We consider the problem of estimating a p-dimensional vector [mu]1 based on independent variables X1, X2, and U, where X1 is Np([mu]1, [sigma]2[Sigma]1), X2 is Np([mu]2, [sigma]2[Sigma]2), and U is [sigma]2[chi]2n ([Sigma]1 and [Sigma]2 are known). A family of minimax estimators is proposed....

Let X1,...,Xn (n1, p1) be independently and identically distributed normal p-vectors with mean [mu] and covariance matrix ([mu]'[mu]/C2)I, where the coefficient of variation C is known. The authors have obtained the best equivariant estimator of [mu] under the loss function...

Let S: p - p have a nonsingular Wishart distribution with unknown matrix [Sigma] and n degrees of freedom, n = p. For estimating [Sigma], a family of minimax estimators, with respect to the entropy loss, is presented. These estimators are of the form (S) = R[Phi](L) Rt, where R is orthogonal, L...

Let X1, ..., Xn (n p 2) be independently and identically distributed p-dimensional normal random vectors with mean vector [mu] and positive definite covariance matrix [Sigma] and let [Sigma] and . be partioned as1 p-1 1 p-1. We derive here the best equivariant estimators of the regression...

In the class of multivariate exponential power distributions, we derive LBI (locally best invariant) tests for normality in the two cases: (i) mean vector [mu] is known and (ii) [mu] is unknown. In the case (i), the null and nonnull asymptotic distributions of the test statistic are derived. In...

Let Rn-p, (n), Gl(p) and +(p) denote respectively the set of n-p matrices, the set of n-n orthogonal matrices, the set of p-p nonsingular matrices and the set of p - p positive definite matrices. In this paper, it is first shown that a bijective and bimeasurable transformation (BBT) g on...

In this paper, first we make a maximal extension of the well-known Gauss-Markov Theorem (GMT) in its linear framework. In particular, the maximal class of distributions of error term for which the GMT holds is derived. Second, we establish a nonlinear version of the maximal GMT and describe some...

This paper considers the problem of estimating the coefficient matrix B: m - p in a normal multivariate regression model under the risk matrix : m - m and obtains classes of minimax estimators for Baranchik type, Strawderman type, Efron-Morris type, and Stein type estimators.

In this paper, the authors propose a locally most powerful invariant test for the equality of means in the presence of covariate variables. Also the null and nonnull distributions associated with the above test are developed. This problem arises in covariate discriminant analysis and has been...

In the GMANOVA model or equivalent growth curve model, shrinkage effects on the MLE (maximum likelihood estimator) are considered under an invariant risk matrix. We first study the fundamental structure of the problem through which we decompose the estimation problem into some conditional...