Multivariate normal estimation: the case (n < p)

Estimation of the Multivariate Normal Mean under the Extended Reflected Normal Loss Function

Ensemble Minimax Estimation for Multivariate Normal Means

This article discusses estimation of a heteroscedastic multivariate normal mean in terms of the ensemble risk. We first derive the ensemble minimaxity properties of various estimators that shrink towards zero. We then generalize our results to the case where the variances are given as a common unknown but estimable chi-squared random variable scaled by different known factors. We further provid...

estimation of the multivariate normal mean under the extended reflected normal loss function

Ml Estimation and Lr Tests for the Multivariate Normal

In this study ''Ie investigate maximum likelihood (ML) estimation and likelihood ratio (LR) tests for the multivariate normal distribution with mean vector ~ and covariance matrix k following the linear structures: 11 = Xr< and ]:; = I T G , where X and G are properly defined ~ ~ .-g g~g ~ ~g known matrices, and ~ and ! = (T g) are vectors of unknown parameters. Likelihood equations are obtaine...

Maximum likelihood estimation of the multivariate normal mixture model

The Hessian of the multivariate normal mixture model is derived, and estimators of the information matrix are obtained, thus enabling consistent estimation of all parameters and their precisions. The usefulness of the new theory is illustrated with two examples and some simulation experiments. The newly proposed estimators appear to be superior to the existing ones. AMS 1991 subject classificat...