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Mixed model prediction and small area estimation. (With comments of P. Hall, D. Morales, C. N. Morris, J. N. K. Rao, and J. L. Eltinge). (English) Zbl 1149.62320
Summary: Over the last three decades, mixed models have been frequently used in a wide range of small area applications. Such models offer great flexibilities in combining information from various sources, and thus are well suited for solving most small area estimation problems. The present article reviews major research developments in the classical inferential approach for linear and generalized linear mixed models that are relevant to different issues concerning small area estimation and related problems.

##### MSC:
 62J12 Generalized linear models (logistic models) 62F10 Point estimation 62C12 Empirical decision procedures; empirical Bayes procedures 62F40 Bootstrap, jackknife and other resampling methods 62D05 Sampling theory, sample surveys
##### Software:
S-PLUS; MEMSS; BayesDA; goodwin.f77
Full Text:
##### References:
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