Abstract:
Maximum likelihood estimation under constraints for estimation in the Wishart class
of distributions, is considered. It provides a unified approach to estimation in a variety of
problems concerning covariance matrices. Virtually all covariance structures can be translated
to constraints on the covariances. This includes covariance matrices with given structure
such as linearly patterned covariance matrices, covariance matrices with zeros, independent
covariance matrices and structurally dependent covariance matrices. The methodology
followed in this paper provides a useful and simple approach to directly obtain the exact
maximum likelihood estimates. These maximum likelihood estimates are obtained via an
estimation procedure for the exponential class using constraints.
