genomic correlations for milk yield and fat yield. The new multi-trait Bayesian method using latent variables
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...
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.
Covariance Analysis of Symmetry Energy Observables from Heavy Ion Collision
Zhang, Yingxun; Li, Zhuxia
2015-01-01
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 $^{124}$Sn+$^{124}$Sn, $^{124}$Sn+$^{112}$Sn and $^{112}$Sn+$^{112}$Sn reactions at beam energies of 50 and 120 MeV per nucleon, we have identified that the nucleon effective mass splitting are 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 ($\\sim$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 do...
Covariant Quantization of CPT-violating Photons
Colladay, D; Noordmans, J P; Potting, R
2016-01-01
We perform the covariant canonical quantization of the CPT- and Lorentz-symmetry-violating photon sector of the minimal Standard-Model Extension, which contains a general (timelike, lightlike, or spacelike) fixed background tensor $k_{AF}^\\mu$. Well-known stability issues, arising from complex-valued energy states, are solved by introducing a small photon mass, orders of magnitude below current experimental bounds. We explicitly construct a covariant basis of polarization vectors, in which the photon field can be expanded. We proceed to derive the Feynman propagator and show that the theory is microcausal. Despite the occurrence of negative energies and vacuum-Cherenkov radiation, we do not find any runaway stability issues, because the energy remains bounded from below. An important observation is that the ordering of the roots of the dispersion relations is the same in any observer frame, which allows for a frame-independent condition that selects the correct branch of the dispersion relation. This turns ou...
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.
Covariant holography of a tachyonic accelerating universe
Rozas-Fernández, Alberto
2014-01-01
We apply the holographic principle to a flat dark energy dominated Friedmann-Robertson-Walker spacetime filled with a tachyon scalar field with constant equation of state $w=p/\\rho$, both for $w>-1$ and $w<-1$. By using a geometrical covariant procedure, which allows the construction of holographic hypersurfaces, we have obtained for each case the position of the preferred screen and have then compared these with those obtained by using the holographic dark energy model with the future event horizon as the infrared cutoff. In the phantom scenario, one of the two obtained holographic screens is placed on the big rip hypersurface, both for the covariant holographic formalism and the holographic phantom model. It is also analysed whether the existence of these preferred screens allows a mathematically consistent formulation of fundamental theories based on the existence of a S matrix at infinite distances.
Model selection for Poisson processes with covariates
Sart, Mathieu
2011-01-01
We observe $n$ inhomogeneous Poisson processes with covariates and aim at estimating their intensities. To handle this problem, we assume that the intensity of each Poisson process is of the form $s (\\cdot, x)$ where $x$ is the covariate and where $s$ is an unknown function. We propose a model selection approach where the models are used to approximate the multivariate function $s$. We show that our estimator satisfies an oracle-type inequality under very weak assumptions both on the intensities and the models. By using an Hellinger-type loss, we establish non-asymptotic risk bounds and specify them under various kind of assumptions on the target function $s$ such as being smooth or composite. Besides, we show that our estimation procedure is robust with respect to these assumptions.
Errors on errors - Estimating cosmological parameter covariance
Joachimi, Benjamin
2014-01-01
Current and forthcoming cosmological data analyses share the challenge of huge datasets alongside increasingly tight requirements on the precision and accuracy of extracted cosmological parameters. The community is becoming increasingly aware that these requirements not only apply to the central values of parameters but, equally important, also to the error bars. Due to non-linear effects in the astrophysics, the instrument, and the analysis pipeline, data covariance matrices are usually not well known a priori and need to be estimated from the data itself, or from suites of large simulations. In either case, the finite number of realisations available to determine data covariances introduces significant biases and additional variance in the errors on cosmological parameters in a standard likelihood analysis. Here, we review recent work on quantifying these biases and additional variances and discuss approaches to remedy these effects.
Linear transformations of variance/covariance matrices.
Parois, Pascal; Lutz, Martin
2011-07-01
Many applications in crystallography require the use of linear transformations on parameters and their standard uncertainties. While the transformation of the parameters is textbook knowledge, the transformation of the standard uncertainties is more complicated and needs the full variance/covariance matrix. For the transformation of second-rank tensors it is suggested that the 3 × 3 matrix is re-written into a 9 × 1 vector. The transformation of the corresponding variance/covariance matrix is then straightforward and easily implemented into computer software. This method is applied in the transformation of anisotropic displacement parameters, the calculation of equivalent isotropic displacement parameters, the comparison of refinements in different space-group settings and the calculation of standard uncertainties of eigenvalues.
Covariant holography of a tachyonic accelerating universe
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.)
Chiral Four-Dimensional Heterotic Covariant Lattices
Beye, Florian
2014-01-01
In the covariant lattice formalism, chiral four-dimensional heterotic string vacua are obtained from certain even self-dual lattices which completely decompose into a left-mover and a right-mover lattice. The main purpose of this work is to classify all right-mover lattices that can appear in such a chiral model, and to study the corresponding left-mover lattices using the theory of lattice genera. In particular, the Smith-Minkowski-Siegel mass formula is employed to calculate a lower bound on the number of left-mover lattices. Also, the known relationship between asymmetric orbifolds and covariant lattices is considered in the context of our classification.
Systematic of Nuclear Ground State Properties in Sr Isotope by Covariant Density Functional Theory
Institute of Scientific and Technical Information of China (English)
TIAN; Yuan
2012-01-01
<正>The hyperfine structure and isotope shifts of Sr-isotopes, both even-even and odd-even nuclei, are studied in the covariant density functional theory (DFT) with the new parameter set DD-PC1. Pairing correlation is treated by using the Bogoliubov with a separable form of the pairing interaction. Spin-parity,
The Consequences of Ignoring Multilevel Data Structures in Nonhierarchical Covariance Modeling.
Julian, Marc W.
2001-01-01
Examined the effects of ignoring multilevel data structures in nonhierarchical covariance modeling using a Monte Carlo simulation. Results suggest that when the magnitudes of intraclass correlations are less than 0.05 and the group size is small, the consequences of ignoring the data dependence within the multilevel data structures seem to be…
Empirical data and the variance-covariance matrix for the 1969 Smithsonian Standard Earth (2)
Gaposchkin, E. M.
1972-01-01
The empirical data used in the 1969 Smithsonian Standard Earth (2) are presented. The variance-covariance matrix, or the normal equations, used for correlation analysis, are considered. The format and contents of the matrix, available on magnetic tape, are described and a sample printout is given.
Excess covariance and dynamic instability in a multi-asset model
Anufriev, M.; Bottazzi, G.; Marsili, M.; Pin, P.
2011-01-01
The presence of excess covariance in financial price returns is an accepted empirical fact: the price dynamics of financial assets tend to be more correlated than their fundamentals would justify. We propose an intertemporal equilibrium multi-assets model of financial markets with an explicit and
Twisted Covariant Noncommutative Self-dual Gravity
Estrada-Jimenez, S; Obregón, O; Ramírez, C
2008-01-01
A twisted covariant formulation of noncommutative self-dual gravity is presented. The recent formulation introduced by J. Wess and coworkers for constructing twisted Yang-Mills fields is used. It is shown that the noncommutative torsion is solved at any order of the $\\theta$-expansion in terms of the tetrad and the extra fields of the theory. In the process the first order expansion in $\\theta$ for the Pleba\\'nski action is explicitly obtained.
Covariant quantization of the CBS superparticle
Energy Technology Data Exchange (ETDEWEB)
Grassi, P.A. E-mail: pag5@nyu.edu; Policastro, G.; Porrati, M
2001-07-09
The quantization of the Casalbuoni-Brink-Schwarz superparticle is performed in an explicitly covariant way using the antibracket formalism. Since an infinite number of ghost fields are required, within a suitable off-shell twistor-like formalism, we are able to fix the gauge of each ghost sector without modifying the physical content of the theory. The computation reveals that the antibracket cohomology contains only the physical degrees of freedom.
Adaptive Covariance Estimation with model selection
Biscay, Rolando; Loubes, Jean-Michel
2012-01-01
We provide in this paper a fully adaptive penalized procedure to select a covariance among a collection of models observing i.i.d replications of the process at fixed observation points. For this we generalize previous results of Bigot and al. and propose to use a data driven penalty to obtain an oracle inequality for the estimator. We prove that this method is an extension to the matricial regression model of the work by Baraud.
Economical phase-covariant cloning with multiclones
Institute of Scientific and Technical Information of China (English)
Zhang Wen-Hai; Ye Liu
2009-01-01
This paper presents a very simple method to derive the explicit transformations of the optimal economical to M phase-covariant cloning. The fidelity of clones reaches the theoretic bound [D'Ariano G M and Macchiavello C 2003 Phys. Rcv. A 67 042306]. The derived transformations cover the previous contributions [Delgado Y,Lamata L et al,2007 Phys. Rev. Lett. 98 150502] in which M must be odd.
Unbiased risk estimation method for covariance estimation
Lescornel, Hélène; Chabriac, Claudie
2011-01-01
We consider a model selection estimator of the covariance of a random process. Using the Unbiased Risk Estimation (URE) method, we build an estimator of the risk which allows to select an estimator in a collection of model. Then, we present an oracle inequality which ensures that the risk of the selected estimator is close to the risk of the oracle. Simulations show the efficiency of this methodology.
Risk evaluation with enhaced covariance matrix
Urbanowicz, K; Richmond, P; Holyst, Janusz A.; Richmond, Peter; Urbanowicz, Krzysztof
2006-01-01
We propose a route for the evaluation of risk based on a transformation of the covariance matrix. The approach uses a `potential' or `objective' function. This allows us to rescale data from diferent assets (or sources) such that each set then has similar statistical properties in terms of their probability distributions. The method is tested using historical data from both the New York and Warsaw Stock Exchanges.
Superfield quantization in Sp(2) covariant formalism
Lavrov, P M
2001-01-01
The rules of the superfield Sp(2) covariant quantization of the arbitrary gauge theories for the case of the introduction of the gauging with the derivative equations for the gauge functional are generalized. The possibilities of realization of the expanded anti-brackets are considered and it is shown, that only one of the realizations is compatible with the transformations of the expanded BRST-symmetry in the form of super translations along the Grassmann superspace coordinates
Covariant quantization of the CBS superparticle
Grassi, P. A.; Policastro, G.; Porrati, M.
2001-07-01
The quantization of the Casalbuoni-Brink-Schwarz superparticle is performed in an explicitly covariant way using the antibracket formalism. Since an infinite number of ghost fields are required, within a suitable off-shell twistor-like formalism, we are able to fix the gauge of each ghost sector without modifying the physical content of the theory. The computation reveals that the antibracket cohomology contains only the physical degrees of freedom.
Torsion and geometrostasis in covariant superstrings
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.
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.
ANL Critical Assembly Covariance Matrix Generation
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)
2014-01-15
This report discusses the generation of a covariance matrix for selected critical assemblies that were carried out by Argonne National Laboratory (ANL) using four critical facilities-all of which are now decommissioned. The four different ANL critical facilities are: ZPR-3 located at ANL-West (now Idaho National Laboratory- INL), ZPR-6 and ZPR-9 located at ANL-East (Illinois) and ZPPr located at ANL-West.
Covariant Calculus for Effective String Theories
Dass, N. D. Hari; Matlock, Peter
2007-01-01
A covariant calculus for the construction of effective string theories is developed. Effective string theory, describing quantum string-like excitations in arbitrary dimension, has in the past been constructed using the principles of conformal field theory, but not in a systematic way. Using the freedom of choice of field definition, a particular field definition is made in a systematic way to allow an explicit construction of effective string theories with manifest exact conformal symmetry. ...
Covariates of Craving in Actively Drinking Alcoholics
Chakravorty, Subhajit; Kuna, Samuel T.; Zaharakis, Nikola; O’Brien, Charles P.; Kampman, Kyle M.; Oslin, David
2010-01-01
The goal of this cross-sectional study was to assess the relationship of alcohol craving with biopsychosocial and addiction factors that are clinically pertinent to alcoholism treatment. Alcohol craving was assessed in 315 treatment-seeking, alcohol dependent subjects using the PACS questionnaire. Standard validated questionnaires were used to evaluate a variety of biological, addiction, psychological, psychiatric, and social factors. Individual covariates of craving included age, race, probl...
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…
How covariant is the galaxy luminosity function?
Smith, Robert E
2012-01-01
We investigate the error properties of certain galaxy luminosity function (GLF) estimators. Using a cluster expansion of the density field, we show how, for both volume and flux limited samples, the GLF estimates are covariant. The covariance matrix can be decomposed into three pieces: a diagonal term arising from Poisson noise; a sample variance term arising from large-scale structure in the survey volume; an occupancy covariance term arising due to galaxies of different luminosities inhabiting the same cluster. To evaluate the theory one needs: the mass function and bias of clusters, and the conditional luminosity function (CLF). We use a semi-analytic model (SAM) galaxy catalogue from the Millennium run N-body simulation and the CLF of Yang et al. (2003) to explore these effects. The GLF estimates from the SAM and the CLF qualitatively reproduce results from the 2dFGRS. We also measure the luminosity dependence of clustering in the SAM and find reasonable agreement with 2dFGRS results for bright galaxies. ...
Development of covariance capabilities in EMPIRE code
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.
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.
REFINING GENETICALLY INFERRED RELATIONSHIPS USING TREELET COVARIANCE SMOOTHING1
Crossett, Andrew; Lee, Ann B.; Klei, Lambertus; Devlin, Bernie; Roeder, Kathryn
2013-01-01
Recent technological advances coupled with large sample sets have uncovered many factors underlying the genetic basis of traits and the predisposition to complex disease, but much is left to discover. A common thread to most genetic investigations is familial relationships. Close relatives can be identified from family records, and more distant relatives can be inferred from large panels of genetic markers. Unfortunately these empirical estimates can be noisy, especially regarding distant relatives. We propose a new method for denoising genetically—inferred relationship matrices by exploiting the underlying structure due to hierarchical groupings of correlated individuals. The approach, which we call Treelet Covariance Smoothing, employs a multiscale decomposition of covariance matrices to improve estimates of pairwise relationships. On both simulated and real data, we show that smoothing leads to better estimates of the relatedness amongst distantly related individuals. We illustrate our method with a large genome-wide association study and estimate the “heritability” of body mass index quite accurately. Traditionally heritability, defined as the fraction of the total trait variance attributable to additive genetic effects, is estimated from samples of closely related individuals using random effects models. We show that by using smoothed relationship matrices we can estimate heritability using population-based samples. Finally, while our methods have been developed for refining genetic relationship matrices and improving estimates of heritability, they have much broader potential application in statistics. Most notably, for error-in-variables random effects models and settings that require regularization of matrices with block or hierarchical structure. PMID:24587841
REFINING GENETICALLY INFERRED RELATIONSHIPS USING TREELET COVARIANCE SMOOTHING.
Crossett, Andrew; Lee, Ann B; Klei, Lambertus; Devlin, Bernie; Roeder, Kathryn
2013-06-27
Recent technological advances coupled with large sample sets have uncovered many factors underlying the genetic basis of traits and the predisposition to complex disease, but much is left to discover. A common thread to most genetic investigations is familial relationships. Close relatives can be identified from family records, and more distant relatives can be inferred from large panels of genetic markers. Unfortunately these empirical estimates can be noisy, especially regarding distant relatives. We propose a new method for denoising genetically-inferred relationship matrices by exploiting the underlying structure due to hierarchical groupings of correlated individuals. The approach, which we call Treelet Covariance Smoothing, employs a multiscale decomposition of covariance matrices to improve estimates of pairwise relationships. On both simulated and real data, we show that smoothing leads to better estimates of the relatedness amongst distantly related individuals. We illustrate our method with a large genome-wide association study and estimate the "heritability" of body mass index quite accurately. Traditionally heritability, defined as the fraction of the total trait variance attributable to additive genetic effects, is estimated from samples of closely related individuals using random effects models. We show that by using smoothed relationship matrices we can estimate heritability using population-based samples. Finally, while our methods have been developed for refining genetic relationship matrices and improving estimates of heritability, they have much broader potential application in statistics. Most notably, for error-in-variables random effects models and settings that require regularization of matrices with block or hierarchical structure.
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.
Performance evaluation of sensor allocation algorithm based on covariance control
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
The covariance control capability of sensor allocation algorithms based on covariance control strategy is an important index to evaluate the performance of these algorithms. Owing to lack of standard performance metric indices to evaluate covariance control capability, sensor allocation ratio, etc, there are no guides to follow in the design procedure of sensor allocation algorithm in practical applications. To meet these demands, three quantified performance metric indices are presented, which are average covariance misadjustment quantity (ACMQ), average sensor allocation ratio (ASAR) and matrix metric influence factor (MMIF), where ACMQ, ASAR and MMIF quantify the covariance control capability, the usage of sensor resources and the robustness of sensor allocation algorithm, respectively. Meanwhile, a covariance adaptive sensor allocation algorithm based on a new objective function is proposed to improve the covariance control capability of the algorithm based on information gain. The experiment results show that the proposed algorithm have the advantage over the preceding sensor allocation algorithm in covariance control capability and robustness.
Covariant equations for the NN-πNN system
Phillips, D. R.; Afnan, I. R.
1995-05-01
We explain the deficiencies of the current NN-πNN equations, sketch the derivation of a set of covariant NN-πNN equations and describe the ways in which these equations differ from previous sets of covariant equations.
Symmetry and Covariance of Non-relativistic Quantum Mechanics
Omote, Minoru; kamefuchi, Susumu
2000-01-01
On the basis of a 5-dimensional form of space-time transformations non-relativistic quantum mechanics is reformulated in a manifestly covariant manner. The resulting covariance resembles that of the conventional relativistic quantum mechanics.
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
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.
Covariant Quantum Gravity with Continuous Quantum Geometry I: Covariant Hamiltonian Framework
Pilc, Marián
2016-01-01
The first part of the series is devoted to the formulation of the Einstein-Cartan Theory within the covariant hamiltonian framework. In the first section the general multisymplectic approach is revised and the notion of the d-jet bundles is introduced. Since the whole Standard Model Lagrangian (including gravity) can be written as the functional of the forms, the structure of the d-jet bundles is more appropriate for the covariant hamiltonian analysis than the standard jet bundle approach. The definition of the local covariant Poisson bracket on the space of covariant observables is recalled. The main goal of the work is to show that the gauge group of the Einstein-Cartan theory is given by the semidirect product of the local Lorentz group and the group of spacetime diffeomorphisms. Vanishing of the integral generators of the gauge group is equivalent to equations of motion of the Einstein-Cartan theory and the local covariant algebra generated by Noether's currents is closed Lie algebra.
Covariant gauges without Gribov ambiguities in Yang-Mills theories
Serreau, Julien; Tresmontant, Andréas
2013-01-01
We propose a formulation of a certain class of nonlinear covariant gauges as an extremization procedure that can be implemented on the lattice. At high energies, where the Gribov ambiguities can be ignored, this reduces to the Curci-Ferrari-Delbourgo-Jarvis gauges. We further propose a continuum formulation in terms of a local action which is free of Gribov ambiguities and avoids the Neuberger zero problem of the standard Faddeev-Popov construction. This involves an averaging over Gribov copies with a nonuniform weight, which introduces a new gauge-fixing parameter. We show that the proposed gauge-fixed action is perturbatively renormalizable in four dimensions and we provide explicit expressions of the renormalization factors at one loop. We discuss the possible implications of the present proposal for the calculation of Yang-Mills correlators.
Covariant gauges without Gribov ambiguities in Yang-Mills theories
Serreau, J.; Tissier, M.; Tresmontant, A.
2014-06-01
We propose a one-parameter family of nonlinear covariant gauges which can be formulated as an extremization procedure that may be amenable to lattice implementation. At high energies, where the Gribov ambiguities can be ignored, this reduces to the Curci-Ferrari-Delbourgo-Jarvis gauges. We further propose a continuum formulation in terms of a local action which is free of Gribov ambiguities and avoids the Neuberger zero problem of the standard Faddeev-Popov construction. This involves an averaging over Gribov copies with a nonuniform weight, which introduces a new gauge-fixing parameter. We show that the proposed gauge-fixed action is perturbatively renormalizable in four dimensions and we provide explicit expressions of the renormalization factors at one loop. We discuss the possible implications of the present proposal for the calculation of Yang-Mills correlators.
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.
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.
Koussoroplis, Apostolos-Manuel; Wacker, Alexander
2015-11-27
Understanding animal performance in heterogeneous or variable environments is a central question in ecology. We combine modelling and experiments to test how temperature and food availability variance jointly affect life-history traits of ectotherms. The model predicts that as mean temperatures move away from the ectotherm's thermal optimum, the effect size of joint thermal and food variance should become increasingly sensitive to their covariance. Below the thermal optimum, performance should be positively correlated with food-temperature covariance and the opposite is predicted above it. At lower temperatures, covariance should determine whether food and temperature variance increases or decreases performance compared to constant conditions. Somewhat stronger than predicted, the covariance effect below the thermal optimum was confirmed experimentally on an aquatic ectotherm (Daphnia magna) exposed to diurnal food and temperature variance with different amounts of covariance. Our findings have important implications for understanding ectotherm responses to climate-driven alterations of thermal mean and variance. © 2015 John Wiley & Sons Ltd/CNRS.
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.
Institute of Scientific and Technical Information of China (English)
Seung-Woo LEE; Dong-Kyou LEE
2011-01-01
Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper distribution of satellite-observed information in variational data assimilation. In the NMC (National Meteorological Center) method, background error covariances are underestimated over data-sparse regions such as an ocean because of small differences between different forecast times. Thus, it is necessary to reconstruct and tune the background error covariances so as to maximize the usefulness of the satellite data for the initial state of limited-area models, especially over an ocean where there is a lack of conventional data.In this study, we attempted to estimate background error covariances so as to provide adequate error statistics for data-sparse regions by using ensemble forecasts of optimal perturbations using bred vectors.The background error covariances estimated by the ensemble method reduced the overestimation of error amplitude obtained by the NMC method. By employing an appropriate horizontal length scale to exclude spurious correlations, the ensemble method produced better results than the NMC method in the assimilation of retrieved satellite data. Because the ensemble method distributes observed information over a limited local area, it would be more useful in the analysis of high-resolution satellite data. Accordingly, the performance of forecast models can be improved over the area where the satellite data are assimilated.
Quantum energy inequalities and local covariance II: categorical formulation
Fewster, Christopher J.
