Suppose that the covariance matrix of the errors is Σ.
As an alternative, many methods have been suggested to improve the estimation of the covariance matrix.
Similar ideas can be used when is random with uncertainty in the covariance matrix.
Extensions of this result can be made for more than two random variables, using the covariance matrix.
This covariance matrix is a useful tool in many different areas.
There are several ways to define the two covariance matrices.
The covariance matrix can be used to compute portfolio variance.
The covariance matrix of T will be the identity matrix.
Information about image orientation can be derived by first using the second order central moments to construct a covariance matrix.
Suppose we wish to make inference about a covariance matrix whose prior has a distribution.