# covariance

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Related to covariances: correlation

## covariance

[kō′ver·ē·əns]
(statistics)
A measurement of the tendency of two random variables, X and Y, to vary together, given by the expected value of the variable (X-X [OB ])(Y-Y [OB ]), where X [OB ] and Y [OB ] are the expected values of the variables X and Y respectively.
References in periodicals archive ?
The application of the formula requires that the inverses of the model error covariances [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII] are available.
0 software was used for the analysis with maximum likelihood estimation, and the input matrix was the covariance matrix.
In terms of the covariances, notable is the increased smoothing offered by transfers to changes in head earnings, especially in the middle of the distribution in the depth of the Great Recession, and by the increased negative covariance of other nontransfer income and head earnings in the top half of the income distribution.
are reported in Table 3, whereas the results for the covariance terms, that is, cov([alpha][DELTA][S.
In order to validate this assumption, it was necessary to fit the experimental measurements with the theoretical expressions of morphological parameters of the pores such as the transverse and longitudinal covariances.
The second approach explains the risk premium using covariances with current consumption growth and with news about future consumption growth; this might be called "CCAPM+," as it generalizes the insight about risk that is embodied in the consumption-based CAPM with power utility.
By comparing the statistical values with the critical ones and by taking into consideration the probability that the null hypothesis to be true, we draw the conclusion that our covariance time series is a I(0) process.
The elements of the composite covariance matrix can be obtained from sub-matrices using standard results from linear algebra (Beck and Arnold, 1977)
M])' has a multivariate normal distribution with mean [mu] = 0 and covariance matrix [SIGMA] = [[[sigma].
Model I is the CAPM, in which I assume that the covariances with variables that forecast stock market returns have no effects on the expected stock market return.
The Recent Record on Standard Deviations and Covariance in G-7 Growth

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