2007-11-01
We formulate quantum energy inequalities (QEIs) in the framework of locally covariant quantum field theory developed by Brunetti, Fredenhagen and Verch, which is based on notions taken from category theory. This leads to a new viewpoint on the QEIs, and also to the identification of a new structural property of locally covariant quantum field theory, which we call local physical equivalence. Covariant formulations of the numerical range and spectrum of locally covariant fields are given and investigated, and a new algebra of fields is identified, in which fields are treated independently of their realisation on particular spacetimes and manifestly covariant versions of the functional calculus may be formulated.
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.
Gallilei covariant quantum mechanics in electromagnetic fields
Directory of Open Access Journals (Sweden)
H. E. Wilhelm
1985-01-01
Full Text Available A formulation of the quantum mechanics of charged particles in time-dependent electromagnetic fields is presented, in which both the Schroedinger equation and wave equations for the electromagnetic potentials are Galilei covariant, it is shown that the Galilean relativity principle leads to the introduction of the electromagnetic substratum in which the matter and electromagnetic waves propagate. The electromagnetic substratum effects are quantitatively significant for quantum mechanics in reference frames, in which the substratum velocity w is in magnitude comparable with the velocity of light c. The electromagnetic substratum velocity w occurs explicitly in the wave equations for the electromagnetic potentials but not in the Schroedinger equation.
Inferring Meta-covariates in Classification
Harris, Keith; McMillan, Lisa; Girolami, Mark
This paper develops an alternative method for gene selection that combines model based clustering and binary classification. By averaging the covariates within the clusters obtained from model based clustering, we define “meta-covariates” and use them to build a probit regression model, thereby selecting clusters of similarly behaving genes, aiding interpretation. This simultaneous learning task is accomplished by an EM algorithm that optimises a single likelihood function which rewards good performance at both classification and clustering. We explore the performance of our methodology on a well known leukaemia dataset and use the Gene Ontology to interpret our results.
Minimal covariant observables identifying all pure states
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.
Radiative Transfer in Special Relativity: Covariance
Duque, Mauricio; Duque, Carlos
2007-01-01
The purpose is to introduce in a clear and direct way the students of undergraduate courses in physics and/or astronomy to the subject of radiative transfer. A pedagogical revision is made in order to obtain the radiative transfer equation, its restrictions and the different types of interactions present between the radiation and the matter. Because in the classical literature about radiative transfer the covariance is not fully developed, we show in an explicit manner detail calculations and then we discuss the relativistic effects.
Covariant harmonic oscillators and coupled harmonic oscillators
Han, Daesoo; Kim, Young S.; Noz, Marilyn E.
1995-01-01
It is shown that the system of two coupled harmonic oscillators shares the basic symmetry properties with the covariant harmonic oscillator formalism which provides a concise description of the basic features of relativistic hadronic features observed in high-energy laboratories. It is shown also that the coupled oscillator system has the SL(4,r) symmetry in classical mechanics, while the present formulation of quantum mechanics can accommodate only the Sp(4,r) portion of the SL(4,r) symmetry. The possible role of the SL(4,r) symmetry in quantum mechanics is discussed.
Directory of Open Access Journals (Sweden)
Berge Léonie
2016-01-01
Full Text Available As the need for precise handling of nuclear data covariances grows ever stronger, no information about covariances of prompt fission neutron spectra (PFNS are available in the evaluated library JEFF-3.2, although present in ENDF/B-VII.1 and JENDL-4.0 libraries for the main fissile isotopes. The aim of this work is to provide an estimation of covariance matrices related to PFNS, in the frame of some commonly used models for the evaluated files, such as the Maxwellian spectrum, the Watt spectrum, or the Madland-Nix spectrum. The evaluation of PFNS through these models involves an adjustment of model parameters to available experimental data, and the calculation of the spectrum variance-covariance matrix arising from experimental uncertainties. We present the results for thermal neutron induced fission of 235U. The systematic experimental uncertainties are propagated via the marginalization technique available in the CONRAD code. They are of great influence on the final covariance matrix, and therefore, on the spectrum uncertainty band width. In addition to this covariance estimation work, we have also investigated the importance on a reactor calculation of the fission spectrum model choice. A study of the vessel fluence depending on the PFNS model is presented. This is done through the propagation of neutrons emitted from a fission source in a simplified PWR using the TRIPOLI-4® code. This last study includes thermal fission spectra from the FIFRELIN Monte-Carlo code dedicated to the simulation of prompt particles emission during fission.
Berge, Léonie; Litaize, Olivier; Serot, Olivier; Archier, Pascal; De Saint Jean, Cyrille; Pénéliau, Yannick; Regnier, David
2016-02-01
As the need for precise handling of nuclear data covariances grows ever stronger, no information about covariances of prompt fission neutron spectra (PFNS) are available in the evaluated library JEFF-3.2, although present in ENDF/B-VII.1 and JENDL-4.0 libraries for the main fissile isotopes. The aim of this work is to provide an estimation of covariance matrices related to PFNS, in the frame of some commonly used models for the evaluated files, such as the Maxwellian spectrum, the Watt spectrum, or the Madland-Nix spectrum. The evaluation of PFNS through these models involves an adjustment of model parameters to available experimental data, and the calculation of the spectrum variance-covariance matrix arising from experimental uncertainties. We present the results for thermal neutron induced fission of 235U. The systematic experimental uncertainties are propagated via the marginalization technique available in the CONRAD code. They are of great influence on the final covariance matrix, and therefore, on the spectrum uncertainty band width. In addition to this covariance estimation work, we have also investigated the importance on a reactor calculation of the fission spectrum model choice. A study of the vessel fluence depending on the PFNS model is presented. This is done through the propagation of neutrons emitted from a fission source in a simplified PWR using the TRIPOLI-4® code. This last study includes thermal fission spectra from the FIFRELIN Monte-Carlo code dedicated to the simulation of prompt particles emission during fission.
Employment of the covariance matrix in parameter estimation for stochastic processes in cell biology
Preuss, R.; Dieterich, P.
2013-08-01
The dynamics of movements of biological cells can be described with models from correlated stochastic processes. In order to overcome problems from correlated and insufficient data in the determination of the model parameters of such processes we employ the covariance matrix of the data. Since the covariance suffers itself from statistical uncertainty it is corrected by a renormalization treatment [1]. For the example of normal and fractional Brownian motion, which allows both to access all quantities on full theoretical grounds and to generate data similar to experiment, we discuss our results and those of previous works by Gregory [2] and Sivia [3]. The presented approach has the potential to estimate the aging correlation function of observed cell paths and can be applied to more complicated models.
Shrinkage covariance matrix approach for microarray data
Karjanto, Suryaefiza; Aripin, Rasimah
2013-04-01
Microarray technology was developed for the purpose of monitoring the expression levels of thousands of genes. A microarray data set typically consists of tens of thousands of genes (variables) from just dozens of samples due to various constraints including the high cost of producing microarray chips. As a result, the widely used standard covariance estimator is not appropriate for this purpose. One such technique is the Hotelling's T2 statistic which is a multivariate test statistic for comparing means between two groups. It requires that the number of observations (n) exceeds the number of genes (p) in the set but in microarray studies it is common that n Hotelling's T2 statistic with the shrinkage approach is proposed to estimate the covariance matrix for testing differential gene expression. The performance of this approach is then compared with other commonly used multivariate tests using a widely analysed diabetes data set as illustrations. The results across the methods are consistent, implying that this approach provides an alternative to existing techniques.
Covariant Entropy Bound and Padmanabhan's Emergent Paradigm
Hadi, H; Darabi, F
2016-01-01
The covariant entropy conjecture is invariant under time reversal and consequently its origin must be statistical rather than thermodynamical. This may impose a fundamental constraint on the number of degrees of freedom in nature. Indeed, the covariant entropy bound imposes an upper entropy bound for any physical system. Considering a cosmological system, we show that Padmanabhan's emergent paradigm, which indicates that the emergence of cosmic space is due to the discrepancy between the surface and bulk degrees of freedom, leads to a lower entropy bound. The lower and upper entropy bounds may coincide on the apparent horizon for the radiation field and dark energy with the equations of state $\\omega=\\frac{1}{3}$ and $\\omega=-1$, respectively. Moreover, the maximal entropy inside the apparent horizon occurs when it is filled completely by the radiation field or dark energy. It turns out that for dark energy case (pure de Sitter space)\\ the holographic principle is satisfied in the sense that the number of deg...
Stochastic precipitation generator with hidden state covariates
Kim, Yongku; Lee, GyuWon
2017-08-01
Time series of daily weather such as precipitation, minimum temperature and maximum temperature are commonly required for various fields. Stochastic weather generators constitute one of the techniques to produce synthetic daily weather. The recently introduced approach for stochastic weather generators is based on generalized linear modeling (GLM) with covariates to account for seasonality and teleconnections (e.g., with the El Niño). In general, stochastic weather generators tend to underestimate the observed interannual variance of seasonally aggregated variables. To reduce this overdispersion, we incorporated time series of seasonal dry/wet indicators in the GLM weather generator as covariates. These seasonal time series were local (or global) decodings obtained by a hidden Markov model of seasonal total precipitation and implemented in the weather generator. The proposed method is applied to time series of daily weather from Seoul, Korea and Pergamino, Argentina. This method provides a straightforward translation of the uncertainty of the seasonal forecast to the corresponding conditional daily weather statistics.
Arai, Kaori; Nakagawa, Yui; Iwata, Toyoto; Horiguchi, Hyogo; Murata, Katsuyuki
2013-01-01
To clarify the links between ECG QT-related parameters and heart rate variability (HRV) and the covariates possibly distorting them, the averaged RR and QT intervals in a single lead ECG were measured for 64 male and 86 female subjects aged 18-26. The QT index, defined by Rautaharju et al., in the young adults was not significantly related to any HRV parameters nor heart rate, but the Bazett's corrected QT (QTc) interval was associated negatively with the parasympathetic activity and positively with heart rate. No significant differences in the QTc interval, QT index or heart rate were seen between the men and women, but they significantly differed between both sexes after adjustment for possible covariates such as age and body mass index (BMI). Significant sex differences in parasympathetic parameters of the HRV were unchanged before and after the adjustment, but significant differences observed in the unadjusted sympathetic parameters disappeared after adjusting for covariates. Age, BMI and body fat percentage also were significant covariates affecting these ECG parameters. Consequently, QT index, unaffected by heart rate and HRV parameters, appears to be a more useful indicator than the QTc interval. Instead, the QT index and HRV parameters are recommended to be simultaneously measured in epidemiological research because they are probably complementary in assessing autonomic nervous function. Also, these parameters should be analyzed in men and women separately. Copyright © 2012 Elsevier B.V. All rights reserved.
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 with ...
Benchmarking Judgmentally Adjusted Forecasts
Ph.H.B.F. Franses (Philip Hans); L.P. de Bruijn (Bert)
2017-01-01
textabstractMany publicly available macroeconomic forecasts are judgmentally adjusted model-based forecasts. In practice, usually only a single final forecast is available, and not the underlying econometric model, nor are the size and reason for adjustment known. Hence, the relative weights given
Benchmarking judgmentally adjusted forecasts
Ph.H.B.F. Franses (Philip Hans); L.P. de Bruijn (Bert)
2015-01-01
markdownabstractMany publicly available macroeconomic forecasts are judgmentally-adjusted model-based forecasts. In practice usually only a single final forecast is available, and not the underlying econometric model, nor are the size and reason for adjustment known. Hence, the relative weights
Benchmarking judgmentally adjusted forecasts
Ph.H.B.F. Franses (Philip Hans); L.P. de Bruijn (Bert)
2015-01-01
markdownabstractMany publicly available macroeconomic forecasts are judgmentally-adjusted model-based forecasts. In practice usually only a single final forecast is available, and not the underlying econometric model, nor are the size and reason for adjustment known. Hence, the relative weights give
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)
Directory of Open Access Journals (Sweden)
Marcin Studnicki
2016-06-01
Full Text Available 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.
Parallel ICA identifies sub-components of resting state networks that covary with behavioral indices
Directory of Open Access Journals (Sweden)
Timothy eMeier
2012-10-01
Full Text Available Parallel Independent Component Analysis (para-ICA is a multivariate method that can identify complex relationships between different data modalities by simultaneously performing Independent Component Analysis on each data set while finding mutual information between the two data sets. We use para-ICA to test the hypothesis that spatial sub-components of common resting state networks (RSNs covary with specific behavioral measures. Resting state scans and a battery of behavioral indices were collected from 24 younger adults. Group ICA was performed and common RSNs were identified by spatial correlation to publically available templates. Nine RSNs were identified and para-ICA was run on each network with a matrix of behavioral measures serving as the second data type. Five networks had spatial sub-components that significantly correlated with behavioral components. These included a sub-component of the temporo-parietal attention network that differentially covaried with different trial-types of a sustained attention task, sub-components of default mode networks that covaried with attention and working memory tasks, and a sub-component of the bilateral frontal network that split the left inferior frontal gyrus into three clusters according to its cytoarchitecture that differentially covaried with working memory performance. Additionally, we demonstrate the validity of para-ICA in cases with unbalanced dimensions using simulated data.
Covariances of the few-group homogenized cross-sections for diffusion calculation
Energy Technology Data Exchange (ETDEWEB)
Sánchez-Cervera, S.; Castro, S.; García-Herranz, N.
2015-07-01
In the context of the NEA/OECD benchmark for Uncertainty Analysis in Modelling (UAM), Exercise I-3 consists of neutronic calculations to propagate uncertainties to core parameters such as k-effective or power distribution. In core simulators, the input uncertainties arise, among others, from few-group lattice-averaged cross-section uncertainties. In this paper, an analysis of those uncertainties due to nuclear data is performed. The core analyzed in Exercise I-3 is the initial loading of the PWR TMI-1, composed by 11 different types of fuel assemblies. By statistically sampling the nuclear data input, the sequence SAMPLER from SCALE system (using its NEWT lattice code) allows to obtain the few-group homogenized cross-sections and with a statistical analysis generates the covariance matrices. The correlations among different reactions and energy groups of the covariance matrices are analyzed. The impact of burnable poisons, control rods or the environment of the assembly is also assessed. It is shown the importance of the correlation between different assembly types. The global covariance matrix will permit to compute the uncertainties in k-eff in a core simulator, once sensitivity coefficients are known. Only if the complete covariance matrix is considered, similar uncertainties to the ones provided by other methodologies are obtained. (Author)
Bertram, Susan M; Fitzsimmons, Lauren P; McAuley, Emily M; Rundle, Howard D; Gorelick, Root
2012-01-01
The phenotypic variance-covariance matrix (P) describes the multivariate distribution of a population in phenotypic space, providing direct insight into the appropriateness of measured traits within the context of multicollinearity (i.e., do they describe any significant variance that is independent of other traits), and whether trait covariances restrict the combinations of phenotypes available to selection. Given the importance of P, it is therefore surprising that phenotypic covariances are seldom jointly analyzed and that the dimensionality of P has rarely been investigated in a rigorous statistical framework. Here, we used a repeated measures approach to quantify P separately for populations of four cricket species using seven acoustic signaling traits thought to enhance mate attraction. P was of full or almost full dimensionality in all four species, indicating that all traits conveyed some information that was independent of the other traits, and that phenotypic trait covariances do not constrain the combinations of signaling traits available to selection. P also differed significantly among species, although the dominant axis of phenotypic variation (p(max)) was largely shared among three of the species (Acheta domesticus, Gryllus assimilis, G. texensis), but different in the fourth (G. veletis). In G. veletis and A. domesticus, but not G. assimilis and G. texensis, p(max) was correlated with body size, while p(max) was not correlated with residual mass (a condition measure) in any of the species. This study reveals the importance of jointly analyzing phenotypic traits.
Lasso adjustments of treatment effect estimates in randomized experiments.
Bloniarz, Adam; Liu, Hanzhong; Zhang, Cun-Hui; Sekhon, Jasjeet S; Yu, Bin
2016-07-05
We provide a principled way for investigators to analyze randomized experiments when the number of covariates is large. Investigators often use linear multivariate regression to analyze randomized experiments instead of simply reporting the difference of means between treatment and control groups. Their aim is to reduce the variance of the estimated treatment effect by adjusting for covariates. If there are a large number of covariates relative to the number of observations, regression may perform poorly because of overfitting. In such cases, the least absolute shrinkage and selection operator (Lasso) may be helpful. We study the resulting Lasso-based treatment effect estimator under the Neyman-Rubin model of randomized experiments. We present theoretical conditions that guarantee that the estimator is more efficient than the simple difference-of-means estimator, and we provide a conservative estimator of the asymptotic variance, which can yield tighter confidence intervals than the difference-of-means estimator. Simulation and data examples show that Lasso-based adjustment can be advantageous even when the number of covariates is less than the number of observations. Specifically, a variant using Lasso for selection and ordinary least squares (OLS) for estimation performs particularly well, and it chooses a smoothing parameter based on combined performance of Lasso and OLS.
Estimating the power spectrum covariance matrix with fewer mock samples
Pearson, David W
2015-01-01
The covariance matrices of power-spectrum (P(k)) measurements from galaxy surveys are difficult to compute theoretically. The current best practice is to estimate covariance matrices by computing a sample covariance of a large number of mock catalogues. The next generation of galaxy surveys will require thousands of large volume mocks to determine the covariance matrices to desired accuracy. The errors in the inverse covariance matrix are larger and scale with the number of P(k) bins, making the problem even more acute. We develop a method of estimating covariance matrices using a theoretically justified, few-parameter model, calibrated with mock catalogues. Using a set of 600 BOSS DR11 mock catalogues, we show that a seven parameter model is sufficient to fit the covariance matrix of BOSS DR11 P(k) measurements. The covariance computed with this method is better than the sample covariance at any number of mocks and only ~100 mocks are required for it to fully converge and the inverse covariance matrix conver...
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.
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
Adjustment of Romanian Immigrant Students in a New Educational Context
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Aniella Mihaela VIERIU
2014-06-01
Full Text Available The present study focuses on the adjustment of Romanian immigrant students in emigration schools. The sample was comprised of 102 Romanian immigrant students, 40 male and 62 female, between the ages of 11 and 18, attending different schools in countries such as Spain, Italy and Belgium. Students’ adjustment was investigated by means of a questionnaire consisting of four subscales: linguistic adaptation, cultural adaptation, school adjustment and teacher-student relationship. Results indicate that while immigrant students have a satisfactory level of educational and linguistic adjustment, the social adjustment is less satisfactory. We also obtained correlations between linguistic adaptation and school adjustment, linguistic adaptation and social adaptation, linguistic adaptation and teacher-student relationship, school adjustment and social adaptation, school adjustment and teacher-student relationship, social adaptation and teacher-student relationship. Other correlations were found between the number of years that Romanian immigrant students spent in the host country and linguistic adaptation, school adjustment and teacher-student relationship.
Holographic bound in covariant loop quantum gravity
Tamaki, Takashi
2016-01-01
We investigate puncture statistics based on the covariant area spectrum in loop quantum gravity. First, we consider Maxwell-Boltzmann statistics with a Gibbs factor for punctures. We establish formulae which relate physical quantities such as horizon area to the parameter characterizing holographic degrees of freedom. We also perform numerical calculations and obtain consistency with these formulae. These results tell us that the holographic bound is satisfied in the large area limit and correction term of the entropy-area law can be proportional to the logarithm of the horizon area. Second, we also consider Bose-Einstein statistics and show that the above formulae are also useful in this case. By applying the formulae, we can understand intrinsic features of Bose-Einstein condensate which corresponds to the case when the horizon area almost consists of punctures in the ground state. When this phenomena occurs, the area is approximately constant against the parameter characterizing the temperature. When this ...
The covariance of GPS coordinates and frames
Lachièze-Rey, M
2006-01-01
We explore, in the general relativistic context, the properties of the recently introduced GPS coordinates, as well as those of the associated frames and coframes. We show that they are covariant, and completely independent of any observer. We show that standard spectroscopic and astrometric observations allow any observer to measure (i) the values of the GPS coordinates at his position, (ii) the components of his [four-]velocity and (iii) the components of the metric in the GPS frame. This provides to this system an unique value both for conceptual discussion (no frame dependence) and for practical use (involved quantities are directly measurable): localisation, motion monitoring, astrometry, cosmography, tests of gravitation theories. We show explicitly, in the general relativistic context, how an observer may estimate its position and motion, and reconstruct the components of the metric. This arises from two main results: the extension of the velocity fields of the probes to the whole (curved) spacetime; a...
Covariant Hyperbolization of Force-free Electrodynamics
Carrasco, Federico
2016-01-01
Force-Free Flectrodynamics (FFE) is a non-linear system of equations modeling the evolution of the electromagnetic field, in the presence of a magnetically dominated relativistic plasma. This configuration arises on several astrophysical scenarios, which represent exciting laboratories to understand physics in extreme regimes. We show that this system, when restricted to the correct constraint submanifold, is symmetric hyperbolic. In numerical applications is not feasible to keep the system in that submanifold, and so, it is necessary to analyze its structure first in the tangent space of that submanifold and then in a whole neighborhood of it. As already shown by Pfeiffer, a direct (or naive) formulation of this system (in the whole tangent space) results in a weakly hyperbolic system of evolution equations for which well-possednes for the initial value formulation does not follows. Using the generalized symmetric hyperbolic formalism due to Geroch, we introduce here a covariant hyperbolization for the FFE s...
Supergeometry in locally covariant quantum field theory
Hack, Thomas-Paul; Schenkel, Alexander
2015-01-01
In this paper we analyze supergeometric locally covariant quantum field theories. We develop suitable categories SLoc of super-Cartan supermanifolds, which generalize Lorentz manifolds in ordinary quantum field theory, and show that, starting from a few representation theoretic and geometric data, one can construct a functor A : SLoc --> S*Alg to the category of super-*-algebras which can be interpreted as a non-interacting super-quantum field theory. This construction turns out to disregard supersymmetry transformations as the morphism sets in the above categories are too small. We then solve this problem by using techniques from enriched category theory, which allows us to replace the morphism sets by suitable morphism supersets that contain supersymmetry transformations as their higher superpoints. We construct super-quantum field theories in terms of enriched functors eA : eSLoc --> eS*Alg between the enriched categories and show that supersymmetry transformations are appropriately described within the en...
Baryon Spectrum Analysis using Covariant Constraint Dynamics
Whitney, Joshua; Crater, Horace
2012-03-01
The energy spectrum of the baryons is determined by treating each of them as a three-body system with the interacting forces coming from a set of two-body potentials that depend on both the distance between the quarks and the spin and orbital angular momentum coupling terms. The Two Body Dirac equations of constraint dynamics derived by Crater and Van Alstine, matched with the quasipotential formalism of Todorov as the underlying two-body formalism are used, as well as the three-body constraint formalism of Sazdjian to integrate the three two-body equations into a single relativistically covariant three body equation for the bound state energies. The results are analyzed and compared to experiment using a best fit method and several different algorithms, including a gradient approach, and Monte Carlo method. Results for all well-known baryons are presented and compared to experiment, with good accuracy.
