Linear Estimation in Censored Samples from Multivariate Normal Populations

Abstract

In this paper, the known methods of linear estimation are extended to various cases of censored samples from multivariate normal populations. The two estimators considered correspond to the minimum variance and the `alternative' estimators treated by Gupta [3] and Sarhan and Greenberg [4], [5] for univariate samples. It is found that the `alternative' estimator has important applications in multivariate samples, being easy of computation and of low variance.