Theory of statistics / Mark J. Schervish.

Author
Schervish, Mark J. [Browse]
Format
Book
Language
English
Published/​Created
New York : Springer-Verlag, c1995.
Description
xvi, 702 p. : ill. ; 25 cm.

Details

Subject(s)
Mathematical statistics [Browse]
Series
Springer series in statistics. [More in this series]
Summary note
  • 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 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.
  • Commencing with chapters on probability models and the theory of sufficient statistics, the author covers decision theory, hypothesis testing, estimation, equivariance, large sample theory, hierarchical models, and, finally, sequential analysis. Every chapter concludes with exercises which range in difficulty from the easy to the challenging. As a result, this textbook provides an excellent course in modern theoretical statistics.
Bibliographic references
Includes bibliographical references (p. [675]-688) and indexes.
Contents
Ch. 1. Probability Models -- Ch. 2. Sufficient Statistics -- Ch. 3. Decision Theory -- Ch. 4. Hypothesis Testing -- Ch. 5. Estimation -- Ch. 6. Equivariance -- Ch. 7. Large Sample Theory -- Ch. 8. Hierarchical Models -- Ch. 9. Sequential Analysis -- Appendix A: Measure and Integration Theory -- Appendix B: Probability Theory -- Appendix C: Mathematical Theorems Not Proven Here -- Appendix D: Summary of Distributions.
ISBN
0387945466 (New York : acid-free paper)
LCCN
95011235
OCLC
32552026
RCP
C - S

Supplementary Information

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