Noncommutative Spacetime Symmetries from Covariant Quantum Mechanics
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Alessandro Moia
2017-01-01
Full Text Available In the last decades, noncommutative spacetimes and their deformed relativistic symmetries have usually been studied in the context of field theory, replacing the ordinary Minkowski background with an algebra of noncommutative coordinates. However, spacetime noncommutativity can also be introduced into single-particle covariant quantum mechanics, replacing the commuting operators representing the particle’s spacetime coordinates with noncommuting ones. In this paper, we provide a full characterization of a wide class of physically sensible single-particle noncommutative spacetime models and the associated deformed relativistic symmetries. In particular, we prove that they can all be obtained from the standard Minkowski model and the usual Poincaré transformations via a suitable change of variables. Contrary to previous studies, we find that spacetime noncommutativity does not affect the dispersion relation of a relativistic quantum particle, but only the transformation properties of its spacetime coordinates under translations and Lorentz transformations.
Multisymplectic formalism and the covariant phase
Hélein, Frédéric
2011-01-01
The formulation of a relativistic dynamical problem as a system of Hamilton equations by respecting the principles of Relativity is a delicate task, because in their classical form the Hamilton equations require the use of a time coordinate, which of course contradicts the Relativity. Two interesting solutions have been proposed during the last century: the covariant phase space and the multisymplectic formalism. These two approaches were inspired at the beginning by different points of view. However, as shown by works by Kijowski-Szczyrba, Forger-Romero and Vitagliano, a synthetic vision of the two theories leads probably to the most satisfactory answer to the basic question of understanding the Hamiltonian structure of relativistic fields theory.
Universal Gravitation as Lorentz-covariant Dynamics
Kauffmann, Steven Kenneth
2014-01-01
Einstein's equivalence principle implies that the acceleration of a particle in a "specified" gravitational field is independent of its mass. While this is certainly true to great accuracy for bodies we observe in the Earth's gravitational field, a hypothetical body of mass comparable to the Earth's would perceptibly cause the Earth to fall toward it, which would feed back into the strength as a function of time of the Earth's gravitational field affecting that body. In short, Einstein's equivalence principle isn't exact, but is an approximation that ignores recoil of the "specified" gravitational field, which sheds light on why general relativity has no clearly delineated native embodiment of conserved four-momentum. Einstein's 1905 relativity of course doesn't have the inexactitudes he unwittingly built into GR, so it is natural to explore a Lorentz-covariant gravitational theory patterned directly on electromagnetism, wherein a system's zero-divergence overall stress-energy, including all gravitational fee...
Flavour Covariant Formalism for Resonant Leptogenesis
Dev, P S Bhupal; Pilaftsis, Apostolos; Teresi, Daniele
2014-01-01
We present a fully flavour-covariant formalism for transport phenomena and apply it to study the flavour-dynamics of Resonant Leptogenesis (RL). We show that this formalism provides a complete and unified description of RL, consistently accounting for three distinct physical phenomena: (i) resonant mixing and (ii) coherent oscillations between different heavy-neutrino flavours, as well as (iii) quantum decoherence effects in the charged-lepton sector. We describe the necessary emergence of higher-rank tensors in flavour space, arising from the unitarity cuts of partial self-energies. Finally, we illustrate the importance of this formalism within a minimal Resonant $\\tau$-Genesis model by showing that, with the inclusion of all flavour effects in a consistent way, the final lepton asymmetry can be enhanced by up to an order of magnitude, when compared to previous partially flavour-dependent treatments.
Correlation measurement of squeezed light
DEFF Research Database (Denmark)
Krivitsky, Leonid; Andersen, Ulrik Lund; Dong, R.;
2009-01-01
We study the implementation of a correlation measurement technique for the characterization of squeezed light which is nearly free of electronic noise. With two different sources of squeezed light, we show that the sign of the covariance coefficient, revealed from the time-resolved correlation data...
Subirà, Marta; Cano, Marta; de Wit, Stella J.; Alonso, Pino; Cardoner, Narcís; Hoexter, Marcelo Q.; Kwon, Jun Soo; Nakamae, Takashi; Lochner, Christine; Sato, João R.; Jung, Wi Hoon; Narumoto, Jin; Stein, Dan J.; Pujol, Jesus; Mataix-Cols, David; Veltman, Dick J.; Menchón, José M.; van den Heuvel, Odile A.; Soriano-Mas, Carles
2016-01-01
Background Frontostriatal and frontoamygdalar connectivity alterations in patients with obsessive–compulsive disorder (OCD) have been typically described in functional neuroimaging studies. However, structural covariance, or volumetric correlations across distant brain regions, also provides network-level information. Altered structural covariance has been described in patients with different psychiatric disorders, including OCD, but to our knowledge, alterations within frontostriatal and frontoamygdalar circuits have not been explored. Methods We performed a mega-analysis pooling structural MRI scans from the Obsessive–compulsive Brain Imaging Consortium and assessed whole-brain voxel-wise structural covariance of 4 striatal regions (dorsal and ventral caudate nucleus, and dorsal-caudal and ventral-rostral putamen) and 2 amygdalar nuclei (basolateral and centromedial-superficial). Images were preprocessed with the standard pipeline of voxel-based morphometry studies using Statistical Parametric Mapping software. Results Our analyses involved 329 patients with OCD and 316 healthy controls. Patients showed increased structural covariance between the left ventral-rostral putamen and the left inferior frontal gyrus/frontal operculum region. This finding had a significant interaction with age; the association held only in the subgroup of older participants. Patients with OCD also showed increased structural covariance between the right centromedial-superficial amygdala and the ventromedial prefrontal cortex. Limitations This was a cross-sectional study. Because this is a multisite data set analysis, participant recruitment and image acquisition were performed in different centres. Most patients were taking medication, and treatment protocols differed across centres. Conclusion Our results provide evidence for structural network–level alterations in patients with OCD involving 2 frontosubcortical circuits of relevance for the disorder and indicate that structural
... Public / Speech, Language and Swallowing / Disorders and Diseases Family Adjustment to Aphasia Richard S. was a senior manager ... It also presents a great challenge to the family. There may be tension among family members and ...
Remotely Adjustable Hydraulic Pump
Kouns, H. H.; Gardner, L. D.
1987-01-01
Outlet pressure adjusted to match varying loads. Electrohydraulic servo has positioned sleeve in leftmost position, adjusting outlet pressure to maximum value. Sleeve in equilibrium position, with control land covering control port. For lowest pressure setting, sleeve shifted toward right by increased pressure on sleeve shoulder from servovalve. Pump used in aircraft and robots, where hydraulic actuators repeatedly turned on and off, changing pump load frequently and over wide range.
Baryon Wave Functions in Covariant Relativistic Quark Models
Dillig, M
2002-01-01
We derive covariant baryon wave functions for arbitrary Lorentz boosts. Modeling baryons as quark-diquark systems, we reduce their manifestly covariant Bethe-Salpeter equation to a covariant 3-dimensional form by projecting on the relative quark-diquark energy. Guided by a phenomenological multigluon exchange representation of a covariant confining kernel, we derive for practical applications explicit solutions for harmonic confinement and for the MIT Bag Model. We briefly comment on the interplay of boosts and center-of-mass corrections in relativistic quark models.
Kriging approach for the experimental cross-section covariances estimation
Directory of Open Access Journals (Sweden)
Garlaud A.
2013-03-01
Full Text Available In the classical use of a generalized χ2 to determine the evaluated cross section uncertainty, we need the covariance matrix of the experimental cross sections. The usual propagation error method to estimate the covariances is hardly usable and the lack of data prevents from using the direct empirical estimator. We propose in this paper to apply the kriging method which allows to estimate the covariances via the distances between the points and with some assumptions on the covariance matrix structure. All the results are illustrated with the 2555Mn nucleus measurements.
Relativistic Covariance and Quark-Diquark Wave Functions
Dillig, M
2006-01-01
We derive covariant wave functions for hadrons composed of two constituents for arbitrary Lorentz boosts. Focussing explicitly on baryons as quark-diquark systems, we reduce their manifestly covariant Bethe-Salpeter equation to covariant 3-dimensional forms by projecting on the relative quark-diquark energy. Guided by a phenomenological multi gluon exchange representation of covariant confining kernels, we derive explicit solutions for harmonic confinement and for the MIT Bag Model. We briefly sketch implications of breaking the spherical symmetry of the ground state and the transition from the instant form to the light cone via the infinite momentum frame.
Weighted triangulation adjustment
Anderson, Walter L.
1969-01-01
The variation of coordinates method is employed to perform a weighted least squares adjustment of horizontal survey networks. Geodetic coordinates are required for each fixed and adjustable station. A preliminary inverse geodetic position computation is made for each observed line. Weights associated with each observed equation for direction, azimuth, and distance are applied in the formation of the normal equations in-the least squares adjustment. The number of normal equations that may be solved is twice the number of new stations and less than 150. When the normal equations are solved, shifts are produced at adjustable stations. Previously computed correction factors are applied to the shifts and a most probable geodetic position is found for each adjustable station. Pinal azimuths and distances are computed. These may be written onto magnetic tape for subsequent computation of state plane or grid coordinates. Input consists of punch cards containing project identification, program options, and position and observation information. Results listed include preliminary and final positions, residuals, observation equations, solution of the normal equations showing magnitudes of shifts, and a plot of each adjusted and fixed station. During processing, data sets containing irrecoverable errors are rejected and the type of error is listed. The computer resumes processing of additional data sets.. Other conditions cause warning-errors to be issued, and processing continues with the current data set.
Weighted triangulation adjustment
Anderson, Walter L.
1969-01-01
The variation of coordinates method is employed to perform a weighted least squares adjustment of horizontal survey networks. Geodetic coordinates are required for each fixed and adjustable station. A preliminary inverse geodetic position computation is made for each observed line. Weights associated with each observed equation for direction, azimuth, and distance are applied in the formation of the normal equations in-the least squares adjustment. The number of normal equations that may be solved is twice the number of new stations and less than 150. When the normal equations are solved, shifts are produced at adjustable stations. Previously computed correction factors are applied to the shifts and a most probable geodetic position is found for each adjustable station. Pinal azimuths and distances are computed. These may be written onto magnetic tape for subsequent computation of state plane or grid coordinates. Input consists of punch cards containing project identification, program options, and position and observation information. Results listed include preliminary and final positions, residuals, observation equations, solution of the normal equations showing magnitudes of shifts, and a plot of each adjusted and fixed station. During processing, data sets containing irrecoverable errors are rejected and the type of error is listed. The computer resumes processing of additional data sets.. Other conditions cause warning-errors to be issued, and processing continues with the current data set.
Design of DNA pooling to allow incorporation of covariates in rare variants analysis.
Directory of Open Access Journals (Sweden)
Weihua Guan
Full Text Available Rapid advances in next-generation sequencing technologies facilitate genetic association studies of an increasingly wide array of rare variants. To capture the rare or less common variants, a large number of individuals will be needed. However, the cost of a large scale study using whole genome or exome sequencing is still high. DNA pooling can serve as a cost-effective approach, but with a potential limitation that the identity of individual genomes would be lost and therefore individual characteristics and environmental factors could not be adjusted in association analysis, which may result in power loss and a biased estimate of genetic effect.For case-control studies, we propose a design strategy for pool creation and an analysis strategy that allows covariate adjustment, using multiple imputation technique.Simulations show that our approach can obtain reasonable estimate for genotypic effect with only slight loss of power compared to the much more expensive approach of sequencing individual genomes.Our design and analysis strategies enable more powerful and cost-effective sequencing studies of complex diseases, while allowing incorporation of covariate adjustment.
Social Support and Parental Adjustment to Pediatric Cancer.
Morrow, Gary R.; And Others
1981-01-01
Assessed the psychosocial adjustment of (N=107) parents whose children had cancer. Different patterns of association between 11 sources of social support and adjustment were found among groups of parents. Psychosocial adjustment of parents with a child in treatment was correlated more frequently with perceived social support. (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).
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
Energy Technology Data Exchange (ETDEWEB)
Alfred Stadler, Franz Gross
2010-10-01
We provide a short overview of the Covariant Spectator Theory and its applications. The basic ideas are introduced through the example of a {phi}{sup 4}-type theory. High-precision models of the two-nucleon interaction are presented and the results of their use in calculations of properties of the two- and three-nucleon systems are discussed. A short summary of applications of this framework to other few-body systems is also presented.
Energy Technology Data Exchange (ETDEWEB)
Bryan, M.F.; Piepel, G.F.; Simpson, D.B.
1996-03-01
The high-level waste (HLW) vitrification plant at the Hanford Site was being designed to transuranic and high-level radioactive waste in borosilicate class. Each batch of plant feed material must meet certain requirements related to plant performance, and the resulting class must meet requirements imposed by the Waste Acceptance Product Specifications. Properties of a process batch and the resultlng glass are largely determined by the composition of the feed material. Empirical models are being developed to estimate some property values from data on feed composition. Methods for checking and documenting compliance with feed and glass requirements must account for various types of uncertainties. This document focuses on the estimation. manipulation, and consequences of composition uncertainty, i.e., the uncertainty inherent in estimates of feed or glass composition. Three components of composition uncertainty will play a role in estimating and checking feed and glass properties: batch-to-batch variability, within-batch uncertainty, and analytical uncertainty. In this document, composition uncertainty and its components are treated in terms of variances and variance components or univariate situations, covariance matrices and covariance components for multivariate situations. The importance of variance and covariance components stems from their crucial role in properly estimating uncertainty In values calculated from a set of observations on a process batch. Two general types of methods for estimating uncertainty are discussed: (1) methods based on data, and (2) methods based on knowledge, assumptions, and opinions about the vitrification process. Data-based methods for estimating variances and covariance matrices are well known. Several types of data-based methods exist for estimation of variance components; those based on the statistical method analysis of variance are discussed, as are the strengths and weaknesses of this approach.
Contextualized Network Analysis: Theory and Methods for Networks with Node Covariates
Binkiewicz, Norbert M.
Biological and social systems consist of myriad interacting units. The interactions can be intuitively represented in the form of a graph or network. Measurements of these graphs can reveal the underlying structure of these interactions, which provides insight into the systems that generated the graphs. Moreover, in applications such as neuroconnectomics, social networks, and genomics, graph data is accompanied by contextualizing measures on each node. We leverage these node covariates to help uncover latent communities, using a modification of spectral clustering. Statistical guarantees are provided under a joint mixture model called the node contextualized stochastic blockmodel, including a bound on the mis-clustering rate. For most simulated conditions, covariate assisted spectral clustering yields superior results relative to both regularized spectral clustering without node covariates and an adaptation of canonical correlation analysis. We apply covariate assisted spectral clustering to large brain graphs derived from diffusion MRI, using the node locations or neurological regions as covariates. In both cases, covariate assisted spectral clustering yields clusters that are easier to interpret neurologically. A low rank update algorithm is developed to reduce the computational cost of determining the tuning parameter for covariate assisted spectral clustering. As simulations demonstrate, the low rank update algorithm increases the speed of covariate assisted spectral clustering up to ten-fold, while practically matching the clustering performance of the standard algorithm. Graphs with node attributes are sometimes accompanied by ground truth labels that align closely with the latent communities in the graph. We consider the example of a mouse retina neuron network accompanied by the neuron spatial location and neuronal cell types. In this example, the neuronal cell type is considered a ground truth label. Current approaches for defining neuronal cell type vary
Covariant and quasi-covariant quantum dynamics in Robertson-Walker space-times
Buchholz, D; Summers, S J; Buchholz, Detlev; Mund, Jens; Summers, Stephen J.
2002-01-01
We propose a canonical description of the dynamics of quantum systems on a class of Robertson-Walker space-times. We show that the worldline of an observer in such space-times determines a unique orbit in the local conformal group SO(4,1) of the space-time and that this orbit determines a unique transport on the space-time. For a quantum system on the space-time modeled by a net of local algebras, the associated dynamics is expressed via a suitable family of ``propagators''. In the best of situations, this dynamics is covariant, but more typically the dynamics will be ``quasi-covariant'' in a sense we make precise. We then show by using our technique of ``transplanting'' states and nets of local algebras from de Sitter space to Robertson-Walker space that there exist quantum systems on Robertson-Walker spaces with quasi-covariant dynamics. The transplanted state is locally passive, in an appropriate sense, with respect to this dynamics.
Khoury, Justin; Tolley, Andrew J
2014-01-01
Traditional derivations of general relativity from the graviton degrees of freedom assume space-time Lorentz covariance as an axiom. In this essay, we survey recent evidence that general relativity is the unique spatially-covariant effective field theory of the transverse, traceless graviton degrees of freedom. The Lorentz covariance of general relativity, having not been assumed in our analysis, is thus plausibly interpreted as an accidental or emergent symmetry of the gravitational sector. From this point of view, Lorentz covariance is a necessary feature of low-energy graviton dynamics, not a property of space-time. This result has revolutionary implications for fundamental physics.
Electromagnetic structure of the Delta baryon within the covariant spectator theory
Energy Technology Data Exchange (ETDEWEB)
M. T. Pena, G. Ramalho, Franz Gross
2010-12-01
We calculated all the electromagnetic observables for the nucleon and its lowest-lying Delta(1232) excitation within a constituent quark model for those two baryons based on the covariant spectator theory. Once the reactions gamma N \\to N and gamma N \\to Delta were described, we predicted without further adjusting of parameters the four electromagnetic Delta form factors: the electric charge G_{E0}, the magnetic dpole G_{M1}, the electric quadrupole G_{E2} and the magnetic octupole G_{M3}. The results are compatible with the available experimental data and recent lattice QCD data.
Zhang, Xuguang; Zhang, Yun; Zhang, Jie; Chen, Shengyong; Chen, Dan; Li, Xiaoli
2012-04-01
Toward the unsupervised clustering for color logo images corrupted by noise, we propose a novel framework in which the logo images are described by a model called singular values based region covariance matrices (SVRCM), and the mean shift algorithm is performed on Lie groups for clustering covariance matrices. To decrease the influence of noise, we choose the larger singular values, which can better represent the original image and discard the smaller singular values. Therefore, the chosen singular values are grouped and fused by a covariance matrix to form a SVRCM model that can represent the correlation and variance between different singular value features to enhance the discriminating ability of the model. In order to cluster covariance matrices, which do not lie on Euclidean space, the mean shift algorithm is performed on manifolds by iteratively transforming points between the Lie group and Lie algebra. Experimental results on 38 categories of logo images demonstrate the superior performance of the proposed method whose clustering rate can be achieved at 88.55%.
Information content of weak lensing bispectrum: including the non-Gaussian error covariance matrix
Kayo, Issha; Jain, Bhuvnesh
2013-01-01
We address a long-standing problem, how can we extract information in the non-Gaussian regime of weak lensing surveys, by accurate modeling of all relevant covariances between the power spectra and bispectra. We use 1000 ray-tracing simulation realizations for a Lambda-CDM model and an analytical halo model. We develop a formalism to describe the covariance matrices of power spectra and bispectra of all triangle configurations, which extend to 6-point correlation functions. We include a new contribution arising from coupling of the lensing Fourier modes with large-scale mass fluctuations on scales comparable with the survey region via halo bias theory, which we call the halo sample variance (HSV) effect. We show that the model predictions are in excellent agreement with the simulation results for the power spectrum and bispectrum covariances. The HSV effect gives a dominant contribution to the covariances at multipoles l > 10^3, which arise from massive halos with masses of about 10^14 solar masses and at rel...
Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates
Patino, Reynaldo; VanLandeghem, Matthew M.; Denny, Shawn
2016-01-01
Golden alga (Prymnesium parvum) is a toxic haptophyte that has caused considerable ecological damage to marine and inland aquatic ecosystems worldwide. Studies focused primarily on laboratory cultures have indicated that toxicity is poorly correlated with the abundance of golden alga cells. This relationship, however, has not been rigorously evaluated in the field where environmental conditions are much different. The ability to predict toxicity using readily measured environmental variables and golden alga abundance would allow managers rapid assessments of ichthyotoxicity potential without laboratory bioassay confirmation, which requires additional resources to accomplish. To assess the potential utility of these relationships, several a priori models relating lethal levels of golden alga ichthyotoxicity to golden alga abundance and environmental covariates were constructed. Model parameters were estimated using archived data from four river basins in Texas and New Mexico (Colorado, Brazos, Red, Pecos). Model predictive ability was quantified using cross-validation, sensitivity, and specificity, and the relative ranking of environmental covariate models was determined by Akaike Information Criterion values and Akaike weights. Overall, abundance was a generally good predictor of ichthyotoxicity as cross validation of golden alga abundance-only models ranged from ∼ 80% to ∼ 90% (leave-one-out cross-validation). Environmental covariates improved predictions, especially the ability to predict lethally toxic events (i.e., increased sensitivity), and top-ranked environmental covariate models differed among the four basins. These associations may be useful for monitoring as well as understanding the abiotic factors that influence toxicity during blooms.
Covariation between eumelanic pigmentation and body mass only under specific conditions
Roulin, Alexandre
2009-03-01
Identifying the factors that mediate covariation between an ornament and other phenotypic attributes is important to determine the signaling function of ornaments. Sign and magnitude of a covariation may vary across environments if the expression of the ornament or of its linked genes regulating correlated phenotypes is condition-dependent. I investigated in the barn owl Tyto alba whether sign and magnitude of covariation between body mass and two heritable melanin-based plumage ornaments change with food supply, along the reproductive cycle and from the morning to the evening. Using a dataset of 1,848 measurements of body mass in 336 breeding females, I found that females displaying large black spots were heavier than conspecifics with smaller spots in the afternoon (i.e., a long time after the last feeding) but not in the morning (i.e., a short time after the last feeding). This is consistent with the recently proposed hypothesis that eumelanin-based ornaments are associated with the ability to maintain energy balance between food intake and energy expenditure. Thus, covariation between melanin-based coloration and body mass can be detected only under specific conditions potentially explaining why it has been reported in only ten out of 28 vertebrate species. The proposition that ornamented individuals achieve a higher fitness than drab conspecifics only in specific environments should be tested for other ornaments.
