Hierarchical Bayes Estimators of the Error Variance in Balanced Fixed-Effects Two-Way ANOVA Models

Hierarchical Bayes Estimators of the Error Variance in Balanced Fixed-Effects Two-Way ANOVA Models

We propose a class of hierarchical Bayes estimators of the error variance under the relative squared error loss in balanced fixed-effects two-way analysis of variance models. Also we provide analytic expressions for the risk improvement of the hierarchical Bayes estimators over multiples of the error sum of squares. Using these expressions we identify a subclass of the hierarchical Bayes estimators each member of which dominates the best multiple of the error sum of squares which is known to be minimax. Numerical values of the percentage risk improvement are given in some special cases.