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Prediction theory for finite populations. (English) Zbl 0751.62003
Springer Series in Statistics. New York etc.: Springer-Verlag. xi, 207 p. (1992).
This book is a systematic treatment of prediction theory for finite populations based on superpopulation models, and brings together material scattered in papers during the last two decades. After a brief outline of ideas and principles, the following topics are dealt with in separate chapters:
Optimal predictors of population quantities; Bayes and minimax predictors; maximum likelihood predictors; classical and Bayes prediction intervals; the effects of model misspecification; conditions for robustness and Bayesian modelling; models with measurement errors; asymptotic properties in finite populations, design characteristics of predictors.
The emphasis is on the analysis of the data rather than on the design.

62D05 Sampling theory, sample surveys
62F15 Bayesian inference