Structural covariance in the hallucinating brain: a voxel-based morphometry study
Modinos, Gemma; Vercammen, Ans; Mechelli, Andrea; Knegtering, Henderikus; McGuire, Philip K.; Aleman, André
2009-01-01
Background Neuroimaging studies have indicated that a number of cortical regions express altered patterns of structural covariance in schizophrenia. The relation between these alterations and specific psychotic symptoms is yet to be investigated. We used voxel-based morphometry to examine regional grey matter volumes and structural covariance associated with severity of auditory verbal hallucinations. Methods We applied optimized voxel-based morphometry to volumetric magnetic resonance imaging data from 26 patients with medication-resistant auditory verbal hallucinations (AVHs); statistical inferences were made at p < 0.05 after correction for multiple comparisons. Results Grey matter volume in the left inferior frontal gyrus was positively correlated with severity of AVHs. Hallucination severity influenced the pattern of structural covariance between this region and the left superior/middle temporal gyri, the right inferior frontal gyrus and hippocampus, and the insula bilaterally. Limitations The results are based on self-reported severity of auditory hallucinations. Complementing with a clinician-based instrument could have made the findings more compelling. Future studies would benefit from including a measure to control for other symptoms that may covary with AVHs and for the effects of antipsychotic medication. Conclusion The results revealed that overall severity of AVHs modulated cortical intercorrelations between frontotemporal regions involved in language production and verbal monitoring, supporting the critical role of this network in the pathophysiology of hallucinations. PMID:19949723
Jacobs, Jesse V; Lyman, Courtney A; Hitt, Juvena R; Henry, Sharon M
2017-08-01
People with low back pain exhibit altered postural coordination that has been suggested as a target for treatment, but heterogeneous presentation has rendered it difficult to identify appropriate candidates and protocols for such treatments. This study evaluated the associations of task-related and person-related factors with the effect of low back pain on anticipatory postural adjustments. Thirteen subjects with and 13 without low back pain performed seated, rapid arm flexion in self-initiated and cued conditions. Mixed-model ANOVA were used to evaluate group and condition effects on APA onset latencies of trunk muscles, arm-raise velocity, and pre-movement cortical potentials. These measures were evaluated for correlation with pain ratings, Fear Avoidance Beliefs Questionnaire scores, and Modified Oswestry Questionnaire scores. Delayed postural adjustments of subjects with low back pain were greater in the cued condition than in the self-initiated condition. The group with low back pain exhibited larger-amplitude cortical potentials than the group without pain, but also significantly slower arm-raise velocities. With arm-raise velocity as a covariate, the effect of low back pain remained significant for the latencies of postural adjustments but not for cortical potentials. Latencies of the postural adjustments significantly correlated with Oswestry and Fear Avoidance Beliefs scores. Delayed postural adjustments with low back pain appear to be influenced by cueing of movement, pain-related disability and fear of activity. These results highlight the importance of subject characteristics, task condition, and task performance when comparing across studies or when developing treatment of people with low back pain. Copyright © 2017 Elsevier B.V. All rights reserved.
Predicting Covariance Matrices with Financial Conditions Indexes
A. Opschoor (Anne); D.J.C. van Dijk (Dick); M. van der Wel (Michel)
2013-01-01
textabstractWe model the impact of financial conditions on asset market volatility and correlation. We propose extensions of (factor-)GARCH models for volatility and DCC models for correlation that allow for including indexes that measure financial conditions. In our empirical application we
Predicting Covariance Matrices with Financial Conditions Indexes
A. Opschoor (Anne); D.J.C. van Dijk (Dick); M. van der Wel (Michel)
2013-01-01
textabstractWe model the impact of financial conditions on asset market volatility and correlation. We propose extensions of (factor-)GARCH models for volatility and DCC models for correlation that allow for including indexes that measure financial conditions. In our empirical application we conside
Role of Osmotic Adjustment in Plant Productivity
Energy Technology Data Exchange (ETDEWEB)
Gebre, G.M.
2001-01-11
Successful implementation of short rotation woody crops requires that the selected species and clones be productive, drought tolerant, and pest resistant. Since water is one of the major limiting factors in poplar (Populus sp.) growth, there is little debate for the need of drought tolerant clones, except on the wettest of sites (e.g., lower Columbia River delta). Whether drought tolerance is compatible with productivity remains a debatable issue. Among the many mechanisms of drought tolerance, dehydration postponement involves the maintenance of high leaf water potential due to, for example, an adequate root system. This trait is compatible with productivity, but requires available soil moisture. When the plant leaf water potential and soil water content decline, the plant must be able to survive drought through dehydration tolerance mechanisms, such as low osmotic potential or osmotic adjustment. Osmotic adjustment and low osmotic potential are considered compatible with growth and yield because they aid in the maintenance of leaf turgor. However, it has been shown that turgor alone does not regulate cell expansion or stomatal conductance and, therefore, the role of osmotic adjustment is debated. Despite this finding, osmotic adjustment has been correlated with grain yield in agronomic crop species, and gene markers responsible for osmotic adjustment are being investigated to improve drought tolerance in productive progenies. Although osmotic adjustment and low osmotic potentials have been investigated in several forest tree species, few studies have investigated the relationship between osmotic adjustment and growth. Most of these studies have been limited to greenhouse or container-grown plants. Osmotic adjustment and rapid growth have been specifically associated in Populus and black spruce (Picea mariuna (Mill.) B.S.P.) progenies. We tested whether these relationships held under field conditions using several poplar clones. In a study of two hybrid poplar
A fully covariant description of CMB anisotropies
Dunsby, P K S
1997-01-01
Starting from the exact non-linear description of matter and radiation, a fully covariant and gauge-invariant formula for the observed temperature anisotropy of the cosmic microwave background (CBR) radiation, expressed in terms of the electric ($E_{ab}$) and magnetic ($H_{ab}$) parts of the Weyl tensor, is obtained by integrating photon geodesics from last scattering to the point of observation today. This improves and extends earlier work by Russ et al where a similar formula was obtained by taking first order variations of the redshift. In the case of scalar (density) perturbations, $E_{ab}$ is related to the harmonic components of the gravitational potential $\\Phi_k$ and the usual dominant Sachs-Wolfe contribution $\\delta T_R/\\bar{T}_R\\sim\\Phi_k$ to the temperature anisotropy is recovered, together with contributions due to the time variation of the potential (Rees-Sciama effect), entropy and velocity perturbations at last scattering and a pressure suppression term important in low density universes. We a...
General Covariance from the Quantum Renormalization Group
Shyam, Vasudev
2016-01-01
The Quantum renormalization group (QRG) is a realisation of holography through a coarse graining prescription that maps the beta functions of a quantum field theory thought to live on the `boundary' of some space to holographic actions in the `bulk' of this space. A consistency condition will be proposed that translates into general covariance of the gravitational theory in the $D + 1$ dimensional bulk. This emerges from the application of the QRG on a planar matrix field theory living on the $D$ dimensional boundary. This will be a particular form of the Wess--Zumino consistency condition that the generating functional of the boundary theory needs to satisfy. In the bulk, this condition forces the Poisson bracket algebra of the scalar and vector constraints of the dual gravitational theory to close in a very specific manner, namely, the manner in which the corresponding constraints of general relativity do. A number of features of the gravitational theory will be fixed as a consequence of this form of the Po...
New covariant Lagrange formulation for field theories
Ootsuka, T
2012-01-01
A novel approach for Lagrange formulation for field theories is proposed in terms of Kawaguchi geometry (areal metric space). On the extended configuration space M for classical field theory composed of spacetime and field configuration space, one can define a geometrical structure called Kawaguchi areal metric K from the field Lagrangian and (M,K) can be regarded as Kawaguchi manifold. The geometrical action functional is given by K and the dynamics of field is determined by covariant Euler-Lagrange equation derived from the variational principle of the action. The solution to the equation becomes a minimal hypersurface on (M,K) which has the same dimension as spacetime. We propose that this hypersurface is what we should regard as our real spacetime manifold, while the usual way to understand spacetime is to consider it as the parameter spacetime (base manifold) of a fibre bundle. In this way, the dynamics of field and spacetime structure is unified by Kawaguchi geometry. The theory has the property of stro...
Historical Hamiltonian Dynamics: symplectic and covariant
Lachieze-Rey, M
2016-01-01
This paper presents a "historical" formalism for dynamical systems, in its Hamiltonian version (Lagrangian version was presented in a previous paper). It is universal, in the sense that it applies equally well to time dynamics and to field theories on space-time. It is based on the notion of (Hamiltonian) histories, which are sections of the (extended) phase space bundle. It is developed in the space of sections, in contradistinction with the usual formalism which works in the bundle manifold. In field theories, the formalism remains covariant and does not require a spitting of space-time. It considers space-time exactly in the same manner than time in usual dynamics, both being particular cases of the evolution domain. It applies without modification when the histories (the fields) are forms rather than scalar functions, like in electromagnetism or in tetrad general relativity. We develop a differential calculus in the infinite dimensional space of histories. It admits a (generalized) symplectic form which d...
The covariance of GPS coordinates and frames
Energy Technology Data Exchange (ETDEWEB)
Lachieze-Rey, Marc [CNRS APC, UMR 7164 Service d' Astrophysique, CE Saclay, 91191 Gif sur Yvette Cedex (France)
2006-05-21
We explore, in the general relativistic context, the properties of the recently introduced global positioning system (GPS) coordinates, as well as those of the associated frames and coframes that they define. We show that they are covariant and completely independent of any observer. We show that standard spectroscopic and astrometric observations allow any observer to measure (i) the values of the GPS coordinates at his position (ii) the components of his 4-velocity and (iii) the components of the metric in the GPS frame. This provides this system with a unique value both for conceptual discussion (no frame dependence) and for practical use (involved quantities are directly measurable): localization, motion monitoring, astrometry, cosmography and tests of gravitation theories. We show explicitly, in the general relativistic context, how an observer may estimate his position and motion, and reconstruct the components of the metric. This arises from two main results: the extension of the velocity fields of the probes to the whole (curved) spacetime, and the identification of the components of the observer's velocity in the GPS frame with the (inversed) observed redshifts of the probes. Specific cases (non-relativistic velocities, Minkowski and Friedmann-Lemaitre spacetimes, geodesic motions) are studied in detail.
Schwinger mechanism in linear covariant gauges
Aguilar, A C; Papavassiliou, J
2016-01-01
In this work we explore the applicability of a special gluon mass generating mechanism in the context of the linear covariant gauges. In particular, the implementation of the Schwinger mechanism in pure Yang-Mills theories hinges crucially on the inclusion of massless bound-state excitations in the fundamental nonperturbative vertices of the theory. The dynamical formation of such excitations is controlled by a homogeneous linear Bethe-Salpeter equation, whose nontrivial solutions have been studied only in the Landau gauge. Here, the form of this integral equation is derived for general values of the gauge-fixing parameter, under a number of simplifying assumptions that reduce the degree of technical complexity. The kernel of this equation consists of fully-dressed gluon propagators, for which recent lattice data are used as input, and of three-gluon vertices dressed by a single form factor, which is modelled by means of certain physically motivated Ans\\"atze. The gauge-dependent terms contributing to this ke...
Comparison between covariant and orthogonal Lyapunov vectors.
Yang, Hong-liu; Radons, Günter
2010-10-01
Two sets of vectors, covariant Lyapunov vectors (CLVs) and orthogonal Lyapunov vectors (OLVs), are currently used to characterize the linear stability of chaotic systems. A comparison is made to show their similarity and difference, especially with respect to the influence on hydrodynamic Lyapunov modes (HLMs). Our numerical simulations show that in both Hamiltonian and dissipative systems HLMs formerly detected via OLVs survive if CLVs are used instead. Moreover, the previous classification of two universality classes works for CLVs as well, i.e., the dispersion relation is linear for Hamiltonian systems and quadratic for dissipative systems, respectively. The significance of HLMs changes in different ways for Hamiltonian and dissipative systems with the replacement of OLVs with CLVs. For general dissipative systems with nonhyperbolic dynamics the long-wavelength structure in Lyapunov vectors corresponding to near-zero Lyapunov exponents is strongly reduced if CLVs are used instead, whereas for highly hyperbolic dissipative systems the significance of HLMs is nearly identical for CLVs and OLVs. In contrast the HLM significance of Hamiltonian systems is always comparable for CLVs and OLVs irrespective of hyperbolicity. We also find that in Hamiltonian systems different symmetry relations between conjugate pairs are observed for CLVs and OLVs. Especially, CLVs in a conjugate pair are statistically indistinguishable in consequence of the microreversibility of Hamiltonian systems. Transformation properties of Lyapunov exponents, CLVs, and hyperbolicity under changes of coordinate are discussed in appendices.
Covariance and objectivity in mechanics and turbulence
Frewer, Michael
2016-01-01
Form-invariance (covariance) and frame-indifference (objectivity) are two notions in classical continuum mechanics which have attracted much attention and controversy over the past decades. Particularly in turbulence modelling it seems that there still is a need for clarification. The aim and purpose of this study is fourfold: (i) To achieve consensus in general on definitions and principles when trying to establish an invariant theory for modelling constitutive structures and dynamic processes in mechanics, where special focus is put on the principle of Material Frame-Indifference (MFI). (ii) To show that in constitutive modelling MFI can only be regarded as an approximation that needs to be reduced to a weaker statement when trying to advance it to an axiom of nature. (iii) To convince that in dynamical modelling, as in turbulence, MFI may not be utilized as a modelling guideline, not even in an approximative sense. Instead, its reduced form has to be supplemented by a second, independent axiom that include...
Frame Indifferent (Truly Covariant) Formulation of Electrodynamics
Christov, Christo
2010-10-01
The Electromagnetic field is considered from the point of view of mechanics of continuum. It is shown that Maxwell's equations are mathematically strict corollaries form the equation of motions of an elastic incompressible liquid. If the concept of frame-indifference (material invariance) is applied to the model of elastic liquid, then the partial time derivatives have to be replaced by the convective time derivative in the momentum equations, and by the Oldroyd upper-convected derivative in the constitutive relation. The convective/convected terms involve the velocity at a point of the field, and as a result, when deriving the Maxwell form of the equations, one arrives at equations which contain both the terms of Maxwell's equation and the so-called laws of motional EMF: Faraday's, Oersted--Ampere's, and the Lorentz-force law. Thus a unification of the electromagnetism is achieved. Since the new model is frame indifferent, it is truly covariant in the sense that the governing system is invariant when changing to a coordinate frame that can accelerate or even deform in time.
IMPROVED COVARIANCE DRIVEN BLIND SUBSPACE IDENTIFICATION METHOD
Institute of Scientific and Technical Information of China (English)
ZHANG Zhiyi; FAN Jiangling; HUA Hongxing
2006-01-01
An improved covariance driven subspace identification method is presented to identify the weakly excited modes. In this method, the traditional Hankel matrix is replaced by a reformed one to enhance the identifiability of weak characteristics. The robustness of eigenparameter estimation to noise contamination is reinforced by the improved Hankel matrix. In combination with component energy index (CEI) which indicates the vibration intensity of signal components, an alternative stabilization diagram is adopted to effectively separate spurious and physical modes. Simulation of a vibration system of multiple-degree-of-freedom and experiment of a frame structure subject to wind excitation are presented to demonstrate the improvement of the proposed blind method. The performance of this blind method is assessed in terms of its capability in extracting the weak modes as well as the accuracy of estimated parameters. The results have shown that the proposed blind method gives a better estimation of the weak modes from response signals of small signal to noise ratio (SNR)and gives a reliable separation of spurious and physical estimates.
On the bilinear covariants associated to mass dimension one spinors
Energy Technology Data Exchange (ETDEWEB)
Silva, J.M.H. da; Villalobos, C.H.C.; Rogerio, R.J.B. [DFQ, UNESP, Guaratingueta, SP (Brazil); Scatena, E. [Universidade Federal de Santa Catarina-CEE, Blumenau, SC (Brazil)
2016-10-15
In this paper we approach the issue of Clifford algebra basis deformation, allowing for bilinear covariants associated to Elko spinors which satisfy the Fierz-Pauli-Kofink identities. We present a complete analysis of covariance, taking into account the involved dual structure associated to Elko spinors. Moreover, the possible generalizations to the recently presented new dual structure are performed. (orig.)
Validity of covariance models for the analysis of geographical variation
DEFF Research Database (Denmark)
Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio
2014-01-01
1. Due to the availability of large molecular data-sets, covariance models are increasingly used to describe the structure of genetic variation as an alternative to more heavily parametrised biological models. 2. We focus here on a class of parametric covariance models that received sustained...
Perturbative approach to covariance matrix of the matter power spectrum
Energy Technology Data Exchange (ETDEWEB)
Mohammed, Irshad [Fermilab; Seljak, Uros [UC, Berkeley, Astron. Dept.; Vlah, Zvonimir [Stanford U., ITP
2016-06-30
We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (beat coupling or super-sample variance), and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10\\% level up to $k \\sim 1 h {\\rm Mpc^{-1}}$. We show that all the connected components are dominated by the large-scale modes ($k<0.1 h {\\rm Mpc^{-1}}$), regardless of the value of the wavevectors $k,\\, k'$ of the covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher $k$ it is dominated by a single eigenmode. The full covariance matrix can be approximated as the disconnected part only, with the connected part being treated as an external nuisance parameter with a known scale dependence, and a known prior on its variance for a given survey volume. Finally, we provide a prescription for how to evaluate the covariance matrix from small box simulations without the need to simulate large volumes.
Validity of covariance models for the analysis of geographical variation
DEFF Research Database (Denmark)
Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio
2014-01-01
attention lately and show that the conditions under which they are valid mathematical models have been overlooked so far. 3. We provide rigorous results for the construction of valid covariance models in this family. 4. We also outline how to construct alternative covariance models for the analysis...
Covariation Is a Poor Measure of Molecular Coevolution.
Talavera, David; Lovell, Simon C; Whelan, Simon
2015-09-01
Recent developments in the analysis of amino acid covariation are leading to breakthroughs in protein structure prediction, protein design, and prediction of the interactome. It is assumed that observed patterns of covariation are caused by molecular coevolution, where substitutions at one site affect the evolutionary forces acting at neighboring sites. Our theoretical and empirical results cast doubt on this assumption. We demonstrate that the strongest coevolutionary signal is a decrease in evolutionary rate and that unfeasibly long times are required to produce coordinated substitutions. We find that covarying substitutions are mostly found on different branches of the phylogenetic tree, indicating that they are independent events that may or may not be attributable to coevolution. These observations undermine the hypothesis that molecular coevolution is the primary cause of the covariation signal. In contrast, we find that the pairs of residues with the strongest covariation signal tend to have low evolutionary rates, and that it is this low rate that gives rise to the covariation signal. Slowly evolving residue pairs are disproportionately located in the protein's core, which explains covariation methods' ability to detect pairs of residues that are close in three dimensions. These observations lead us to propose the "coevolution paradox": The strength of coevolution required to cause coordinated changes means the evolutionary rate is so low that such changes are highly unlikely to occur. As modern covariation methods may lead to breakthroughs in structural genomics, it is critical to recognize their biases and limitations.
A pure S-wave covariant model for the nucleon
Gross, F; Peña, M T; Gross, Franz
2006-01-01
Using the manifestly covariant spectator theory, and modeling the nucleon as a system of three constituent quarks with their own electromagnetic structure, we show that all four nucleon electromagnetic form factors can be very well described by a manifestly covariant nucleon wave function with zero orbital angular momentum.
On the bilinear covariants associated to mass dimension one spinors
da Silva, J M Hoff; Rogerio, R J Bueno; Scatena, E
2016-01-01
In this paper we approach the issue of Clifford algebra basis deformation, allowing for bilinear covariants associated to Elko spinors which satisfy the Fierz-Pauli-Kofink identities. We present a complete analysis of covariance, taking into account the involved dual structure associated to Elko. Moreover, the possible generalizations to the recently presented new dual structure are performed.
Perturbative approach to covariance matrix of the matter power spectrum
Mohammed, Irshad; Seljak, Uroš; Vlah, Zvonimir
2017-04-01
We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (supersample variance) and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10 per cent level up to k ˜ 1 h Mpc-1. We show that all the connected components are dominated by the large-scale modes (k covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher k, it is dominated by a single eigenmode. The full covariance matrix can be approximated as the disconnected part only, with the connected part being treated as an external nuisance parameter with a known scale dependence, and a known prior on its variance for a given survey volume. Finally, we provide a prescription for how to evaluate the covariance matrix from small box simulations without the need to simulate large volumes.
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
DEFF Research Database (Denmark)
Andersen, P.; Brincker, Rune; Kirkegaard, Poul Henning
1996-01-01
In this paper the theoretical background for using covariance equivalent ARMAV models in modal analysis is discussed. It is shown how to obtain a covariance equivalent ARMA model for a univariate linear second order continous-time system excited by Gaussian white noise. This result is generalized...
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
DEFF Research Database (Denmark)
Andersen, P.; Brincker, Rune; Kirkegaard, Poul Henning
In this paper the theoretical background for using covariance equivalent ARMAV models in modal analysis is discussed. It is shown how to obtain a covariance equivalent ARMA model for a univariate linear second order continuous-time system excited by Gaussian white noise. This result is generalize...
Theory of Covariance Equivalent ARMAV Models of Civil Engineering Structures
DEFF Research Database (Denmark)
Andersen, P.; Brincker, Rune; Kirkegaard, Poul Henning
1996-01-01
In this paper the theoretical background for using covariance equivalent ARMAV models in modal analysis is discussed. It is shown how to obtain a covariance equivalent ARMA model for a univariate linear second order continous-time system excited by Gaussian white noise. This result is generalized...
Gaussian covariance matrices for anisotropic galaxy clustering measurements
Grieb, Jan Niklas; Salazar-Albornoz, Salvador; Vecchia, Claudio dalla
2015-01-01
Measurements of the redshift-space galaxy clustering have been a prolific source of cosmological information in recent years. In the era of precision cosmology, accurate covariance estimates are an essential step for the validation of galaxy clustering models of the redshift-space two-point statistics. For cases where only a limited set of simulations is available, assessing the data covariance is not possible or only leads to a noisy estimate. Also, relying on simulated realisations of the survey data means that tests of the cosmology dependence of the covariance are expensive. With these two points in mind, this work aims at presenting a simple theoretical model for the linear covariance of anisotropic galaxy clustering observations with synthetic catalogues. Considering the Legendre moments (`multipoles') of the two-point statistics and projections into wide bins of the line-of-sight parameter (`clustering wedges'), we describe the modelling of the covariance for these anisotropic clustering measurements f...
