# covariance

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Related to covariance: Covariance matrix

## 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.

## 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]
ThesaurusAntonymsRelated WordsSynonymsLegend:
 Noun 1 covariance - (statistics) the mean value of the product of the deviations of two variates from their respective meansstatistics - a branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parametersvariance - the second moment around the mean; the expected value of the square of the deviations of a random variable from its mean value
Based on WordNet 3.0, Farlex clipart collection. © 2003-2012 Princeton University, Farlex Inc.
Translations
kovariance
kowariancja
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References in periodicals archive ?
Hua Ma, has concluded that, if vector space is having the following symmetry, orthogonality, homogeneity and completeness, it should have three dimensions having the energy obeys the law of conservation and the dynamics law is ruled by the covariance principle and hence we can define the cross product in the space.
Data from partially repeated-measure designs (PRMD), or other structurally similar designs (e.g., split-plot and variations of the Latin square), are usually analyzed by using univariate analysis of variance (ANOVA) or multivariate analysis of variance (MANOVA), despite being highly sensitive to deviations from the multisample sphericity assumption (i.e., equality of covariance matrices across groups and sphericity for the common covariance matrix) when group sizes are not reasonably balanced.
In this work, focus is directed on the usage of covariance matrices for trajectory categorization.
A suitable selection of process noise and measurement noise covariance matrices is important in EKF estimation.
For the purpose of studying the carbon cycle of forests, there are hundreds of eddy covariance stations worldwide to quantify the atmosphere-biosphere fluxes of C[O.sub.2] [2].
Information filtering, which is essentially a Kalman filter expressed in terms of the inverse of the covariance matrix, has been widely used in multiple sensor estimation [10].
A time evolution of the dispersion of space pieces from a breakup event to the ground impact time is represented in terms of covariance ellipsoids, and in this paper, two covariance propagation methods are introduced.
For instance, it has to calculate the tedious covariance matrix square root and reconstruct the covariance matrix during the iteration of SLAM.
The Khalifa University of Science and Technology has announced that its state-of-the-art Masdar Institute Environmental Monitoring Platform (MIEMP) recently deployed at the Abu Dhabi Mangrove National Park, has become the first eddy covariance station in the Arab world to join the Fluxnet network.
The aim of this study was (1) to define the random regression model that best fits the observed data of egg production of Barred Plymouth Rock and White Plymouth Rock hens between 5 and 12 months of age; (2) to test different structures of genotypic covariance matrices (random effect matrix G) and residuals (R); and (3) to estimate broad-sense heritability, and environmental and genotypic correlations.
The difference of the covariance method is that matrices in calculations aren't Teoplitz matrices.

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