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  • noun

Words related to covariance

(statistics) the mean value of the product of the deviations of two variates from their respective means

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The Kalman filter algorithm for estimating states and their error covariances can be written as follows.
Results indicated invariance of CUs, factor loadings, item intercepts, and factor variances and covariances.
It is important to recall that these are not covariances across levels of income sources, but rather the covariance of income volatilities.
Spatial statistics and spatio-temporal data; covariance functions and directional properties.
It is also the covariances between the latter three terms that enter into this determination and these could be quite influential in periods of external or financial turmoil and in crises in particular.
The input of the observed size distributions enables us to check the validity of the model, by comparison of the measured and calculated covariances.
We first use the consumption-based asset pricing framework and then present a less structured empirical analysis that relates bond risk premiums to changing covariances of bonds with stocks.
One of the most important properties of covariance is the fact that according to its formula, the covariance of two independent time series is zero.
By using the conventional approach, aggregate productivity can be decomposed into the average productivity of industry and the allocative efficiency component, which is often measured by the covariance between market share of individual firms in a given industry and their productivity (Olley and Pakes 1996).
The elements of the MSEM contain the covariances for the model predictions, plus the squared bias.
He covers the fundamental covariance structure, including state and innovation covariances, recursions for L and L-1, forward recursions, smoothing, initialization, normal priors and a general state-space model.
Extended tables of means, variances, and covariances of all order statistics for sample sizes up to 30 have been provided by Balakrishnan and Chan [45] and Balakrishnan and Chan [46].
I find that the CAPM fails to explain the predictability of stock market returns because covariances with the forecasting variables are also important determinants of stock market returns.
The importance of these factors in explaining the fall in the standard deviations and covariances of growth in the G-7 is unresolved.