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About this book
Argues that Bayesian ideas should play a more significant role in both the theory and practice of finite population sampling.
Contents
Bayesian FoundationsNotationSufficiencyThe Sufficiency and Likelihood PrinciplesA Bayesian ExamplePosterior LinearityOverviewA Noninfromative Bayesian ApproachA Binomial ExampleA Characterization of AdmissibilityAdmissibility of the Sample MeanSet EstimationThe Polya UrnThe Polya PosteriorSimulating the Polya PosteriorSome ExamplesExtensions of the Polya PosteriorPrior InformationUsing an Auxiliary VariableStratification and Prior InformationChoosing between ExperimentsNonresponseSome Nonparametric ProblemsLinear InterpolationEmpirical Bayes EstimationIntroduction Stepwise Bayes EstimatorsEstimation of Stratum MeansRobust Estimation of Stratum MeansMultistage SamplingAuxiliary InformationNested Error Regression ModelsHierarchical Bayes EstimationIntroductionStepwise Bayes EstimatorsEstimation of Stratum MeansAuxiliary Information IAuxiliary Information II
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