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Testing Statistical Hypotheses, 2 Teile

BuchGebunden
1012 Seiten
Englisch
Springererschienen am24.06.20224. Aufl.
New additions include an expanded treatment of multiple hypothesis testing, a new section on extensions of the Central Limit Theorem, coverage of high-dimensional testing, expanded discussions of permutation and randomization tests, coverage of testing moment inequalities, and many new problems throughout the text.mehr
Verfügbare Formate
BuchGebunden
EUR117,69
BuchKartoniert, Paperback
EUR96,29
E-BookPDF1 - PDF WatermarkE-Book
EUR85,59

Produkt

KlappentextNew additions include an expanded treatment of multiple hypothesis testing, a new section on extensions of the Central Limit Theorem, coverage of high-dimensional testing, expanded discussions of permutation and randomization tests, coverage of testing moment inequalities, and many new problems throughout the text.
Zusammenfassung
Develops the foundations, principles, theory, and methods of hypothesis testing

Offers new coverage of multiple hypothesis testing, high-dimensional testing, permutation, and more

Features over 100 new problems, bringing the total to approximately 900 problems across both volumes.
Details
ISBN/GTIN978-3-030-70577-0
ProduktartBuch
EinbandartGebunden
Verlag
Erscheinungsjahr2022
Erscheinungsdatum24.06.2022
Auflage4. Aufl.
ReiheSpringer Texts in Statistics
Seiten1012 Seiten
SpracheEnglisch
IllustrationenXV, 1012 p. 13 illus., 7 illus. in color. In 2 volumes, not available separately.
Artikel-Nr.49370621

Inhalt/Kritik

Inhaltsverzeichnis
1. The General Decision Problem.- 2. The Probability Background.- 3. Uniformly Most Powerful Tests.- 4. Unbiasedness: Theory and First Applications.- 5. