Statistical decision theory : estimation, testing, and selection / Friedrich Liese, Klaus-J. Miescke.

By: Liese, Friedrich, 1944-Contributor(s): Miescke, Klaus-J Material type: Text

TextLanguage: English Series: Springer series in statisticsPublication details: New York : Springer Verlag, c2008. Description: 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

Contents:

TOC 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: 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...

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode	Item holds
E-Book	Dr. S. R. Lasker Library, EWU E-book	Non-fiction	519.542 LIS 2008 (Browse shelf(Opens below))		Not for loan
Text	Dr. S. R. Lasker Library, EWU Reserve Section	Non-fiction	519.542 LIS 2008 (Browse shelf(Opens below))	C-1	Not For Loan		26616

Total holds: 0

Includes bibliographical references and indexes.

TOC 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...

Saifun Momota

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