Under a balanced loss function, we investigate the optimal and minimax prediction of finite population regression coefficient in a general linear regression superpopulation model with normal errors. The best unbiased prediction (BUP) is obtained in the class of all unbiased predictors. The...

This paper considers the problem of estimating the population total in two-stage cluster sampling when cluster sizes are unknown, making use of a population model arising basically from a variance component model. The problem can be considered as one of predicting the unobserved part Z of the...

This paper considers the problem of estimating the population total in two-stage cluster sampling when cluster sizes are unknown, making use of a population model arising basically from a variance component model. The problem can be considered as one of predicting the unobserved part Z of the...

The predictor that minimizes mean-squared prediction error is used to derive a goodness-of-fit measure that offers an asymptotically valid model selection criterion for a wide variety of regression models. In particular, a new goodness-of-fit criterion (cr2) is proposed for censored or otherwise...