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Theory of Statistics

  • Mark J. Schervish

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

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Mark J. Schervish
    Pages 1-81
  3. Mark J. Schervish
    Pages 82-143
  4. Mark J. Schervish
    Pages 144-213
  5. Mark J. Schervish
    Pages 214-295
  6. Mark J. Schervish
    Pages 296-343
  7. Mark J. Schervish
    Pages 344-393
  8. Mark J. Schervish
    Pages 394-475
  9. Mark J. Schervish
    Pages 476-535
  10. Mark J. Schervish
    Pages 536-569
  11. Mark J. Schervish
    Pages 704-716
  12. Back Matter
    Pages 570-703

About this book

Introduction

The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as preparation for work on a Ph.D. An important strength of this book is that it provides a mathematically rigorous and even-handed account of both Classical and Bayesian inference in order to give readers a broad perspective. For example, the "uniformly most powerful" approach to testing is contrasted with available decision-theoretic approaches.

Keywords

ANOVA Estimator Likelihood Probability distribution Probability theory Variance bayesian statistics best fit

Authors and affiliations

  • Mark J. Schervish
    • 1
  1. 1.Department of StatisticsCarnegie Mellon UniversityPittsburghUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4612-4250-5
  • Copyright Information Springer-Verlag New York, Inc. 1995
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4612-8708-7
  • Online ISBN 978-1-4612-4250-5
  • Series Print ISSN 0172-7397
  • Series Online ISSN 2197-568X
  • Buy this book on publisher's site