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Prediction Theory for Finite Populations

  • Book
  • © 1992

Overview

Authors:
  1. Heleno Bolfarine

    1. Department of Statistics, Institute of Mathematics and Statistics, University of Sao Paulo, Sao Paulo, Brazil

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  2. Shelemyahu Zacks

    1. Department of Mathematical Sciences, State University of New York at Binghamton, Binghamton, USA

    View author publications

    You can also search for this author in PubMed   Google Scholar

Part of the book series: Springer Series in Statistics (SSS)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xi
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  2. Synopsis

    • Heleno Bolfarine, Shelemyahu Zacks
    Pages 1-4

  3. Basic Ideas and Principles

    • Heleno Bolfarine, Shelemyahu Zacks
    Pages 5-22

  4. Optimal Predictors of Population Quantities

    • Heleno Bolfarine, Shelemyahu Zacks
    Pages 23-65

  5. Bayes and Minimax Predictors

    • Heleno Bolfarine, Shelemyahu Zacks
    Pages 66-98

  6. Maximum—Likelihood Predictors

    • Heleno Bolfarine, Shelemyahu Zacks
    Pages 99-118

  7. Classical and Bayesian Prediction Intervals

    • Heleno Bolfarine, Shelemyahu Zacks
    Pages 119-127

  8. The Effects of Model Misspecification, Conditions for Robustness, and Bayesian Modeling

    • Heleno Bolfarine, Shelemyahu Zacks
    Pages 128-149

  9. Models with Measurement Errors

    • Heleno Bolfarine, Shelemyahu Zacks
    Pages 150-168

  10. Asymptotic Properties in Finite Populations

    • Heleno Bolfarine, Shelemyahu Zacks
    Pages 169-181

  11. Design Characteristics of Predictors

    • Heleno Bolfarine, Shelemyahu Zacks
    Pages 182-192

  12. Back Matter

    Pages 193-209
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Keywords

About this book

A large number of papers have appeared in the last twenty years on estimating and predicting characteristics of finite populations. This monograph is designed to present this modern theory in a systematic and consistent manner. The authors' approach is that of superpopulation models in which values of the population elements are considered as random variables having joint distributions. Throughout, the emphasis is on the analysis of data rather than on the design of samples. Topics covered include: optimal predictors for various superpopulation models, Bayes, minimax, and maximum likelihood predictors, classical and Bayesian prediction intervals, model robustness, and models with measurement errors. Each chapter contains numerous examples, and exercises which extend and illustrate the themes in the text. As a result, this book will be ideal for all those research workers seeking an up-to-date and well-referenced introduction to the subject.

Authors and Affiliations

  • Department of Statistics, Institute of Mathematics and Statistics, University of Sao Paulo, Sao Paulo, Brazil

    Heleno Bolfarine

  • Department of Mathematical Sciences, State University of New York at Binghamton, Binghamton, USA

    Shelemyahu Zacks

Bibliographic Information

  • Book Title: Prediction Theory for Finite Populations

  • Authors: Heleno Bolfarine, Shelemyahu Zacks

  • Series Title: Springer Series in Statistics

  • DOI: https://doi.org/10.1007/978-1-4612-2904-9

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag New York Inc. 1992

  • Softcover ISBN: 978-1-4612-7713-2Published: 26 September 2011

  • eBook ISBN: 978-1-4612-2904-9Published: 06 December 2012

  • Series ISSN: 0172-7397

  • Series E-ISSN: 2197-568X

  • Edition Number: 1

  • Number of Pages: XII, 207

  • Topics: Applications of Mathematics

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