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AuthorGabler, Siegfried. author
TitleMinimax Solutions in Sampling from Finite Populations [electronic resource] / by Siegfried Gabler
ImprintNew York, NY : Springer New York, 1990
Connect tohttp://dx.doi.org/10.1007/978-1-4612-3442-5
Descript V, 132 p. online resource

CONTENT

1: Decision Theoretic Foundations in Survey Sampling -- 1.1 General Definitions in Survey Sampling -- 1.2 Examples of Sampling Strategies -- 1.3 Classes of Strategies -- 1.4 Admissible Strategies -- 1.5 Superpopulation Models and Blu Predictors -- 1.6 Bayes Estimators -- 1.7 Minimax Strategies -- 1.8 A Modified Minimax Rule -- 1.9 Conditional Minimax Rules -- 1.10 Supplements -- 2: Minimax Solutions in Permutation Invariant Parameter Spaces -- 2.1 The Permutation Model -- 2.2 Supplements and Generalizations -- 3: The Cuboid as Parameter Space -- 3.1 The Scott Smith Solution -- 3.2 Lover Bounds -- 3.3 Some Special Cases -- 3.4 Representative Minimax Solutions -- 3.5 Unbiased Minimax Solutions -- 3.6 Conditional Minimax Estimators -- 4: The HH- Space as Parameter Space -- 4.1 HT- Strategy Versus HH- Strategy -- 4.2 Conditions for a Gain in Efficiency -- 4.3 Minimax Solutions Using the HT- Estimator -- 4.4 Modified Minimax Solutions Using the HT- Estimator -- 4.5 Minimax Solutions in General Classes of Strategies -- 5: The Generalized HH- Space as Parameter Space -- 5.1 Determination of the Relevant Parameter Space -- 5.2 A Modified Minimax Estimator -- 5.3 Conditional Minimax Estimators -- 5.4 Examples -- 5.5 The Blu Property of the Modified and Conditional Minimax Estimator -- 5.6 The Modified and Conditional Estimator as Bayes Estimator -- 5.7 Sampling Designs With Constant Risk -- List of Notation


Mathematics Applied mathematics Engineering mathematics Mathematics Applications of Mathematics



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