Newton law in covariant unimodular $F(R)$ gravity
Nojiri, S; Oikonomou, V K
2016-01-01
We propose a covariant ghost-free unimodular $F(R)$ gravity theory, which contains a three-form field and study its structure using the analogy of the proposed theory with a quantum system which describes a charged particle in uniform magnetic field. Newton's law in non-covariant unimodular $F(R)$ gravity as well as in unimodular Einstein gravity is derived and it is shown to be just the same as in General Relativity. The derivation of Newton's law in covariant unimodular $F(R)$ gravity shows that it is modified precisely in the same way as in the ordinary $F(R)$ theory. We also demonstrate that the cosmology of a Friedmann-Robertson-Walker background, is equivalent in the non-covariant and covariant formulations of unimodular $F(R)$ theory.
Analysis of the covariance structure of digital ridge counts in the offspring of monozygotic twins.
Cantor, R M; Nance, W E; Eaves, L J; Winter, P M; Blanchard, M M
1983-03-01
Improved methods for analysis of covariance structures now permit the rigorous testing of multivariate genetic hypotheses. Using Jöreskog's Lisrel IV computer program we have conducted a confirmatory factor analysis of dermal ridge counts on the individual fingers of 509 offspring of 107 monozygotic twin pairs. Prior to the initiation of the model-fitting procedure, the sex-adjusted ridge counts for the offspring of male and female twins were partitioned by a multivariate nested analysis of variance yielding five 10 X 10 variance-covariance matrices containing a total of 275 distinctly observed parameters with which to estimate latent sources of genetic and environmental variation and test hypotheses about the factor structure of those latent causes. To provide an adequate explanation for the observed patterns of covariation, it was necessary to include additive genetic, random environmental, epistatic and maternal effects in the model and a structure for the additive genetic effects which included a general factor and allowed for hand asymmetry and finger symmetry. The results illustrate the value of these methods for the analysis of interrelated metric traits.
Early selection in open-pollinated Eucalyptus families based on competition covariates
Directory of Open Access Journals (Sweden)
Bruno Ettore Pavan
2014-06-01
Full Text Available The objetive of this work was to evaluate the influence of intergenotypic competition in open-pollinated families of Eucalyptus and its effects on early selection efficiency. Two experiments were carried out, in which the timber volume was evaluated at three ages, in a randomized complete block design. Data from the three years of evaluation (experiment 1, at 2, 4, and 7 years; and experiment 2, at 2, 5, and 7 years were analyzed using mixed models. The following were estimated: variance components, genetic parameters, selection gains, effective number, early selection efficiency, selection gain per unit time, and coincidence of selection with and without the use of competition covariates. Competition effect was nonsignificant for ages under three years, and adjustment using competition covariates was unnecessary. Early selection for families is effective; families that have a late growth spurt are more vulnerable to competition, which markedly impairs ranking at the end of the cycle. Early selection is efficient according to all adopted criteria, and the age of around three years is the most recommended, given the high efficiency and accuracy rate in the indication of trees and families. The addition of competition covariates at the end of the cycle improves early selection efficiency for almost all studied criteria.
Zeng, Rongping; Petrick, Nicholas; Gavrielides, Marios A; Myers, Kyle J
2011-10-07
Multi-slice computed tomography (MSCT) scanners have become popular volumetric imaging tools. Deterministic and random properties of the resulting CT scans have been studied in the literature. Due to the large number of voxels in the three-dimensional (3D) volumetric dataset, full characterization of the noise covariance in MSCT scans is difficult to tackle. However, as usage of such datasets for quantitative disease diagnosis grows, so does the importance of understanding the noise properties because of their effect on the accuracy of the clinical outcome. The goal of this work is to study noise covariance in the helical MSCT volumetric dataset. We explore possible approximations to the noise covariance matrix with reduced degrees of freedom, including voxel-based variance, one-dimensional (1D) correlation, two-dimensional (2D) in-plane correlation and the noise power spectrum (NPS). We further examine the effect of various noise covariance models on the accuracy of a prewhitening matched filter nodule size estimation strategy. Our simulation results suggest that the 1D longitudinal, 2D in-plane and NPS prewhitening approaches can improve the performance of nodule size estimation algorithms. When taking into account computational costs in determining noise characterizations, the NPS model may be the most efficient approximation to the MSCT noise covariance matrix.
Auto Adjusting Astronomical Telescope
Directory of Open Access Journals (Sweden)
Rohit R. Ghalsasi
2014-04-01
Full Text Available Astronomical telescope is powerful and basic tool for star or celestial observation. Here we proposed integrated system using Raspberry Pi for auto adjusting astronomical telescope. This integrated circuit helps to control stellar monitoring, stellar targeting, and tracking functions of telescope. Astro compass gives the direction of the celestial objects.
Psychological Adjustment and Homosexuality.
Gonsiorek, John C.
In this paper, the diverse literature bearing on the topic of homosexuality and psychological adjustment is critically reviewed and synthesized. The first chapter discusses the most crucial methodological issue in this area, the problem of sampling. The kinds of samples used to date are critically examined, and some suggestions for improved…
Covariance among multiple health risk behaviors in adolescents.
Directory of Open Access Journals (Sweden)
Kayla de la Haye
Full Text Available PURPOSE: In a diverse group of early adolescents, this study explores the co-occurrence of a broad range of health risk behaviors: alcohol, cigarette, and marijuana use; physical inactivity; sedentary computing/gaming; and the consumption of low-nutrient energy-dense food. We tested differences in the associations of unhealthy behaviors over time, and by gender, race/ethnicity, and socioeconomic status. METHODS: Participants were 8360 students from 16 middle schools in California (50% female; 52% Hispanic, 17% Asian, 16% White, and 15% Black/multiethnic/other. Behaviors were measured with surveys in Spring 2010 and Spring 2011. Confirmatory factor analysis was used to assess if an underlying factor accounted for the covariance of multiple behaviors, and composite reliability methods were used to determine the degree to which behaviors were related. RESULTS: The measured behaviors were explained by two moderately correlated factors: a 'substance use risk factor' and an 'unhealthy eating and sedentary factor'. Physical inactivity did not reflect the latent factors as expected. There were few differences in the associations among these behaviors over time or by demographic characteristics. CONCLUSIONS: Two distinct, yet related groups of health compromising behaviors were identified that could be jointly targeted in multiple health behavior change interventions among early adolescents of diverse backgrounds.
Recurrence Analysis of Eddy Covariance Fluxes
Lange, Holger; Flach, Milan; Foken, Thomas; Hauhs, Michael
2015-04-01
The eddy covariance (EC) method is one key method to quantify fluxes in biogeochemical cycles in general, and carbon and energy transport across the vegetation-atmosphere boundary layer in particular. EC data from the worldwide net of flux towers (Fluxnet) have also been used to validate biogeochemical models. The high resolution data are usually obtained at 20 Hz sampling rate but are affected by missing values and other restrictions. In this contribution, we investigate the nonlinear dynamics of EC fluxes using Recurrence Analysis (RA). High resolution data from the site DE-Bay (Waldstein-Weidenbrunnen) and fluxes calculated at half-hourly resolution from eight locations (part of the La Thuile dataset) provide a set of very long time series to analyze. After careful quality assessment and Fluxnet standard gapfilling pretreatment, we calculate properties and indicators of the recurrent structure based both on Recurrence Plots as well as Recurrence Networks. Time series of RA measures obtained from windows moving along the time axis are presented. Their interpretation is guided by three different questions: (1) Is RA able to discern periods where the (atmospheric) conditions are particularly suitable to obtain reliable EC fluxes? (2) Is RA capable to detect dynamical transitions (different behavior) beyond those obvious from visual inspection? (3) Does RA contribute to an understanding of the nonlinear synchronization between EC fluxes and atmospheric parameters, which is crucial for both improving carbon flux models as well for reliable interpolation of gaps? (4) Is RA able to recommend an optimal time resolution for measuring EC data and for analyzing EC fluxes? (5) Is it possible to detect non-trivial periodicities with a global RA? We will demonstrate that the answers to all five questions is affirmative, and that RA provides insights into EC dynamics not easily obtained otherwise.
Schwinger mechanism in linear covariant gauges
Aguilar, A. C.; Binosi, D.; Papavassiliou, J.
2017-02-01
In this work we explore the applicability of a special gluon mass generating mechanism in the context of the linear covariant gauges. In particular, the implementation of the Schwinger mechanism in pure Yang-Mills theories hinges crucially on the inclusion of massless bound-state excitations in the fundamental nonperturbative vertices of the theory. The dynamical formation of such excitations is controlled by a homogeneous linear Bethe-Salpeter equation, whose nontrivial solutions have been studied only in the Landau gauge. Here, the form of this integral equation is derived for general values of the gauge-fixing parameter, under a number of simplifying assumptions that reduce the degree of technical complexity. The kernel of this equation consists of fully dressed gluon propagators, for which recent lattice data are used as input, and of three-gluon vertices dressed by a single form factor, which is modeled by means of certain physically motivated Ansätze. The gauge-dependent terms contributing to this kernel impose considerable restrictions on the infrared behavior of the vertex form factor; specifically, only infrared finite Ansätze are compatible with the existence of nontrivial solutions. When such Ansätze are employed, the numerical study of the integral equation reveals a continuity in the type of solutions as one varies the gauge-fixing parameter, indicating a smooth departure from the Landau gauge. Instead, the logarithmically divergent form factor displaying the characteristic "zero crossing," while perfectly consistent in the Landau gauge, has to undergo a dramatic qualitative transformation away from it, in order to yield acceptable solutions. The possible implications of these results are briefly discussed.
Metagenomic covariation along densely sampled environmental gradients in the Red Sea
Thompson, Luke R
2016-07-15
Oceanic microbial diversity covaries with physicochemical parameters. Temperature, for example, explains approximately half of global variation in surface taxonomic abundance. It is unknown, however, whether covariation patterns hold over narrower parameter gradients and spatial scales, and extending to mesopelagic depths. We collected and sequenced 45 epipelagic and mesopelagic microbial metagenomes on a meridional transect through the eastern Red Sea. We asked which environmental parameters explain the most variation in relative abundances of taxonomic groups, gene ortholog groups, and pathways—at a spatial scale of <2000 km, along narrow but well-defined latitudinal and depth-dependent gradients. We also asked how microbes are adapted to gradients and extremes in irradiance, temperature, salinity, and nutrients, examining the responses of individual gene ortholog groups to these parameters. Functional and taxonomic metrics were equally well explained (75–79%) by environmental parameters. However, only functional and not taxonomic covariation patterns were conserved when comparing with an intruding water mass with different physicochemical properties. Temperature explained the most variation in each metric, followed by nitrate, chlorophyll, phosphate, and salinity. That nitrate explained more variation than phosphate suggested nitrogen limitation, consistent with low surface N:P ratios. Covariation of gene ortholog groups with environmental parameters revealed patterns of functional adaptation to the challenging Red Sea environment: high irradiance, temperature, salinity, and low nutrients. Nutrient-acquisition gene ortholog groups were anti-correlated with concentrations of their respective nutrient species, recapturing trends previously observed across much larger distances and environmental gradients. This dataset of metagenomic covariation along densely sampled environmental gradients includes online data exploration supplements, serving as a community
Moore, Mollie N.; Shirtcliff, Elizabeth A.; Lemery-Chalfant, Kathryn; Goldsmith, H. Hill
2015-01-01
Although several studies have shown that pubertal tempo and timing are shaped by genetic and environmental factors, few studies consider to what extent endocrine triggers of puberty are shaped by genetic and environmental factors. Doing so moves the field from examining correlated developmentally-sensitive biomarkers toward understanding what drives those associations. Two puberty related hormones, dehydroepiandrosterone and testosterone, were assayed from salivary samples in 118 MZ (62 % female), 111 same sex DZ (46 % female) and 103 opposite-sex DZ twin pairs, aged 12–16 years (M = 13.1, SD = 1.3). Pubertal status was assessed with a composite of mother- and self-reports. We used biometric models to estimate the genetic and environmental influences on the variance and covariance in testosterone and DHEA, with and without controlling for their association with puberty, and to test for sex differences. In males, the variance in testosterone and pubertal status was due to shared and non-shared environmental factors; variation in DHEA was due to genetic and non-shared environmental factors. In females, variance in testosterone was due to genetic and non-shared environmental factors; genetic, shared, and non-shared environmental factors contributed equally to variation in DHEA. In males, the testosterone-DHEA covariance was primarily due to shared environmental factors that overlapped with puberty as well as shared and non-shared environmental covariation specific to testosterone and DHEA. In females, the testosterone-DHEA covariance was due to genetic factors overlapping with pubertal status, and shared and non-shared environmental covariation specific to testosterone and DHEA. PMID:25633628
Cognitive Radio Spectrum Sensing Algorithms based on Eigenvalue and Covariance methods
Directory of Open Access Journals (Sweden)
K.SESHU KUMAR
2013-04-01
Full Text Available Spectrum sensing method is the fundamental factor when we are working with cognitive radio systems. Main aim and fundamental problem of cognitive radio is to identify weather primary users in authorized or licensed spectrum is presented or not. Paper deals with a new scheme of sensing based on the eigenvalues concept. It contain signals of covariance matrix received by the secondary users. In this method we are suggested two algorithms of sensing, one algorithm established by the maximum to minimum eigenvalue ratio. Other algorithm focused on average to minimum eigenvalue ratio. These two are done by using random matrix theories (RMT, and also these RMT are latest and also produce some accurate results. Now we calculate the ratios of distributions and probabilities of detection (Pd and derive the probabilities of false alarm (Pfa for the proposed algorithms, and also finding thresholds values for given Pfa. This method will improve the problem of noise uncertainty, and also performance isimproved compare to energy detection when highly correlated signal is available. Paper also deals with another method is and also covariance methods. First one is statistical covariance method, it has different noise and received signal, and it is used for finding the primary users presence where there is only noise. These algorithms implemented by use of small number of received signal samples and processed to calculate the sample covariance matrix. By use of sample covariance matrix we are extracted two test statistics. Finally we compare these results and concluded that signal presence. These are used in many signal detection applications, and also do not need signal information, also noise power and channel. We did the Simulations based on two ways. First one is randomly generated signals. Other one is done by captured DTV signals taken from ATSV committee, these are broadcasting signals. These methods confirm and verifies the efficiency of the proposed
Developmental plasticity in covariance structure of the skull: effects of prenatal stress.
Gonzalez, Paula N; Hallgrímsson, Benedikt; Oyhenart, Evelia E
2011-02-01
Environmental perturbations of many kinds influence growth and development. Little is known, however, about the influence of environmental factors on the patterns of phenotypic integration observed in complex morphological traits. We analyze the changes in phenotypic variance-covariance structure of the rat skull throughout the early postnatal ontogeny (from birth to weaning) and evaluate the effect of intrauterine growth retardation (IUGR) on this structure. Using 2D coordinates taken from lateral radiographs obtained every 4 days, from birth to 21 days old, we show that the pattern of covariance is temporally dynamic from birth to 21 days. The environmental perturbation provoked during pregnancy altered the skull growth, and reduced the mean size of the IUGR group. These environmental effects persisted throughout lactancy, when the mothers of both groups received a standard diet. More strikingly, the effect grew larger beyond this point. Altering environmental conditions did not affect all traits equally, as revealed by the low correlations between covariance matrices of treatments at the same age. Finally, we found that the IUGR treatment increased morphological integration as measured by the scaled variance of eigenvalues. This increase coincided and is likely related to an increase in morphological variance in this group. This result is expected if somatic growth is a major determinant of covariance structure of the skull. In summary, our findings suggest that environmental perturbations experienced in early ontogeny alter fundamental developmental processes and are an important factor in shaping the variance-covariance structure of complex phenotypic traits. © 2010 The Authors. Journal of Anatomy © 2010 Anatomical Society of Great Britain and Ireland.
Reid, Jane M
2012-11-22
The evolutionary forces that underlie polyandry, including extra-pair reproduction (EPR) by socially monogamous females, remain unclear. Selection on EPR and resulting evolution have rarely been explicitly estimated or predicted in wild populations, and evolutionary predictions are vulnerable to bias due to environmental covariances and correlated selection through unmeasured traits. However, evolutionary responses to (correlated) selection on any trait can be directly predicted as additive genetic covariances (cov(A)) with appropriate components of relative fitness. I used comprehensive life-history, paternity and pedigree data from song sparrows (Melospiza melodia) to estimate cov(A) between a female's liability to produce extra-pair offspring and two specific fitness components: relative annual reproductive success (ARS) and survival to recruitment. All three traits showed non-zero additive genetic variance. Estimates of cov(A) were positive, predicting evolution towards increased EPR, but 95% credible intervals overlapped zero. There was therefore no conclusive prediction of evolutionary change in EPR due to (correlated) selection through female ARS or recruitment. Negative environmental covariance between EPR and ARS would have impeded evolutionary prediction from phenotypic selection differentials. These analyses demonstrate an explicit quantitative genetic approach to predicting evolutionary responses to components of (correlated) selection on EPR that should be unbiased by environmental covariances and unmeasured traits.
Soil Respiration in Eddy Covariance Footprints using Forced Diffusion
Nickerson, N.; Gabriel, C. E.; Creelman, C.
2016-12-01
Eddy covariance (EC) has been widely used across the globe for more than 20 years, offering researchers invaluable measurements of parameters including Net Ecosystem Exchange and ecosystem respiration. However, research suggests that EC assumptions and technical obstacles can cause biased gas exchange estimates. Measurements of soil respiration (RS) at the ground level may help alleviate these biases; for example, by allowing researchers to reconcile nocturnal EC flux data with RS or by providing a means to inform gap-filling models. RS measurements have been used sparingly alongside EC towers because of the large cost required to scale chamber systems to the EC footprint and data integration and processing burdens. Here we present the Forced Diffusion (FD) method for the measurement of RS at EC sites. The FD method allows for inexpensive and autonomous measurements, providing a scalable approach to matching the EC footprint compared to other RS systems. A pilot study at the Howland Forest AmeriFlux site was carried out from July 15, 2016 to Dec., 2016 using EC, custom-made automated chambers, and FD chambers in tandem. These results emphasize how RS measurements, like those from the eosFD, can identify decoupling of above and below canopy air masses and assist in informing and parameterizing gap-filling techniques. Uncertainty in nocturnal EC fluxes has been extensively characterized at Howland Forest with EC measurements spanning more than 20 years. Similarly, long term automated measurements of RS are also made at Howland, and have already been used to inform EC gap-filling models, making Howland the ideal site for such a study. This study has been designed to reproduce previous findings from Howland using the FD approach, aiming to demonstrate that the measurements taken using the eosFD correlate well with the existing chamber systems and can be used with equal efficacy to inform gap filling models or for other other eddy covariance QA/QC procedures, including
Quantification of Covariance in Tropical Cyclone Activity across Teleconnected Basins
Tolwinski-Ward, S. E.; Wang, D.
2015-12-01
Rigorous statistical quantification of natural hazard covariance across regions has important implications for risk management, and is also of fundamental scientific interest. We present a multivariate Bayesian Poisson regression model for inferring the covariance in tropical cyclone (TC) counts across multiple ocean basins and across Saffir-Simpson intensity categories. Such covariability results from the influence of large-scale modes of climate variability on local environments that can alternately suppress or enhance TC genesis and intensification, and our model also simultaneously quantifies the covariance of TC counts with various climatic modes in order to deduce the source of inter-basin TC covariability. The model explicitly treats the time-dependent uncertainty in observed maximum sustained wind data, and hence the nominal intensity category of each TC. Differences in annual TC counts as measured by different agencies are also formally addressed. The probabilistic output of the model can be probed for probabilistic answers to such questions as: - Does the relationship between different categories of TCs differ statistically by basin? - Which climatic predictors have significant relationships with TC activity in each basin? - Are the relationships between counts in different basins conditionally independent given the climatic predictors, or are there other factors at play affecting inter-basin covariability? - How can a portfolio of insured property be optimized across space to minimize risk? Although we present results of our model applied to TCs, the framework is generalizable to covariance estimation between multivariate counts of natural hazards across regions and/or across peril types.
Covariance of maximum likelihood evolutionary distances between sequences aligned pairwise.
Dessimoz, Christophe; Gil, Manuel
2008-06-23
The estimation of a distance between two biological sequences is a fundamental process in molecular evolution. It is usually performed by maximum likelihood (ML) on characters aligned either pairwise or jointly in a multiple sequence alignment (MSA). Estimators for the covariance of pairs from an MSA are known, but we are not aware of any solution for cases of pairs aligned independently. In large-scale analyses, it may be too costly to compute MSAs every time distances must be compared, and therefore a covariance estimator for distances estimated from pairs aligned independently is desirable. Knowledge of covariances improves any process that compares or combines distances, such as in generalized least-squares phylogenetic tree building, orthology inference, or lateral gene transfer detection. In this paper, we introduce an estimator for the covariance of distances from sequences aligned pairwise. Its performance is analyzed through extensive Monte Carlo simulations, and compared to the well-known variance estimator of ML distances. Our covariance estimator can be used together with the ML variance estimator to form covariance matrices. The estimator performs similarly to the ML variance estimator. In particular, it shows no sign of bias when sequence divergence is below 150 PAM units (i.e. above ~29% expected sequence identity). Above that distance, the covariances tend to be underestimated, but then ML variances are also underestimated.
Generalized linear models with coarsened covariates: a practical Bayesian approach.
Johnson, Timothy R; Wiest, Michelle M
2014-06-01
Coarsened covariates are a common and sometimes unavoidable phenomenon encountered in statistical modeling. Covariates are coarsened when their values or categories have been grouped. This may be done to protect privacy or to simplify data collection or analysis when researchers are not aware of their drawbacks. Analyses with coarsened covariates based on ad hoc methods can compromise the validity of inferences. One valid method for accounting for a coarsened covariate is to use a marginal likelihood derived by summing or integrating over the unknown realizations of the covariate. However, algorithms for estimation based on this approach can be tedious to program and can be computationally expensive. These are significant obstacles to their use in practice. To overcome these limitations, we show that when expressed as a Bayesian probability model, a generalized linear model with a coarsened covariate can be posed as a tractable missing data problem where the missing data are due to censoring. We also show that this model is amenable to widely available general-purpose software for simulation-based inference for Bayesian probability models, providing researchers a very practical approach for dealing with coarsened covariates.
Westgate, Philip M; Braun, Thomas M
2012-09-10
Generalized estimating equations (GEE) are commonly used for the analysis of correlated data. However, use of quadratic inference functions (QIFs) is becoming popular because it increases efficiency relative to GEE when the working covariance structure is misspecified. Although shown to be advantageous in the literature, the impacts of covariates and imbalanced cluster sizes on the estimation performance of the QIF method in finite samples have not been studied. This cluster size variation causes QIF's estimating equations and GEE to be in separate classes when an exchangeable correlation structure is implemented, causing QIF and GEE to be incomparable in terms of efficiency. When utilizing this structure and the number of clusters is not large, we discuss how covariates and cluster size imbalance can cause QIF, rather than GEE, to produce estimates with the larger variability. This occurrence is mainly due to the empirical nature of weighting QIF employs, rather than differences in estimating equations classes. We demonstrate QIF's lost estimation precision through simulation studies covering a variety of general cluster randomized trial scenarios and compare QIF and GEE in the analysis of data from a cluster randomized trial. Copyright © 2012 John Wiley & Sons, Ltd.
