Contracting towards subspaces when estimating the mean of a multivariate normal distribution

Estimating a Bounded Normal Mean Under the LINEX Loss Function

Let X be a random variable from a normal distribution with unknown mean θ and known variance σ2. In many practical situations, θ is known in advance to lie in an interval, say [−m,m], for some m > 0. As the usual estimator of θ, i.e., X under the LINEX loss function is inadmissible, finding some competitors for X becomes worthwhile. The only study in the literature considered the problem of min...

Screening for a Multivariate Mixture Normal Distribution

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

estimating a bounded normal mean under the linex loss function

let x be a random variable from a normal distribution with unknown mean θ and known variance σ2. in many practical situations, θ is known in advance to lie in an interval, say [−m,m], for some m > 0. as the usual estimator of θ, i.e., x under the linex loss function is inadmissible, finding some competitors for x becomes worthwhile. the only study in the literature considered the problem of min...

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...