Improved estimators for the GMANOVA problem with application to Monte Carlo simulation

The problem of finding classes of estimators which improve upon the usual (e.g., ML, LS) estimator of the parameter matrix in the GMANOVA model under (matrix) quadratic loss is considered. Classes of improved estimators are obtained via combining integration-by-parts methods for normal and Wishart distributions. Also considered is the application of control variates to achieve better efficiency in multipopulation multivariate simulation studies.