Zhang, Zhongrui; Zhong, Quanlin; Niklas, Karl J.; Cai, Liang; Yang, Yusheng; Cheng, Dongliang
2016-08-01
Metabolic scaling theory (MST) posits that the scaling exponents among plant height H, diameter D, and biomass M will covary across phyletically diverse species. However, the relationships between scaling exponents and normalization constants remain unclear. Therefore, we developed a predictive model for the covariation of H, D, and stem volume V scaling relationships and used data from Chinese fir (Cunninghamia lanceolata) in Jiangxi province, China to test it. As predicted by the model and supported by the data, normalization constants are positively correlated with their associated scaling exponents for D vs. V and H vs. V, whereas normalization constants are negatively correlated with the scaling exponents of H vs. D. The prediction model also yielded reliable estimations of V (mean absolute percentage error = 10.5 ± 0.32 SE across 12 model calibrated sites). These results (1) support a totally new covariation scaling model, (2) indicate that differences in stem volume scaling relationships at the intra-specific level are driven by anatomical or ecophysiological responses to site quality and/or management practices, and (3) provide an accurate non-destructive method for predicting Chinese fir stem volume.
Distribution and variance/covariance structure of pesticide environmental fate data.
Spurlock, Frank
2008-08-01
Hydrophobicity, persistence, and volatility data for individual pesticides are widely used in risk assessment and transport modeling, so it is important to understand their distribution, variation, and covariation. Correlations (normalized covariance) among properties across a range of multiple pesticides are also important for understanding fundamental relationships among the properties. For the present study, multiple determinations of 11 physicochemical properties of 262 individual pesticides were compiled, primarily from registrant submissions. A Z-score normality analysis indicates that, barring specific data to the contrary, log normality is a reasonable assumption for three properties commonly treated as random variables in modeling: Organic carbon-normalized soil sorption coefficient, aerobic soil metabolism half-life, and field dissipation half-life. Various percentiles for coefficients of variation of the variables are provided, allowing probabilistic modelers to choose realistic population parameters for sampling distributions. A second data set consisting of median values of individual properties for each pesticide was used to investigate the covariance structure of eight of the most important fate properties across 172 pesticides using correlation analysis and exploratory common factor analysis. That analysis demonstrated the use of common factor analysis for reducing the dimensionality of multicollinear environmental fate data, yielding three new orthogonal variables containing most of the information in the original data, and provided insight into the fundamental data structure.
Zhang, Zhongrui; Zhong, Quanlin; Niklas, Karl J; Cai, Liang; Yang, Yusheng; Cheng, Dongliang
2016-08-24
Metabolic scaling theory (MST) posits that the scaling exponents among plant height H, diameter D, and biomass M will covary across phyletically diverse species. However, the relationships between scaling exponents and normalization constants remain unclear. Therefore, we developed a predictive model for the covariation of H, D, and stem volume V scaling relationships and used data from Chinese fir (Cunninghamia lanceolata) in Jiangxi province, China to test it. As predicted by the model and supported by the data, normalization constants are positively correlated with their associated scaling exponents for D vs. V and H vs. V, whereas normalization constants are negatively correlated with the scaling exponents of H vs. D. The prediction model also yielded reliable estimations of V (mean absolute percentage error = 10.5 ± 0.32 SE across 12 model calibrated sites). These results (1) support a totally new covariation scaling model, (2) indicate that differences in stem volume scaling relationships at the intra-specific level are driven by anatomical or ecophysiological responses to site quality and/or management practices, and (3) provide an accurate non-destructive method for predicting Chinese fir stem volume.
Ristorcelli, J. R.
1995-01-01
The mathematical consequences of a few simple scaling assumptions about the effects of compressibility are explored using a simple singular perturbation idea and the methods of statistical fluid mechanics. Representations for the pressure-dilation and dilatational dissipation covariances appearing in single-point moment closures for compressible turbulence are obtained. While the results are expressed in the context of a second-order statistical closure they provide some interesting and very clear physical metaphors for the effects of compressibility that have not been seen using more traditional linear stability methods. In the limit of homogeneous turbulence with quasi-normal large-scales the expressions derived are - in the low turbulent Mach number limit - asymptotically exact. The expressions obtained are functions of the rate of change of the turbulence energy, its correlation length scale, and the relative time scale of the cascade rate. The expressions for the dilatational covariances contain constants which have a precise and definite physical significance; they are related to various integrals of the longitudinal velocity correlation. The pressure-dilation covariance is found to be a nonequilibrium phenomena related to the time rate of change of the internal energy and the kinetic energy of the turbulence. Also of interest is the fact that the representation for the dilatational dissipation in turbulence, with or without shear, features a dependence on the Reynolds number. This article is a documentation of an analytical investigation of the implications of a pseudo-sound theory for the effects of compressibility.
Klous, Miriam; Mikulic, Pavle; Latash, Mark L
2011-05-01
We used the framework of the uncontrolled manifold hypothesis to explore the relations between anticipatory synergy adjustments (ASAs) and anticipatory postural adjustments (APAs) during feedforward control of vertical posture. ASAs represent a drop in the index of a multimuscle-mode synergy stabilizing the coordinate of the center of pressure in preparation to an action. ASAs reflect early changes of an index of covariation among variables reflecting muscle activation, whereas APAs reflect early changes in muscle activation levels averaged across trials. The assumed purpose of ASAs is to modify stability of performance variables, whereas the purpose of APAs is to change magnitudes of those variables. We hypothesized that ASAs would be seen before APAs and that this finding would be consistent with regard to the muscle-mode composition defined on the basis of different tasks and phases of action. Subjects performed a voluntary body sway task and a quick, bilateral shoulder flexion task under self-paced and reaction time conditions. Surface muscle activity of 12 leg and trunk muscles was analyzed to identify sets of 4 muscle modes for each task and for different phases within the shoulder flexion task. Variance components in the muscle-mode space and indexes of multimuscle-mode synergy stabilizing shift of the center of pressure were computed. ASAs were seen ∼ 100-150 ms prior to the task initiation, before APAs. The results were consistent with respect to different sets of muscle modes defined over the two tasks and different shoulder flexion phases. We conclude that the preparation for a self-triggered postural perturbation is associated with two types of anticipatory adjustments, ASAs and APAs. They reflect different feedforward processes within the hypothetical hierarchical control scheme, resulting in changes in patterns of covariation of elemental variables and in their patterns averaged across trials, respectively. The results show that synergies quantified
Performance of growth mixture models in the presence of time-varying covariates.
Diallo, Thierno M O; Morin, Alexandre J S; Lu, HuiZhong
2016-10-31
Growth mixture modeling is often used to identify unobserved heterogeneity in populations. Despite the usefulness of growth mixture modeling in practice, little is known about the performance of this data analysis technique in the presence of time-varying covariates. In the present simulation study, we examined the impacts of five design factors: the proportion of the total variance of the outcome explained by the time-varying covariates, the number of time points, the error structure, the sample size, and the mixing ratio. More precisely, we examined the impact of these factors on the accuracy of parameter and standard error estimates, as well as on the class enumeration accuracy. Our results showed that the consistent Akaike information criterion (CAIC), the sample-size-adjusted CAIC (SCAIC), the Bayesian information criterion (BIC), and the integrated completed likelihood criterion (ICL-BIC) proved to be highly reliable indicators of the true number of latent classes in the data, across design conditions, and that the sample-size-adjusted BIC (SBIC) also proved quite accurate, especially in larger samples. In contrast, the Akaike information criterion (AIC), the entropy, the normalized entropy criterion (NEC), and the classification likelihood criterion (CLC) proved to be unreliable indicators of the true number of latent classes in the data. Our results also showed that substantial biases in the parameter and standard error estimates tended to be associated with growth mixture models that included only four time points.
Use of an OSSE to Evaluate Background Error Covariances Estimated by the 'NMC Method'
Errico, Ronald M.; Prive, Nikki C.; Gu, Wei
2014-01-01
The NMC method has proven utility for prescribing approximate background-error covariances required by variational data assimilation systems. Here, untunedNMCmethod estimates are compared with explicitly determined error covariances produced within an OSSE context by exploiting availability of the true simulated states. Such a comparison provides insights into what kind of rescaling is required to render the NMC method estimates usable. It is shown that rescaling of variances and directional correlation lengths depends greatly on both pressure and latitude. In particular, some scaling coefficients appropriate in the Tropics are the reciprocal of those in the Extratropics. Also, the degree of dynamic balance is grossly overestimated by the NMC method. These results agree with previous examinations of the NMC method which used ensembles as an alternative for estimating background-error statistics.
A VLBI variance-covariance analysis interactive computer program. M.S. Thesis
Bock, Y.
1980-01-01
An interactive computer program (in FORTRAN) for the variance covariance analysis of VLBI experiments is presented for use in experiment planning, simulation studies and optimal design problems. The interactive mode is especially suited to these types of analyses providing ease of operation as well as savings in time and cost. The geodetic parameters include baseline vector parameters and variations in polar motion and Earth rotation. A discussion of the theroy on which the program is based provides an overview of the VLBI process emphasizing the areas of interest to geodesy. Special emphasis is placed on the problem of determining correlations between simultaneous observations from a network of stations. A model suitable for covariance analyses is presented. Suggestions towards developing optimal observation schedules are included.
PRACTICAL METHOD FOR ESTIMATING NEUTRON CROSS SECTION COVARIANCES IN THE RESONANCE REGION
Energy Technology Data Exchange (ETDEWEB)
Cho, Y.S.; Oblozinsky, P.; Mughabghab,S.F.; Mattoon,C.M.; Herman,M.
2010-04-30
Recent evaluations of neutron cross section covariances in the resolved resonance region reveal the need for further research in this area. Major issues include declining uncertainties in multigroup representations and proper treatment of scattering radius uncertainty. To address these issues, the present work introduces a practical method based on kernel approximation using resonance parameter uncertainties from the Atlas of Neutron Resonances. Analytical expressions derived for average cross sections in broader energy bins along with their sensitivities provide transparent tool for determining cross section uncertainties. The role of resonance-resonance and bin-bin correlations is specifically studied. As an example we apply this approach to estimate (n,{gamma}) and (n,el) covariances for the structural material {sup 55}Mn.
On the influence of Gribov ambiguities in a class of nonlinear covariant gauges
Serreau, Julien; Tresmontant, Andréas
2015-01-01
We consider Yang-Mills theories in a recently proposed family of nonlinear covariant gauges that consistently deals with the issue of Gribov ambiguities. Such gauges provide a generalization of the Curci-Ferrari-Delbourgo-Jarvis gauges which can be formulated as an extremization procedure and might be implemented in numerical calculations. This would allow for nonperturbative studies of Yang-Mills correlators in a broad class of covariant gauges continuously connected to the well studied Landau gauge. We compute the ghost and gluon propagators in the continuum formulation at one-loop order in perturbation theory and we study their momentum dependence down to the deep infrared regime, with and without renormalization group improvement. In particular, we show that the theory admits infrared safe renormalization group trajectories with no Landau pole. Both the gluon and the ghost behave as massive fields at low energy, and the gluon propagator is transverse even away from the Landau gauge limit. We compare our r...
Reality conditions for Ashtekar gravity from Lorentz-covariant formulation
Energy Technology Data Exchange (ETDEWEB)
Alexandrov, Sergei [Institute for Theoretical Physics and Spinoza Institute, Utrecht University, Postbus 80.195, 3508 TD Utrecht (Netherlands)
2006-03-21
We study the limit of the Lorentz-covariant canonical formulation where the Immirzi parameter approaches {beta} = i. We show that, formulated in terms of a shifted spacetime connection, which also plays a crucial role in the covariant quantization, the limit is smooth and reproduces the canonical structure of the self-dual Ashtekar gravity. The reality conditions of Ashtekar gravity can be incorporated by means of the Dirac brackets derived from the covariant formulation and defined on an extended phase space which involves, besides the self-dual variables, also their anti-self-dual counterparts.
Poincaré covariance of relativistic quantum position
Farkas, S; Weiner, M D; Farkas, Sz.
2002-01-01
A great number of problems of relativistic position in quantum mechanics are due to the use of coordinates which are not inherent objects of spacetime, cause unnecessary complications and can lead to misconceptions. We apply a coordinate-free approach to rule out such problems. Thus it will be clear, for example, that the Lorentz covariance of position, required usually on the analogy of Lorentz covariance of spacetime coordinates, is not well posed and we show that in a right setting the Newton--Wigner position is Poincar\\'e covariant, in contradiction with the usual assertions.
Metric adjusted skew information
DEFF Research Database (Denmark)
Hansen, Frank
2008-01-01
establish a connection between the geometrical formulation of quantum statistics as proposed by Chentsov and Morozova and measures of quantum information as introduced by Wigner and Yanase and extended in this article. We show that the set of normalized Morozova-Chentsov functions describing the possible...... quantum statistics is a Bauer simplex and determine its extreme points. We determine a particularly simple skew information, the "¿-skew information," parametrized by a ¿ ¿ (0, 1], and show that the convex cone this family generates coincides with the set of all metric adjusted skew informations.......We extend the concept of Wigner-Yanase-Dyson skew information to something we call "metric adjusted skew information" (of a state with respect to a conserved observable). This "skew information" is intended to be a non-negative quantity bounded by the variance (of an observable in a state...
Directory of Open Access Journals (Sweden)
Fabiana Rocha
2003-03-01
Full Text Available Two questions are addressed in this paper. The first one is the determination of periods of fiscal consolidation and fiscal stimulus. The second one is the importance of the composition of fiscal adjustments for their success, defined as a declining debt to GDP ratio. We, characterize 1994 and 1999 as points of fiscal consolidation. The 1994 consolidation can not be considered successful since after that period the debt to GDP ratio has grown continuously. The adjustment can be characterized as a type 2 adjustment (Alesina and Perotti (1997 in the sense that cuts were made mainly in public investment, while government wages and transfers remained almost unchanged. This type of adjustment usually has a low likelihood of being a success.Duas questões são tratadas neste artigo. A primeira é a determinação dos períodos de consolidação fiscal e estímulo fiscal. A segunda questão é a importância da composição dos ajustamentos fiscais para o seu sucesso, definido como um declínio na razo dívida/PIB. Nós, caracterizamos 1994 e 1999 como pontos de consolidação fiscal. A consolidação de 1994 não pode ser considerada um sucesso pois nos anos seguintes a razão dívida/PIB cresceu continuamente. O ajustamento pode ser considerado como um ajustamento do tipo 2 (Alesina and Perotti, 1997 no sentido de que foram feitos cortes principalmente no investimento público, enquanto os salários e transferências permaneceram praticamente inalterados. Este tipo de ajustamento geralmente tem uma baixa probabilidade de sucesso.
Covariation of Cognitive Styles, Intelligence and Achievement.
Satterly, D. J.
1979-01-01
A hierarchical factor analysis of 430 pupils' scores was performed on a matrix of correlations between three measures of cognitive style (analytic-synthetic; field independence; leveling-sharpening) and achievement in mathematics, geography, and English. Findings provide some support for the independence of cognitive style from general…
von Cramon-Taubadel, Noreen; Schroeder, Lauren
2016-10-01
Estimation of the variance-covariance (V/CV) structure of fragmentary bioarchaeological populations requires the use of proxy extant V/CV parameters. However, it is currently unclear whether extant human populations exhibit equivalent V/CV structures. Random skewers (RS) and hierarchical analyses of common principal components (CPC) were applied to a modern human cranial dataset. Cranial V/CV similarity was assessed globally for samples of individual populations (jackknifed method) and for pairwise population sample contrasts. The results were examined in light of potential explanatory factors for covariance difference, such as geographic region, among-group distance, and sample size. RS analyses showed that population samples exhibited highly correlated multivariate responses to selection, and that differences in RS results were primarily a consequence of differences in sample size. The CPC method yielded mixed results, depending upon the statistical criterion used to evaluate the hierarchy. The hypothesis-testing (step-up) approach was deemed problematic due to sensitivity to low statistical power and elevated Type I errors. In contrast, the model-fitting (lowest AIC) approach suggested that V/CV matrices were proportional and/or shared a large number of CPCs. Pairwise population sample CPC results were correlated with cranial distance, suggesting that population history explains some of the variability in V/CV structure among groups. The results indicate that patterns of covariance in human craniometric samples are broadly similar but not identical. These findings have important implications for choosing extant covariance matrices to use as proxy V/CV parameters in evolutionary analyses of past populations. © 2016 Wiley Periodicals, Inc.
Couples' patterns of adjustment to colon cancer.
Northouse, L L; Mood, D; Templin, T; Mellon, S; George, T
2000-01-01
The objectives for this longitudinal study were to: (a) compare colon cancer patients' and their spouses' appraisal of illness, resources, concurrent stress, and adjustment during the first year following surgery; (b) examine the influence of gender (male vs female) and role (patient vs spouse caregiver) on study variables; (c) assess the degree of correlation between patients' and spouses' adjustments; and (d) identify factors that affect adjustment to the illness. Fifty-six couples were interviewed at one week post diagnosis, and at 60 days and one year post surgery. Based on a cognitive-appraisal model of stress, the Smilkstein Stress Scale was used to measure concurrent stress; the Family APGAR, Social Support Questionnaire, and Dyadic Adjustment Scale were used to measure social resources; the Beck Hopelessness Scale and Mishel Uncertainty in Illness Scales were used to measure appraisal of illness; and the Brief Symptom Inventory and Psychosocial Adjustment to Illness Scale were used to measure psychosocial adjustment. Repeated Measures Analysis of Variance indicated that spouses reported significantly more emotional distress and less social support than patients. Gender differences were found, with women reporting more distress, more role problems, and less marital satisfaction, regardless of whether they were patient or spouse. Both patients and spouses reported decreases in their family functioning and social support, but also decreases in emotional distress over time. Moderately high autocorrelations and modest intercorrelations were found among and between patients' and spouses' adjustment scores over time. The strongest predictors of patients' role adjustment problems were hopelessness and spouses' role problems. The strongest predictors of spouses' role problems were spouses' own baseline role problems and level of marital satisfaction. Interventions need to start early in the course of illness, be family-focused, and identify the couples at risk of
Crews, D H
2006-01-01
To estimate adjustment factors and genetic parameters for gestation length (GES), AI and calving date records (n = 40,356) were extracted from the Canadian Charolais Association field database. The average time from AI to calving date was 285.2 d (SD = 4.49 d) and ranged from 274 to 296 d. Fixed effects were sex of calf, age of dam (2, 3, 4, 5 to 10, > or = 11 yr), and gestation contemporary group (year of birth x herd of origin). Variance components were estimated using REML and 4 animal models (n = 84,332) containing from 0 to 3 random maternal effects. Model 1 (M1) contained only direct genetic effects. Model 2 (M2) was G1 plus maternal genetic effects with the direct x maternal genetic covariance constrained to zero, and model 3 (M3) was G2 without the covariance constraint. Model 4 (M4) extended G3 to include a random maternal permanent environmental effect. Direct heritability estimates were high and similar among all models (0.61 to 0.64), and maternal heritability estimates were low, ranging from 0.01 (M2) to 0.09 (M3). Likelihood ratio tests and parameter estimates suggested that M4 was the most appropriate (P or = 11-yr-old cows, respectively. Bivariate animal models were used to estimate genetic parameters for GES with birth and adjusted 205-d weaning weights, and postweaning gain. Direct GES was positively correlated with direct birth weight (BWT; 0.34 +/- 0.04) but negatively correlated with maternal BWT (-0.20 +/- 0.07). Maternal GES had a low, negative genetic correlation with direct BWT (-0.15 +/- 0.05) but a high and positive genetic correlation with maternal BWT (0.62 +/- 0.07). Generally, GES had near-zero genetic correlations with direct and maternal weaning weights. Results suggest that important genetic associations exist for GES with BWT, but genetic correlations with weaning weight and postweaning gain were less important.
Electron localization functions and local measures of the covariance
Indian Academy of Sciences (India)
Paul W Ayers
2005-09-01
The electron localization measure proposed by Becke and Edgecombe is shown to be related to the covariance of the electron pair distribution. Just as with the electron localization function, the local covariance does not seem to be, in and of itself, a useful quantity for elucidating shell structure. A function of the local covariance, however, is useful for this purpose. A different function, based on the hyperbolic tangent, is proposed to elucidate the shell structure encapsulated by the local covariance; this function also seems to work better for the electron localization measure of Becke and Edgecombe. In addition, we propose a different measure for the electron localization that incorporates both the electron localization measure of Becke and Edgecombe and the Laplacian of the electron density; preliminary indications are that this measure is especially good at elucidating the shell structure in valence regions. Methods for evaluating electron localization functions directly from the electron density, without recourse to the Kohn-Sham orbitals, are discussed.
Progress of Covariance Evaluation at the China Nuclear Data Center
Energy Technology Data Exchange (ETDEWEB)
Xu, R., E-mail: xuruirui@ciae.ac.cn [China Nuclear Data Center, P.O. Box, 275(41), Beijing 102413 (China); Zhang, Q. [China Nuclear Data Center, P.O. Box, 275(41), Beijing 102413 (China); Shanxi Normal University, Linfen, Shanxi Province 041004 (China); Zhang, Y.; Liu, T.; Ge, Z.; Lu, H.; Sun, Z.; Yu, B. [China Nuclear Data Center, P.O. Box, 275(41), Beijing 102413 (China); Tang, G. [Peking University, Beijing 100871 (China)
2015-01-15
Covariance evaluations at the China Nuclear Data Center focus on the cross sections of structural materials and actinides in the fast neutron energy range. In addition to the well-known Least-squares approach, a method based on the analysis of the sources of experimental uncertainties is especially introduced to generate a covariance matrix for a particular reaction for which multiple measurements are available. The scheme of the covariance evaluation flow is presented, and an example of n+{sup 90}Zr is given to illuminate the whole procedure. It is proven that the accuracy of measurements can be properly incorporated into the covariance and the long-standing small uncertainty problem can be avoided.
