covariance


Also found in: Dictionary, Thesaurus, Financial, Encyclopedia, Wikipedia.
Related to covariance: Covariance matrix

covariance

 [ko-va´re-ans]
a measure of the tendency of two random variables to vary together. It is the expected value of the product of the deviations of corresponding values of two random variables from their respective means.

covariance

/co·var·i·ance/ (ko-vār´e-ins) a measure of the tendency of two random variables to vary together.

covariance

(kō-vā′rē-ăns)
In statistics, the expected value of the product of the deviations of corresponding values of two variables from their respective means.

covariance

the expected value of the product of the deviations of corresponding values of two random variables from their respective means.

covariance method
used for the calculation of relationship and inbreeding in large populations.
References in periodicals archive ?
We know that mangrove forests are extremely 'good' at storing carbon," said PhD student Saverio Perri, who designed and coordinated the eddy covariance tower deployment at the Abu Dhabi Mangrove National Park.
The fixed curve was modeled by second and third order polynomial regressions using 12 matrix structures of the random variance and covariance matrix (G), maintaining the residual effects matrix (R) always equal to the VC.
In [18], the variance of the output of a transducer as well as the covariance between the input and the output were analyzed.
is equivalent to the estimation of the covariance matrix of CSI errors, i.
Examples of homogenous covariance structures are Compound Symmetry (CS), Variance Component (VC), Toeplitz (TOEP), and First- order Autoregressive (AR(1)).
To compare models with different nested covariance structures, the Restricted Likelihood Ratio Test (RLRT) is used, as well as the BIC Criterion, since it penalizes models with a larger number of parameters.
sAM: direct-maternal additive genetic covariance s2C: maternal permanent environmental variance s2E: residual variance
p]), a covariance function which to express correlation between them is defined.
In this case, the covariance intersection algorithm is suitable for providing a conservative confidence fusion for these correlated estimates [4].
Further, Figure 7 shows that there is a strong positive covariance between these two indexes since as the price of oil increases so does increase the price of commodities.
Since equation (1) holds for any positive integer n, Equation (3) must hold for any number of assets as well once the expected rate of return and their covariance existent or being given.