In this paper, an empirical Bayes (EB) estimator is derived for the estimable functions of the parameters in normal linear model. The superiority of the EB estimator over ordinary least-squares (LS) estimator is investigated under mean square error matrix (MSEM) criterion.

Consider a two-way classification model, and let [alpha] and [beta] be the vectors of treatment effects of two factors A and B under investigation. We discuss the problem of constructing Bayes and empirical Bayes (EB) estimators of the linear functions of [alpha] and [beta]. Under general...

Mack et al. (Comm. Statist. A 28 (1999) 2277) proposed to use the boundary kernel method to estimate the wildlife population density from the line transect data when the detection function does not satisfy the shoulder condition, the first derivative of the detection function at distance zero is...

Suppose that the random variable X is distributed according to exponential families of distributions, conditional on the parameter [theta]. Assume that the parameter [theta] has a (prior) distribution G. Because of the measurement error, we can only observe Y = X + [var epsilon], where the...