Statistical decision theory : estimation, testing, and selection / Friedrich Liese, Klaus-J. Miescke.
By: Liese, Friedrich
Contributor(s): Miescke, Klaus-J
Material type: 
TextLanguage: English Series: Springer series in statisticsPublisher: New York : Springer Verlag, c2008Description: xvii, 677 p. : ill. ; 25 cmISBN: 9780387731933; 0387731938Subject(s): Statistical decisionDDC classification: 519.542 LOC classification: QA279.4 | .L54 2008Online resources: WorldCat details | E-book Fulltext | Item type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds |
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EWU Library E-book | Non-fiction | 519.542 LIS 2008 (Browse shelf) | Not for loan | ||||
Text
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EWU Library Reserve Section | Non-fiction | 519.542 LIS 2008 (Browse shelf) | C-1 | Not For Loan | 26616 |
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| 519.542 BOI 2007 Introduction to Bayesian statistics / | 519.542 COA 2014 Applied Bayesian modelling / | 519.542 LEB 2012 Bayesian statistics : | 519.542 LIS 2008 Statistical decision theory : | 519.542 SAB 2011 Bayesian theory and methods with applications / | 519.544 EFJ 1982 The jackknife, the bootstrap, and other resampling plans / | 519.544 EGM 2009 Maximum penalized likelihood estimation / |
Includes bibliographical references and indexes.
Table of contents Statistical models --
Tests in models with monotonicity properties --
Statistical decision theory --
Comparison of models, reduction by sufficiency --
Invariant statistical decision models --
Large sample approximations of models and decisions --
Estimation --
Testing --
Selection --
Appendix: Topics from analysis, measure theory, and probability theory --
Appendix: Common notation and distributions.
Summary:
"This monograph is written for advanced graduate students, Ph. D. students, and researchers in mathematical statistics and decision theory. All major topics are introduced on a fairly elementary level and then developed gradually to higher levels. The book is self-contained as it provides full proofs, worked-out examples, and problems. It can be used as a basis for graduate courses, seminars, Ph. D. programs, Read more...
Applied Statistics
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