covariance

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co·var·i·ance

 (kō-vâr′ē-əns)
n.
A statistical measure of the tendency of two random variables to vary in the same direction (called positive covariance) or in an opposite direction (called negative covariance) over many observations. Covariance is equal to the summed products of the deviations of corresponding values of the two variables from their respective means.
American Heritage® Dictionary of the English Language, Fifth Edition. Copyright © 2016 by Houghton Mifflin Harcourt Publishing Company. Published by Houghton Mifflin Harcourt Publishing Company. All rights reserved.

covariance

(kəʊˈvɛərɪəns)
n
(Statistics) statistics a measure of the association between two random variables, equal to the expected value of the product of the deviations from the mean of the two variables, and estimated by the sum of products of deviations from the sample mean for associated values of the two variables, divided by the number of sample points. Written as Cov (X, Y)
Collins English Dictionary – Complete and Unabridged, 12th Edition 2014 © HarperCollins Publishers 1991, 1994, 1998, 2000, 2003, 2006, 2007, 2009, 2011, 2014

co•var•i•ance

(koʊˈvɛər i əns)

n.
(in statistics) the value of the product of the standard deviations of two given variants and their correlation coefficient.
[1875–80]
Random House Kernerman Webster's College Dictionary, © 2010 K Dictionaries Ltd. Copyright 2005, 1997, 1991 by Random House, Inc. All rights reserved.
ThesaurusAntonymsRelated WordsSynonymsLegend:
Noun1.covariance - (statistics) the mean value of the product of the deviations of two variates from their respective means
statistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters
variance - the second moment around the mean; the expected value of the square of the deviations of a random variable from its mean value
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References in periodicals archive ?
Durrant-Whyte, "A new method for the nonlinear transformation of means and covariances in filters and estimators," IEEE Transactions on Automatic Control, vol.
Durrant-Whyte, "A new method for the nonlinear transformation of means and covariances in filters and estimators," Institute of Electrical and Electronics Engineers Transactions on Automatic Control, vol.
In this context the conditional transfer entropy can be expressed in terms of the determinants of conditional covariances det ([SIGMA](* | *)) (see (B.5) in Appendix B):
The EKF works on the principle that a linearized transformation of means and covariances is approximately equal to the true nonlinear transformation, but this approximation could be unsatisfactory in practice.
Third, the final best-fitting CFA 5-factor structure determined for Group 2 was cross-validated based on Group 3 (n=582) using two different approaches: (a) comparisons were made regarding model goodness-of-fit for Group 3; and (b) all factor loadings and factor covariances of the final model were tested for their invariance across Groups 2 and 3.
The condition of independence between two sets of variables can be tested using the likelihood ratio test (LRT), i.e., if the covariances between the two groups are equal to zero (FERREIRA, 2008).
Model 5 and Model 6 included additive maternal and maternal permanent environmental effects, ignoring and fitting, respectively, direct maternal covariance. Allowing for and ignoring genetic covariances between direct and maternal effects yielded up to six different analyses for birth weight.
LSC method is generally performed in three phases i) determination of the trend, ii) computation of experimental covariances, iii) prediction of the signals at estimation points.
where, , [beta] =[OMEGA][[omega].sub.m]/[[sigma].sub.m.sup.2], [c.sub.m] = ([R.sub.m] - r)/ [[sigma].sub.m.sup.2], [[lambda].sub.m] = [c.sub.m] [[omega].sub.m], [beta] is the n x 1 vector of beta, [OMEGA][[omega].sub.m] is the n x 1 vector of covariances between the rate of return on ith risky asset [[??].sub.m]i = 1,2, ..., n and the market portfolio rate of return [[??].sub.m],[[sigma].sub.m.sup.2] = [[omega].sub.m.sup.T] [OMEGA][[omega].sub.m].
The matrix T is the covariance matrix, which means that its diagonal elements are the variances [[tau].sup.2.sub.k] and its non-diagonal elements are the covariances [[tau].sub.kl].
In practice, this set of correspondences provides a convenient tool, allowing for inferring indirectly which particular pattern of adaptive constraints actually affects the respective magnitudes of variation of the three functional parameters, on the basis of the pattern of covariances actually recorded between the three growth-based parameters.