Prediction in finite population under error-in-variables superpopulation models

Abstract

In this paper we consider the optimal prediction of finite population total and variance under location model with measurement errors. Bayes predictors of population total and variance under a class of priors have been derived and a minimax predictor for population total has been obtained. Under regression superpopulation model with measurement errors, an optimal predictor of population total has been derived. A Bayesian approach for this model shows the linear regression predictor to be a Bayes predictor.