Results 271 to 280 of about 105,835 (305)

Variance Decomposition for Statistical Quantities of Interest

Journal of Aerospace Information Systems, 2015
Modeling and simulation activities used in engineering analysis and design are subject to a variety of different uncertainties. These include inherent variations in model input variables (aleatory uncertainties) as well as imprecise or limited information about model parameters (epistemic uncertainties).
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Variance decomposition of apolipoproteins and lipids in Danish twins

Atherosclerosis, 2007
Twin studies are used extensively to decompose the variance of a trait, mainly to estimate the heritability of the trait. A second purpose of such studies is to estimate to what extent the non-genetic variance is shared or specific to individuals. To a lesser extent the twin studies have been used in bivariate or multivariate analysis to elucidate ...
Fenger, Mogens, Benyamin, Beben, Schousboe, Karoline, Sorensen, Thorkild I. A., Kyvik, Kirsten O.   +4 more
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Orthant-based variance decomposition in investment portfolios

European Journal of Operational Research, 2021
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A variance decomposition approach to the analysis of genetic algorithms

Proceedings of the 15th annual conference on Genetic and evolutionary computation, 2013
Prediction of the evolutionary process is a long standing problem both in the theory of evolutionary biology and evolutionary computation (EC). It has long been realized that heritable variation is crucial to both the response to selection and the success of genetic algorithms.
Paixão, Tiago; Barton, Nicholas H
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An Optimal Orthogonal Variance Decomposition

SSRN Electronic Journal, 2008
Let e and Sigma be respectively the vector of shocks and its variance covariance matrix in a linear system of equations in reduced form. This article shows that a unique orthogonal variance decomposition can be obtained if we impose a restriction that maximizes the trace of A, a positive definite matrix such that Az=e where z is vector of uncorrelated ...
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A decomposition of some serially-structured variance matrices

Biometrika, 1986
Let e be a stationary process generated by an autoregressive-moving average model of orders p and q (ARMA(p,q)). If V is the variance matrix of a generalized ARMA(p,q) process then there exist real lower-triangular band matrices \(\Phi\) and \(\Theta\) which are \(n\times n\) with bandwidths \((p+1)\) and \((q+1)\) respectively such that \(\Phi V\Phi ...
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Lagrangean Decomposition for Mean-Variance Combinatorial Optimization

2014
We address robust versions of combinatorial optimization problems, focusing on the uncorrelated ellipsoidal uncertainty case, which corresponds to so-called mean-variance optimization. We present a branch and bound-algorithm for such problems that uses lower bounds obtained from Lagrangean decomposition. This approach allows to separate the uncertainty
Frank Baumann, Christoph Buchheim, Anna Ilyina   +2 more
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Quantifying the apparent electron transfer number of electrolyte decomposition reactions in anode-free batteries

Joule, 2022
Mingyue Zhou, Jun-Fan Ding, Li-Peng Hou   +2 more
exaly  

Spinodal decomposition and the pseudo-binary decomposition in high-entropy alloys

Acta Materialia, 2023
Hengwei Luan, Liufei Huang, Xinglong Yang   +2 more
exaly  

Decomposition analysis for policymaking in energy:

Energy Policy, 2004
B W Ang
exaly