Classification into multivariate normal populations when the population means are linearly restricted

This paper considers the problem of classifying a multivariate normal population into one of thek multivariate normal populations when the population means are linearly restricted and the common nonsingular covariance matrix is unknown. It is shown that the maximum likelihood rule is an admissible rule. An example is also given to explain the procedure.