covariance


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Related to covariance: Covariance matrix

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 ?
Three explanations have been advanced as possible causes of the recent reductions in standard deviation and covariance.
From Taylor's series (mentioned above), the approximate covariance is obtained.
To establish factor covariance invariance, another confirmatory factor analysis was performed, where factor covariances were also constrained to be the same across the countries.
1991, `Heteroskedasticity and autocorrelation consistent covariance matrix estimation', Econometrica, vol.
Given the expected excess rate of return vector R-r and non-singular covariance matrix [OMEGA] between the risky securities returns, CAPM holds if and only if the market portfolio [[omega].
Finally, the effect of the terms of trade synchronization is estimated to be significant only in the case of the covariance of exchange rates and relative movements in FX reserves.
Influence of sire misidentification on sire x year interaction variance and direct-maternal genetic covariance for weaning weight in beef cattle.
It is tempting to treat the consumption covariance and the wealth covariance as two separate quantities, but this ignores the fact that consumption and wealth are linked by the intertemporal budget constraint and by a time-series Euler equation.
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)
To address construct validity, we fit a covariance structure model with two factors (see Bollen, 1989).
For instance, for 64 x 64 images, the image vectors will be 4096 dimensional and the covariance matrix will be of 4096 x 4096.