Explicit estimators under m-dependence for a multivariate normal distribution

Screening for a Multivariate Mixture Normal Distribution

screening for a multivariate mixture normal distribution

On combining correlated estimators of the common mean of a multivariate normal distribution

The inferential procedures based on an optimal combination of correlated estimators of the common mean of a multivariate normal distribution are considered. Exact properties of the conditional and unconditional confidence intervals due to Halperin [Halperin, 1961, Almost linearly-optimum combination of unbiased estimates. Journal of the American Statistical Association, 56, 36–43] are numerical...

Another Class of Minimax Estimators of A Variance Covariance Matrix in Multivariate Normal Distribution

It is well known that the best equivariant estimator of a variance covari-ance matrix of multivariate normal distribution with respect to the full ane group of transformation is not even minimax. Some minimax estimators have been proposed. Here we treat this problem in the framework of a multivari-ate analysis of variance(MANOVA) model and give other classes of minimax estimators.

On M-estimators and normal quantiles

Sydney, NSW 2109, Australia Abstract This paper explores a class of robust estimators of normal quantiles filling the gap between maximum likelihood estimators and empirical quantiles. Our estimators are linear combinations of M-estimators. Their asymptotic variances can be arbitrarily close to variances of the maximum likelihood estimators. Compared with empirical quantiles, the new estimators...