Abstract
We consider Bayesian and minimax prediction of some finite population quantities. The usual best linear unbiased predictor of the population total T is shown to be minimax under normality and the squared error loss function. A general Bayesian predictor is derived for the population variance S 2 y . A minimax predictor of S 2 y is presented for the location model. Bayes, minimax and best unbiased prediction is also considered for the finite population regression coefficient β N .
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