Lorentz Covariant Canonical Symplectic Algorithms for Dynamics of Charged Particles
Wang, Yulei; Qin, Hong
2016-01-01
In this paper, the Lorentz covariance of algorithms is introduced. Under Lorentz transformation, both the form and performance of a Lorentz covariant algorithm are invariant. To acquire the advantages of symplectic algorithms and Lorentz covariance, a general procedure for constructing Lorentz covariant canonical symplectic algorithms (LCCSA) is provided, based on which an explicit LCCSA for dynamics of relativistic charged particles is built. LCCSA possesses Lorentz invariance as well as long-term numerical accuracy and stability, due to the preservation of discrete symplectic structure and Lorentz symmetry of the system. For situations with time-dependent electromagnetic fields, which is difficult to handle in traditional construction procedures of symplectic algorithms, LCCSA provides a perfect explicit canonical symplectic solution by implementing the discretization in 4-spacetime. We also show that LCCSA has built-in energy-based adaptive time steps, which can optimize the computation performance when th...
Group Lasso estimation of high-dimensional covariance matrices
Bigot, Jérémie; Loubes, Jean-Michel; Alvarez, Lilian Muniz
2010-01-01
In this paper, we consider the Group Lasso estimator of the covariance matrix of a stochastic process corrupted by an additive noise. We propose to estimate the covariance matrix in a high-dimensional setting under the assumption that the process has a sparse representation in a large dictionary of basis functions. Using a matrix regression model, we propose a new methodology for high-dimensional covariance matrix estimation based on empirical contrast regularization by a group Lasso penalty. Using such a penalty, the method selects a sparse set of basis functions in the dictionary used to approximate the process, leading to an approximation of the covariance matrix into a low dimensional space. Consistency of the estimator is studied in Frobenius and operator norms and an application to sparse PCA is proposed.
Covariance of metabolic and hemostatic risk indicators in men and women
Riese, H; Vrijkotte, TGM; Meijer, P; Kluft, C; de Geus, Eco J.
2001-01-01
Background and objective: Multivariate analyses on clusters of metabolic and hemostatic risk indicators implicitly assume good test-retest reliability of these variables, substantial covariance among the various indicators, stability of covariance structure over time, and comparable covariance struc
Illusory correlation and social anxiety
de Jong, Peter; Merckelbach, H; Bogels, S; Kindt, M
1998-01-01
An illusory correlation (IC) experiment examined the presence of a phobia-relevant covariation bias in the context of social anxiety. Low (n = 28) and high (n = 32) social anxious women were shown a series of slides comprising pictures of angry, happy and neutral faces which were randomly paired wit
Some covariance models based on normal scale mixtures
Schlather, Martin
2011-01-01
Modelling spatio-temporal processes has become an important issue in current research. Since Gaussian processes are essentially determined by their second order structure, broad classes of covariance functions are of interest. Here, a new class is described that merges and generalizes various models presented in the literature, in particular models in Gneiting (J. Amer. Statist. Assoc. 97 (2002) 590--600) and Stein (Nonstationary spatial covariance functions (2005) Univ. Chicago). Furthermore, new models and a multivariate extension are introduced.
Web Tool for Constructing a Covariance Matrix from EXFOR Uncertainties
Directory of Open Access Journals (Sweden)
Zerkin V.
2012-05-01
Full Text Available The experimental nuclear reaction database EXFOR contains almost no covariance data because most experimentalists provide experimental data only with uncertainties. With the tool described here a user can construct an experimental covariance matrix from uncertainties using general assumptions when uncertainty information given in EXFOR is poor (or even absent. The tool is publically available in the IAEA EXFOR Web retrieval system [1].
Comparison of Methods for Handling Missing Covariate Data
Johansson, Åsa M.; Karlsson, Mats O
2013-01-01
Missing covariate data is a common problem in nonlinear mixed effects modelling of clinical data. The aim of this study was to implement and compare methods for handling missing covariate data in nonlinear mixed effects modelling under different missing data mechanisms. Simulations generated data for 200 individuals with a 50% difference in clearance between males and females. Three different types of missing data mechanisms were simulated and information about sex was missing for 50% of the ...
High-dimensional covariance matrix estimation with missing observations
Lounici, Karim
2014-01-01
In this paper, we study the problem of high-dimensional covariance matrix estimation with missing observations. We propose a simple procedure computationally tractable in high-dimension and that does not require imputation of the missing data. We establish non-asymptotic sparsity oracle inequalities for the estimation of the covariance matrix involving the Frobenius and the spectral norms which are valid for any setting of the sample size, probability of a missing observation and the dimensio...
Menendez-Buxadera, A; Carabaño, M J; Gonzalez-Recio, O; Cue, R I; Ugarte, E; Alenda, R
2013-07-01
A total of 304,001 artificial insemination outcomes in up to 7 lactations from 142,389 Holstein cows, daughters of 5,349 sires and 101,433 dams, calving between January 1995 and December 2007 in 1,347 herds were studied by a reaction norm model. The (co)variance components for days to first service (DFS), days open, nonreturn rate in the first service (NRFS), and number of services per conception were estimated by 6 models: 3 Legendre polynomial degrees for the genetic effects and adjustment or not for the level of fat plus protein (FP) production recorded at day closest to DFS. For all traits and type of FP adjustment, a second degree polynomial showed the best fit. The use of the adjusted FP model did not increase the level of genetic (co)variance components except for DFS. The heritability for each of the traits was low in general (0.03-0.10) and increased from the first to fourth calving; nevertheless, very important variability was found for the estimated breeding value (EBV) of the sires. The genetic correlations (rg) were close to unity between adjacent calvings, but decreased for most distant parities, ranging from rg=0.36 (for DFS) to rg=0.63 (for NRFS), confirming the existence of heterogeneous genetic (co)variance components and EBV across lactations. The results of the eigen decomposition of rg shows that the first eigenvalue explained between 82 to 92% and the second between 8 to 14% of the genetic variance for all traits; therefore, a deformation of the overall mean trajectory for reproductive performance across the trajectory of the different calving could be expected if selection favored these eigenfunctions. The results of EBV for the 50 best sires showed a substantial reranking and variation in the shape of response across lactations. The more important aspect to highlight, however, is the difference between the EBV of the same sires in different calvings, a characteristic known as plasticity, which is particularly important for DFS and NRFS. This
Perturbative approach to covariance matrix of the matter power spectrum
Mohammed, Irshad; Vlah, Zvonimir
2016-01-01
We evaluate the covariance matrix of the matter power spectrum using perturbation theory up to dominant terms at 1-loop order and compare it to numerical simulations. We decompose the covariance matrix into the disconnected (Gaussian) part, trispectrum from the modes outside the survey (beat coupling or super-sample variance), and trispectrum from the modes inside the survey, and show how the different components contribute to the overall covariance matrix. We find the agreement with the simulations is at a 10\\% level up to $k \\sim 1 h {\\rm Mpc^{-1}}$. We show that all the connected components are dominated by the large-scale modes ($k<0.1 h {\\rm Mpc^{-1}}$), regardless of the value of the wavevectors $k,\\, k'$ of the covariance matrix, suggesting that one must be careful in applying the jackknife or bootstrap methods to the covariance matrix. We perform an eigenmode decomposition of the connected part of the covariance matrix, showing that at higher $k$ it is dominated by a single eigenmode. The full cova...
The Performance Analysis Based on SAR Sample Covariance Matrix
Directory of Open Access Journals (Sweden)
Esra Erten
2012-03-01
Full Text Available Multi-channel systems appear in several fields of application in science. In the Synthetic Aperture Radar (SAR context, multi-channel systems may refer to different domains, as multi-polarization, multi-interferometric or multi-temporal data, or even a combination of them. Due to the inherent speckle phenomenon present in SAR images, the statistical description of the data is almost mandatory for its utilization. The complex images acquired over natural media present in general zero-mean circular Gaussian characteristics. In this case, second order statistics as the multi-channel covariance matrix fully describe the data. For practical situations however, the covariance matrix has to be estimated using a limited number of samples, and this sample covariance matrix follow the complex Wishart distribution. In this context, the eigendecomposition of the multi-channel covariance matrix has been shown in different areas of high relevance regarding the physical properties of the imaged scene. Specifically, the maximum eigenvalue of the covariance matrix has been frequently used in different applications as target or change detection, estimation of the dominant scattering mechanism in polarimetric data, moving target indication, etc. In this paper, the statistical behavior of the maximum eigenvalue derived from the eigendecomposition of the sample multi-channel covariance matrix in terms of multi-channel SAR images is simplified for SAR community. Validation is performed against simulated data and examples of estimation and detection problems using the analytical expressions are as well given.
Gaussian covariance matrices for anisotropic galaxy clustering measurements
Grieb, Jan Niklas; Sánchez, Ariel G.; Salazar-Albornoz, Salvador; Dalla Vecchia, Claudio
2016-04-01
Measurements of the redshift-space galaxy clustering have been a prolific source of cosmological information in recent years. Accurate covariance estimates are an essential step for the validation of galaxy clustering models of the redshift-space two-point statistics. Usually, only a limited set of accurate N-body simulations is available. Thus, assessing the data covariance is not possible or only leads to a noisy estimate. Further, relying on simulated realizations of the survey data means that tests of the cosmology dependence of the covariance are expensive. With these points in mind, this work presents a simple theoretical model for the linear covariance of anisotropic galaxy clustering observations with synthetic catalogues. Considering the Legendre moments (`multipoles') of the two-point statistics and projections into wide bins of the line-of-sight parameter (`clustering wedges'), we describe the modelling of the covariance for these anisotropic clustering measurements for galaxy samples with a trivial geometry in the case of a Gaussian approximation of the clustering likelihood. As main result of this paper, we give the explicit formulae for Fourier and configuration space covariance matrices. To validate our model, we create synthetic halo occupation distribution galaxy catalogues by populating the haloes of an ensemble of large-volume N-body simulations. Using linear and non-linear input power spectra, we find very good agreement between the model predictions and the measurements on the synthetic catalogues in the quasi-linear regime.
Adjustment Criterion and Algorithm in Adjustment Model with Uncertain
Directory of Open Access Journals (Sweden)
SONG Yingchun
2015-02-01
Full Text Available Uncertainty often exists in the process of obtaining measurement data, which affects the reliability of parameter estimation. This paper establishes a new adjustment model in which uncertainty is incorporated into the function model as a parameter. A new adjustment criterion and its iterative algorithm are given based on uncertainty propagation law in the residual error, in which the maximum possible uncertainty is minimized. This paper also analyzes, with examples, the different adjustment criteria and features of optimal solutions about the least-squares adjustment, the uncertainty adjustment and total least-squares adjustment. Existing error theory is extended with new observational data processing method about uncertainty.
Sustainable urban regime adjustments
DEFF Research Database (Denmark)
Quitzau, Maj-Britt; Jensen, Jens Stissing; Elle, Morten
2013-01-01
The endogenous agency that urban governments increasingly portray by making conscious and planned efforts to adjust the regimes they operate within is currently not well captured in transition studies. There is a need to acknowledge the ambiguity of regime enactment at the urban scale. This directs...... attention to the transformative implications of conscious strategic maneuvering by incumbent regime actors, when confronting regime structurations. This article provides insight to processes of regime enactment performed by local governments by applying a flow-oriented perspective on regime dynamics...
Farley, Gary L.
1994-01-01
Local characteristics of fabrics varied to suit special applications. Adjustable reed machinery proposed for use in weaving fabrics in various net shapes, widths, yarn spacings, and yarn angles. Locations of edges of fabric and configuration of warp and filling yarns varied along fabric to obtain specified properties. In machinery, reed wires mounted in groups on sliders, mounted on lengthwise rails in reed frame. Mechanisms incorporated to move sliders lengthwise, parallel to warp yarns, by sliding them along rails; move sliders crosswise by translating reed frame rails perpendicular to warp yarns; and crosswise by spreading reed rails within group. Profile of reed wires in group on each slider changed.
Jordan Adjusted Human Development
Ababsa, Myriam
2014-01-01
Jordan Human Development Index (HDI) and Adjusted Human Development Index (IHDI) In 1990, the United Nations Development Programme designed a Human Development Index composed of life expectancy at birth, level of education and gross domestic product (GDP) per capita. In 2011, the UNDP ranked Jordan 95th out of 187 countries with a human development index of 0.698, up from 0.591 in 1990, making it the leading medium-range country for human development (fig. VIII.1). In 2010, the inequality adj...
DEFF Research Database (Denmark)
Revsbæk, Line
of ‘adjusting to the emergent’. Newcomer innovation is portrayed as carrying a variety of possible significations, such as unintentional innovation effects of newcomer’s proactive self-socializing behavior; an inspirational basis for designing innovation-generating employee induction; ‘resonant instances...... in standardized induction programs where newcomers are cast in roles as insecure novices needing to be “taught the ropes” of the organizational culture. Linked with this, it is suggested that the prevailing dichotomy of ‘newcomer assimilation’ versus ‘organizational accommodation’ is replaced with a notion...
Retinal thinning correlates with clinical severity in multiple system atrophy.
Ahn, Jeeyun; Lee, Jee-Young; Kim, Tae Wan
2016-10-01
To analyze retinal thickness changes in multiple system atrophy (MSA) and correlate changes with disease severity and subtypes of MSA. A total of 36 MSA (27 MSA-P and 9 MSA-C) patients and 71 healthy control subjects underwent general ophthalmologic examination and optical coherence tomography (OCT) scans. Peripapillary retinal nerve fiber layer (RNFL) thickness and perifoveal retinal thickness were analyzed separately. The generalized estimating equation model was used with age as a covariate to adjust for within-patient inter-eye correlations and the effect of age on retinal or RNFL thickness. Correlation analysis between RNFL, perifoveal thickness, and clinical parameters, the Unified MSA Rating Scale (UMSARS) and Global Disability Score (GDS), was also done. MSA patients showed significantly decreased peripapillary RNFL thickness in the inferior (P = 0.047) and inferotemporal (P = 0.017) sectors and significant perifoveal thinning in the superior outer sector (P = 0.042) compared to healthy controls. Both RNFL and perifoveal thinning were more marked and widespread in MSA-P than MSA-C patients. The UMSARS and GDS showed significant negative correlation with center and total macular perifoveal thickness and also the inferior and nasal outer sectors. Peripapillary RNFL and perifoveal retinal thinning were observed in MSA patients and retinal thinning correlated with the clinical severity of MSA. Structural changes in the retina may reflect the degree and pattern of neurodegeneration occurring in MSA.
Jarmołowski, Wojciech
2017-07-01
Maximum likelihood (ML) and restricted maximum likelihood (REML) are nowadays very popular in geophysics, geodesy and many other fields. There is also a growing number of investigations into how to calculate covariance parameters by ML/REML accurately and fast, and assure the convergence of the iteration steps in derivative-based approaches. The latter condition is not satisfied in many solutions, as it requires composed procedures or takes an unacceptable amount of time. The article implements efficient Fisher scoring (FS) to covariance parameter estimation in least-squares collocation (LSC). FS is optimized through Levenberg-Marquardt (LM) optimization, which provides stability in convergence when estimating two covariance parameters necessary for LSC. The motivation for this work was a very large number of non-optimized FS in the literature, as well as a deficiency of its scientific and engineering applications. The example work adds some usefulness to maximum likelihood estimation (ML) and FS and shows a new application—an alternative approach to LSC—a parametrization with no empirical covariance estimation. The results of LM damping applied to FS (FSLM) require some additional research related with optimal LM parameter. However, the method appears to be a milestone in relation to non-optimized FS, in terms of convergence. The FS with LM provides a reliable convergence, whose speed can be adjusted by manipulating the LM parameter.
Continuously adjustable Pulfrich spectacles
Jacobs, Ken; Karpf, Ron
2011-03-01
A number of Pulfrich 3-D movies and TV shows have been produced, but the standard implementation has inherent drawbacks. The movie and TV industries have correctly concluded that the standard Pulfrich 3-D implementation is not a useful 3-D technique. Continuously Adjustable Pulfrich Spectacles (CAPS) is a new implementation of the Pulfrich effect that allows any scene containing movement in a standard 2-D movie, which are most scenes, to be optionally viewed in 3-D using inexpensive viewing specs. Recent scientific results in the fields of human perception, optoelectronics, video compression and video format conversion are translated into a new implementation of Pulfrich 3- D. CAPS uses these results to continuously adjust to the movie so that the viewing spectacles always conform to the optical density that optimizes the Pulfrich stereoscopic illusion. CAPS instantly provides 3-D immersion to any moving scene in any 2-D movie. Without the glasses, the movie will appear as a normal 2-D image. CAPS work on any viewing device, and with any distribution medium. CAPS is appropriate for viewing Internet streamed movies in 3-D.
Puaud, Yohan; Pohl, Benjamin; Fauchereau, Nicolas; Macron, Clémence; Beltrando, Gérard
2016-08-01
This paper investigates and quantifies co-variability between large-scale convection in the South American and Southern African sectors at different timescales (interannual, intraseasonal and synoptic), during the austral summer seasons (November-February) from 1979 to 2012. Multivariate analyses (Canonical Correlation Analysis and Principal Component Analysis) are applied to daily outgoing longwave radiation (OLR, used as a proxy for atmospheric convection) anomalies to extract the principal modes of variability and co-variability in each and between both regions, filtered to consider the appropriate time-scales. At the interannual timescale, results confirm the predominant role of El Niño Southern Oscillation (ENSO), favoring enhanced convection over both southeastern Brazil and northern Argentina on the one hand, and tropical Africa and the western Indian Ocean on the other hand. At the intraseasonal timescale, the leading mode of co-variability is related to modulations of large-scale atmospheric convection over most of South America, and 10 days later, tropical Southern Africa. This mode accounts for the impacts of the Madden-Julian-oscillation (MJO) over these regions: identifying robust co-variability at the intraseasonal timescale between both regions require thus to consider a temporal shift between the two sectors. At the synoptic scale, however, co-variability consists mostly of a synchronous modulation of the large-scale atmospheric convection over the South American and Southern African sectors. This results from the development of concomitant Rossby waves forming a continuous wave train over the South Atlantic in the mid-latitudes, affecting both the South Atlantic and South Indian Convergence Zones. Among the days when convection shows significant anomalies (30 % of the total days in each sector), this synchronous mode occurs about 25 % of the time, individual Rossby waves modulating convection over one single region only during the remaining 75
Error analysis of quadratic power spectrum estimates for CMB polarization: sampling covariance
Challinor, A; Challinor, Anthony; Chon, Gayoung
2004-01-01
Quadratic methods with heuristic weighting (e.g. pseudo-C_l or correlation function methods) represent an efficient way to estimate power spectra of the cosmic microwave background (CMB) anisotropies and their polarization. We construct the sample covariance properties of such estimators for CMB polarization, and develop semi-analytic techniques to approximate the pseudo-C_l sample covariance matrices at high Legendre multipoles, taking account of the geometric effects of mode coupling and the mixing between the electric (E) and magnetic (B) polarization that arise for observations covering only part of the sky. The E-B mixing ultimately limits the applicability of heuristically-weighted quadratic methods to searches for the gravitational-wave signal in the large-angle B-mode polarization, even for methods that can recover (exactly) unbiased estimates of the B-mode power. We show that for surveys covering one or two per cent of the sky, the contribution of E-mode power to the covariance of the recovered B-mod...
Directory of Open Access Journals (Sweden)
Yue You
2017-01-01
Full Text Available A time and covariance threshold triggered optimal maneuver planning method is proposed for orbital rendezvous using angles-only navigation (AON. In the context of Yamanaka-Ankersen orbital relative motion equations, the square root unscented Kalman filter (SRUKF AON algorithm is developed to compute the relative state estimations from a low-volume/mass, power saving, and low-cost optical/infrared camera’s observations. Multi-impulsive Hill guidance law is employed in closed-loop linear covariance analysis model, based on which the quantitative relative position robustness and relative velocity robustness index are defined. By balancing fuel consumption, relative position robustness, and relative velocity robustness, we developed a time and covariance threshold triggered two-level optimal maneuver planning method, showing how these results correlate to past methods and missions and how they could potentially influence future ones. Numerical simulation proved that it is feasible to control the spacecraft with a two-line element- (TLE- level uncertain, 34.6% of range, initial relative state to a 100 m v-bar relative station keeping point, at where the trajectory dispersion reduces to 3.5% of range, under a 30% data gap per revolution on account of the eclipse. Comparing with the traditional time triggered maneuver planning method, the final relative position accuracy is improved by one order and the relative trajectory robustness and collision probability are obviously improved and reduced, respectively.
Kermarrec, Gaël; Schön, Steffen
2016-12-01
In this contribution, using the example of the Mátern covariance matrices, we study systematically the effect of apriori fully populated variance covariance matrices (VCM) in the Gauss-Markov model, by varying both the smoothness and the correlation length of the covariance function. Based on simulations where we consider a GPS relative positioning scenario with double differences, the true VCM is exactly known. Thus, an accurate study of parameters deviations with respect to the correlation structure is possible. By means of the mean-square error difference of the estimates obtained with the correct and the assumed VCM, the loss of efficiency when the correlation structure is missspecified is considered. The bias of the variance of unit weight is moreover analysed. By acting independently on the correlation length, the smoothness, the batch length, the noise level, or the design matrix, simulations allow to draw conclusions on the influence of these different factors on the least-squares results. Thanks to an adapted version of the Kermarrec-Schön model, fully populated VCM for GPS phase observations are computed where different correlation factors are resumed in a global covariance model with an elevation dependent weighting. Based on the data of the EPN network, two studies for different baseline lengths validate the conclusions of the simulations on the influence of the Mátern covariance parameters. A precise insight into the impact of apriori correlation structures when the VCM is entirely unknown highlights that both the correlation length and the smoothness defined in the Mátern model are important to get a lower loss of efficiency as well as a better estimation of the variance of unit weight. Consecutively, correlations, if present, should not be neglected for accurate test statistics. Therefore, a proposal is made to determine a mean value of the correlation structure based on a rough estimation of the Mátern parameters via maximum likelihood
Kermarrec, Gaël; Schön, Steffen
2017-05-01
In this contribution, using the example of the Mátern covariance matrices, we study systematically the effect of apriori fully populated variance covariance matrices (VCM) in the Gauss-Markov model, by varying both the smoothness and the correlation length of the covariance function. Based on simulations where we consider a GPS relative positioning scenario with double differences, the true VCM is exactly known. Thus, an accurate study of parameters deviations with respect to the correlation structure is possible. By means of the mean-square error difference of the estimates obtained with the correct and the assumed VCM, the loss of efficiency when the correlation structure is missspecified is considered. The bias of the variance of unit weight is moreover analysed. By acting independently on the correlation length, the smoothness, the batch length, the noise level, or the design matrix, simulations allow to draw conclusions on the influence of these different factors on the least-squares results. Thanks to an adapted version of the Kermarrec-Schön model, fully populated VCM for GPS phase observations are computed where different correlation factors are resumed in a global covariance model with an elevation dependent weighting. Based on the data of the EPN network, two studies for different baseline lengths validate the conclusions of the simulations on the influence of the Mátern covariance parameters. A precise insight into the impact of apriori correlation structures when the VCM is entirely unknown highlights that both the correlation length and the smoothness defined in the Mátern model are important to get a lower loss of efficiency as well as a better estimation of the variance of unit weight. Consecutively, correlations, if present, should not be neglected for accurate test statistics. Therefore, a proposal is made to determine a mean value of the correlation structure based on a rough estimation of the Mátern parameters via maximum likelihood
DEFF Research Database (Denmark)
Revsbæk, Line
In her doctoral thesis Line Revsbaek explores newcomer innovation related to organizational entry processes in a changing organization. She introduces process philosophy and complexity theory to research on organizational socialization and newcomer innovation. The study challenges assumptions...... in standardized induction programs where newcomers are cast in roles as insecure novices needing to be “taught the ropes” of the organizational culture. Linked with this, it is suggested that the prevailing dichotomy of ‘newcomer assimilation’ versus ‘organizational accommodation’ is replaced with a notion...... of ‘adjusting to the emergent’. Newcomer innovation is portrayed as carrying a variety of possible significations, such as unintentional innovation effects of newcomer’s proactive self-socializing behavior; an inspirational basis for designing innovation-generating employee induction; ‘resonant instances...
Revised error propagation of 40Ar/39Ar data, including covariances
Vermeesch, Pieter
2015-12-01
The main advantage of the 40Ar/39Ar method over conventional K-Ar dating is that it does not depend on any absolute abundance or concentration measurements, but only uses the relative ratios between five isotopes of the same element -argon- which can be measured with great precision on a noble gas mass spectrometer. The relative abundances of the argon isotopes are subject to a constant sum constraint, which imposes a covariant structure on the data: the relative amount of any of the five isotopes can always be obtained from that of the other four. Thus, the 40Ar/39Ar method is a classic example of a 'compositional data problem'. In addition to the constant sum constraint, covariances are introduced by a host of other processes, including data acquisition, blank correction, detector calibration, mass fractionation, decay correction, interference correction, atmospheric argon correction, interpolation of the irradiation parameter, and age calculation. The myriad of correlated errors arising during the data reduction are best handled by casting the 40Ar/39Ar data reduction protocol in a matrix form. The completely revised workflow presented in this paper is implemented in a new software platform, Ar-Ar_Redux, which takes raw mass spectrometer data as input and generates accurate 40Ar/39Ar ages and their (co-)variances as output. Ar-Ar_Redux accounts for all sources of analytical uncertainty, including those associated with decay constants and the air ratio. Knowing the covariance matrix of the ages removes the need to consider 'internal' and 'external' uncertainties separately when calculating (weighted) mean ages. Ar-Ar_Redux is built on the same principles as its sibling program in the U-Pb community (U-Pb_Redux), thus improving the intercomparability of the two methods with tangible benefits to the accuracy of the geologic time scale. The program can be downloaded free of charge from
Inverse modeling of the terrestrial carbon flux in China with flux covariance among inverted regions
Wang, H.; Jiang, F.; Chen, J. M.; Ju, W.; Wang, H.
2011-12-01
Quantitative understanding of the role of ocean and terrestrial biosphere in the global carbon cycle, their response and feedback to climate change is required for the future projection of the global climate. China has the largest amount of anthropogenic CO2 emission, diverse terrestrial ecosystems and an unprecedented rate of urbanization. Thus information on spatial and temporal distributions of the terrestrial carbon flux in China is of great importance in understanding the global carbon cycle. We developed a nested inversion with focus in China. Based on Transcom 22 regions for the globe, we divide China and its neighboring countries into 17 regions, making 39 regions in total for the globe. A Bayesian synthesis inversion is made to estimate the terrestrial carbon flux based on GlobalView CO2 data. In the inversion, GEOS-Chem is used as the transport model to develop the transport matrix. A terrestrial ecosystem model named BEPS is used to produce the prior surface flux to constrain the inversion. However, the sparseness of available observation stations in Asia poses a challenge to the inversion for the 17 small regions. To obtain additional constraint on the inversion, a prior flux covariance matrix is constructed using the BEPS model through analyzing the correlation in the net carbon flux among regions under variable climate conditions. The use of the covariance among different regions in the inversion effectively extends the information content of CO2 observations to more regions. The carbon flux over the 39 land and ocean regions are inverted for the period from 2004 to 2009. In order to investigate the impact of introducing the covariance matrix with non-zero off-diagonal values to the inversion, the inverted terrestrial carbon flux over China is evaluated against ChinaFlux eddy-covariance observations after applying an upscaling methodology.
Fibromyalgia is characterized by altered frontal and cerebellar structural covariance brain networks
Kim, Hyungjun; Kim, Jieun; Loggia, Marco L.; Cahalan, Christine; Garcia, Ronald G.; Vangel, Mark G.; Wasan, Ajay D.; Edwards, Robert R.; Napadow, Vitaly
2015-01-01
Altered brain morphometry has been widely acknowledged in chronic pain, and recent studies have implicated altered network dynamics, as opposed to properties of individual brain regions, in supporting persistent pain. Structural covariance analysis determines the inter-regional association in morphological metrics, such as gray matter volume, and such structural associations may be altered in chronic pain. In this study, voxel-based morphometry structural covariance networks were compared between fibromyalgia patients (N = 42) and age- and sex-matched pain-free adults (N = 63). We investigated network topology using spectral partitioning, which can delineate local network submodules with consistent structural covariance. We also explored white matter connectivity between regions comprising these submodules and evaluated the association between probabilistic white matter tractography and pain-relevant clinical metrics. Our structural covariance network analysis noted more connections within the cerebellum for fibromyalgia patients, and more connections in the frontal lobe for healthy controls. For fibromyalgia patients, spectral partitioning identified a distinct submodule with cerebellar connections to medial prefrontal and temporal and right inferior parietal lobes, whose gray matter volume was associated with the severity of depression in these patients. Volume for a submodule encompassing lateral orbitofrontal, inferior frontal, postcentral, lateral temporal, and insular cortices was correlated with evoked pain sensitivity. Additionally, the number of white matter fibers between specific submodule regions was also associated with measures of evoked pain sensitivity and clinical pain interference. Hence, altered gray and white matter morphometry in cerebellar and frontal cortical regions may contribute to, or result from, pain-relevant dysfunction in chronic pain patients. PMID:25844321
Fibromyalgia is characterized by altered frontal and cerebellar structural covariance brain networks
Directory of Open Access Journals (Sweden)
Hyungjun Kim
2015-01-01
Full Text Available Altered brain morphometry has been widely acknowledged in chronic pain, and recent studies have implicated altered network dynamics, as opposed to properties of individual brain regions, in supporting persistent pain. Structural covariance analysis determines the inter-regional association in morphological metrics, such as gray matter volume, and such structural associations may be altered in chronic pain. In this study, voxel-based morphometry structural covariance networks were compared between fibromyalgia patients (N = 42 and age- and sex-matched pain-free adults (N = 63. We investigated network topology using spectral partitioning, which can delineate local network submodules with consistent structural covariance. We also explored white matter connectivity between regions comprising these submodules and evaluated the association between probabilistic white matter tractography and pain-relevant clinical metrics. Our structural covariance network analysis noted more connections within the cerebellum for fibromyalgia patients, and more connections in the frontal lobe for healthy controls. For fibromyalgia patients, spectral partitioning identified a distinct submodule with cerebellar connections to medial prefrontal and temporal and right inferior parietal lobes, whose gray matter volume was associated with the severity of depression in these patients. Volume for a submodule encompassing lateral orbitofrontal, inferior frontal, postcentral, lateral temporal, and insular cortices was correlated with evoked pain sensitivity. Additionally, the number of white matter fibers between specific submodule regions was also associated with measures of evoked pain sensitivity and clinical pain interference. Hence, altered gray and white matter morphometry in cerebellar and frontal cortical regions may contribute to, or result from, pain-relevant dysfunction in chronic pain patients.
A new procedure to built a model covariance matrix: first results
Barzaghi, R.; Marotta, A. M.; Splendore, R.; Borghi, A.
2012-04-01
In order to validate the results of geophysical models a common procedure is to compare model predictions with observations by means of statistical tests. A limit of this approach is the lack of a covariance matrix associated to model results, that may frustrate the achievement of a confident statistical significance of the results. Trying to overcome this limit, we have implemented a new procedure to build a model covariance matrix that could allow a more reliable statistical analysis. This procedure has been developed in the frame of the thermo-mechanical model described in Splendore et al. (2010), that predicts the present-day crustal velocity field in the Tyrrhenian due to Africa-Eurasia convergence and to lateral rheological heterogeneities of the lithosphere. Modelled tectonic velocity field has been compared to the available surface velocity field based on GPS observation, determining the best fit model and the degree of fitting, through the use of a χ2 test. Once we have identified the key models parameters and defined their appropriate ranges of variability, we have run 100 different models for 100 sets of randomly values of the parameters extracted within the corresponding interval, obtaining a stack of 100 velocity fields. Then, we calculated variance and empirical covariance for the stack of results, taking into account also cross-correlation, obtaining a positive defined, diagonal matrix that represents the covariance matrix of the model. This empirical approach allows us to define a more robust statistical analysis with respect the classic approach. Reference Splendore, Marotta, Barzaghi, Borghi and Cannizzaro, 2010. Block model versus thermomechanical model: new insights on the present-day regional deformation in the surroundings of the Calabrian Arc. In: Spalla, Marotta and Gosso (Eds) Advances in Interpretation of Geological Processes: Refinement of Multi scale Data and Integration in Numerical Modelling. Geological Society, London, Special
BONNSAI: correlated stellar observables in Bayesian methods
Schneider, F R N; Fossati, L; Langer, N; de Koter, A
2016-01-01
In an era of large spectroscopic surveys of stars and big data, sophisticated statistical methods become more and more important in order to infer fundamental stellar parameters such as mass and age. Bayesian techniques are powerful methods because they can match all available observables simultaneously to stellar models while taking prior knowledge properly into account. However, in most cases it is assumed that observables are uncorrelated which is generally not the case. Here, we include correlations in the Bayesian code BONNSAI by incorporating the covariance matrix in the likelihood function. We derive a parametrisation of the covariance matrix that, in addition to classical uncertainties, only requires the specification of a correlation parameter that describes how observables co-vary. Our correlation parameter depends purely on the method with which observables have been determined and can be analytically derived in some cases. This approach therefore has the advantage that correlations can be accounte...
An Empirical State Error Covariance Matrix for Batch State Estimation
Frisbee, Joseph H., Jr.
2011-01-01
State estimation techniques serve effectively to provide mean state estimates. However, the state error covariance matrices provided as part of these techniques suffer from some degree of lack of confidence in their ability to adequately describe the uncertainty in the estimated states. A specific problem with the traditional form of state error covariance matrices is that they represent only a mapping of the assumed observation error characteristics into the state space. Any errors that arise from other sources (environment modeling, precision, etc.) are not directly represented in a traditional, theoretical state error covariance matrix. Consider that an actual observation contains only measurement error and that an estimated observation contains all other errors, known and unknown. It then follows that a measurement residual (the difference between expected and observed measurements) contains all errors for that measurement. Therefore, a direct and appropriate inclusion of the actual measurement residuals in the state error covariance matrix will result in an empirical state error covariance matrix. This empirical state error covariance matrix will fully account for the error in the state estimate. By way of a literal reinterpretation of the equations involved in the weighted least squares estimation algorithm, it is possible to arrive at an appropriate, and formally correct, empirical state error covariance matrix. The first specific step of the method is to use the average form of the weighted measurement residual variance performance index rather than its usual total weighted residual form. Next it is helpful to interpret the solution to the normal equations as the average of a collection of sample vectors drawn from a hypothetical parent population. From here, using a standard statistical analysis approach, it directly follows as to how to determine the standard empirical state error covariance matrix. This matrix will contain the total uncertainty in the
A Note on the Eigensystem of the Covariance Matrix of Dichotomous Guttman Items.
Davis-Stober, Clintin P; Doignon, Jean-Paul; Suck, Reinhard
2015-01-01
We consider the covariance matrix for dichotomous Guttman items under a set of uniformity conditions, and obtain closed-form expressions for the eigenvalues and eigenvectors of the matrix. In particular, we describe the eigenvalues and eigenvectors of the matrix in terms of trigonometric functions of the number of items. Our results parallel those of Zwick (1987) for the correlation matrix under the same uniformity conditions. We provide an explanation for certain properties of principal components under Guttman scalability which have been first reported by Guttman (1950).
Calculation of Covariance Matrix for Multi-mode Gaussian States in Decoherence Processes
Institute of Scientific and Technical Information of China (English)
XIANG Shao-Hua; SHAO Bin; SONG Ke-Hui
2009-01-01
We investigate the dynamics of n single-mode continuous variable systems in a generic Gaussian state under the influence of the independent and correlated noises making use of the characteristic function method.In two models the bath is assumed to be a squeezed thermal one.We derive an explicit input-output expression between the initial and final covariance matrices.As an example,we study the evolution of entanglement of three-mode Gaussian state embedded in two noisy models.
A note on the eigensystem of the covariance matrix of dichotomous Guttman items
Directory of Open Access Journals (Sweden)
Clintin P Davis-Stober
2015-12-01
Full Text Available We consider the sample covariance matrix for dichotomous Guttman items under a set of uniformity conditions, and obtain closed-form expressions for the eigenvalues and eigenvectors of the matrix. In particular, we describe the eigenvalues and eigenvectors of the matrix in terms of trigonometric functions of the number of items. Our results parallel those of Zwick (1987 for the correlation matrix under the same uniformity conditions. We provide an explanation for certain properties of principal components under Guttman scalability which have been first reported by Guttman (1950.
Fast Component Pursuit for Large-Scale Inverse Covariance Estimation.
Han, Lei; Zhang, Yu; Zhang, Tong
2016-08-01
The maximum likelihood estimation (MLE) for the Gaussian graphical model, which is also known as the inverse covariance estimation problem, has gained increasing interest recently. Most existing works assume that inverse covariance estimators contain sparse structure and then construct models with the ℓ1 regularization. In this paper, different from existing works, we study the inverse covariance estimation problem from another perspective by efficiently modeling the low-rank structure in the inverse covariance, which is assumed to be a combination of a low-rank part and a diagonal matrix. One motivation for this assumption is that the low-rank structure is common in many applications including the climate and financial analysis, and another one is that such assumption can reduce the computational complexity when computing its inverse. Specifically, we propose an efficient COmponent Pursuit (COP) method to obtain the low-rank part, where each component can be sparse. For optimization, the COP method greedily learns a rank-one component in each iteration by maximizing the log-likelihood. Moreover, the COP algorithm enjoys several appealing properties including the existence of an efficient solution in each iteration and the theoretical guarantee on the convergence of this greedy approach. Experiments on large-scale synthetic and real-world datasets including thousands of millions variables show that the COP method is faster than the state-of-the-art techniques for the inverse covariance estimation problem when achieving comparable log-likelihood on test data.
Newton law in covariant unimodular F(R) gravity
Nojiri, S.; Odintsov, S. D.; Oikonomou, V. K.
2016-09-01
We investigate the Newton law in the unimodular F(R) gravity. In the standard F(R) gravity, due to the extra scalar mode, there often appear the large corrections to the Newton law and such models are excluded by the experiments and/or the observations. In the unimodular F(R) gravity, however, the extra scalar mode become not to be dynamical due to the unimodular constraint and there is not any correction to the Newton law. Even in the unimodular Einstein gravity, the Newton law is reproduced but the mechanism is a little bit different from that in the unimodular F(R) gravity. We also investigate the unimodular F(R) gravity in the covariant formulation. In the covariant formulation, we include the three-form field. We show that the three-form field could not have any unwanted property, like ghost nor correction to the Newton law. In the covariant formulation, however, the above extra scalar mode becomes dynamical and could give a correction to the Newton law. We also show that there are no difference in the Friedmann-Robertson-Walker (FRW) dynamics in the non-covariant and covariant formulation.
A simple procedure for the comparison of covariance matrices.
Garcia, Carlos
2012-11-21
Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing the variance explained in each sample by the eigenvectors of its own covariance matrix with that explained by the covariance matrix eigenvectors of the other sample. The rationale of this procedure is that the matrix eigenvectors of two similar samples would explain similar amounts of variance in the two samples. I use computer simulation and morphological covariance matrices from the two morphs in a marine snail hybrid zone to show how the proposed procedure can be used to measure the contribution of the matrices orientation and shape to the overall differentiation. I show how this procedure can detect even modest differences between matrices calculated with moderately sized samples, and how it can be used as the basis for more detailed analyses of the nature of these differences. The new procedure constitutes a useful resource for the comparison of covariance matrices. It could fill the gap between procedures resulting in a single, overall measure of differentiation, and analytical methods based on multiple model comparison not providing such a measure.
A simple procedure for the comparison of covariance matrices
2012-01-01
Background Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing the variance explained in each sample by the eigenvectors of its own covariance matrix with that explained by the covariance matrix eigenvectors of the other sample. The rationale of this procedure is that the matrix eigenvectors of two similar samples would explain similar amounts of variance in the two samples. I use computer simulation and morphological covariance matrices from the two morphs in a marine snail hybrid zone to show how the proposed procedure can be used to measure the contribution of the matrices orientation and shape to the overall differentiation. Results I show how this procedure can detect even modest differences between matrices calculated with moderately sized samples, and how it can be used as the basis for more detailed analyses of the nature of these differences. Conclusions The new procedure constitutes a useful resource for the comparison of covariance matrices. It could fill the gap between procedures resulting in a single, overall measure of differentiation, and analytical methods based on multiple model comparison not providing such a measure. PMID:23171139
A simple procedure for the comparison of covariance matrices
Directory of Open Access Journals (Sweden)
Garcia Carlos
2012-11-01
Full Text Available Abstract Background Comparing the covariation patterns of populations or species is a basic step in the evolutionary analysis of quantitative traits. Here I propose a new, simple method to make this comparison in two population samples that is based on comparing the variance explained in each sample by the eigenvectors of its own covariance matrix with that explained by the covariance matrix eigenvectors of the other sample. The rationale of this procedure is that the matrix eigenvectors of two similar samples would explain similar amounts of variance in the two samples. I use computer simulation and morphological covariance matrices from the two morphs in a marine snail hybrid zone to show how the proposed procedure can be used to measure the contribution of the matrices orientation and shape to the overall differentiation. Results I show how this procedure can detect even modest differences between matrices calculated with moderately sized samples, and how it can be used as the basis for more detailed analyses of the nature of these differences. Conclusions The new procedure constitutes a useful resource for the comparison of covariance matrices. It could fill the gap between procedures resulting in a single, overall measure of differentiation, and analytical methods based on multiple model comparison not providing such a measure.
Covariant Lyapunov vectors of chaotic Rayleigh-Bénard convection.
Xu, M; Paul, M R
2016-06-01
We explore numerically the high-dimensional spatiotemporal chaos of Rayleigh-Bénard convection using covariant Lyapunov vectors. We integrate the three-dimensional and time-dependent Boussinesq equations for a convection layer in a shallow square box geometry with an aspect ratio of 16 for very long times and for a range of Rayleigh numbers. We simultaneously integrate many copies of the tangent space equations in order to compute the covariant Lyapunov vectors. The dynamics explored has fractal dimensions of 20≲D_{λ}≲50, and we compute on the order of 150 covariant Lyapunov vectors. We use the covariant Lyapunov vectors to quantify the degree of hyperbolicity of the dynamics and the degree of Oseledets splitting and to explore the temporal and spatial dynamics of the Lyapunov vectors. Our results indicate that the chaotic dynamics of Rayleigh-Bénard convection is nonhyperbolic for all of the Rayleigh numbers we have explored. Our results yield that the entire spectrum of covariant Lyapunov vectors that we have computed are tangled as indicated by near tangencies with neighboring vectors. A closer look at the spatiotemporal features of the Lyapunov vectors suggests contributions from structures at two different length scales with differing amounts of localization.
Adolescent Mothers' Adjustment to Parenting.
Samuels, Valerie Jarvis; And Others
1994-01-01
Examined adolescent mothers' adjustment to parenting, self-esteem, social support, and perceptions of baby. Subjects (n=52) responded to questionnaires at two time periods approximately six months apart. Mothers with higher self-esteem at Time 1 had better adjustment at Time 2. Adjustment was predicted by Time 2 variables; contact with baby's…
Adolescent Mothers' Adjustment to Parenting.
Samuels, Valerie Jarvis; And Others
1994-01-01
Examined adolescent mothers' adjustment to parenting, self-esteem, social support, and perceptions of baby. Subjects (n=52) responded to questionnaires at two time periods approximately six months apart. Mothers with higher self-esteem at Time 1 had better adjustment at Time 2. Adjustment was predicted by Time 2 variables; contact with baby's…
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Hirdes John P
2005-01-01
Full Text Available Abstract Background There has been increasing interest in enhancing accountability in health care. As such, several methods have been developed to compare the quality of home care services. These comparisons can be problematic if client populations vary across providers and no adjustment is made to account for these differences. The current paper explores the effects of risk adjustment for a set of home care quality indicators (HCQIs based on the Minimum Data Set for Home Care (MDS-HC. Methods A total of 22 home care providers in Ontario and the Winnipeg Regional Health Authority (WRHA in Manitoba, Canada, gathered data on their clients using the MDS-HC. These assessment data were used to generate HCQIs for each agency and for the two regions. Three types of risk adjustment methods were contrasted: a client covariates only; b client covariates plus an "Agency Intake Profile" (AIP to adjust for ascertainment and selection bias by the agency; and c client covariates plus the intake Case Mix Index (CMI. Results The mean age and gender distribution in the two populations was very similar. Across the 19 risk-adjusted HCQIs, Ontario CCACs had a significantly higher AIP adjustment value for eight HCQIs, indicating a greater propensity to trigger on these quality issues on admission. On average, Ontario had unadjusted rates that were 0.3% higher than the WRHA. Following risk adjustment with the AIP covariate, Ontario rates were, on average, 1.5% lower than the WRHA. In the WRHA, individual agencies were likely to experience a decline in their standing, whereby they were more likely to be ranked among the worst performers following risk adjustment. The opposite was true for sites in Ontario. Conclusions Risk adjustment is essential when comparing quality of care across providers when home care agencies provide services to populations with different characteristics. While such adjustment had a relatively small effect for the two regions, it did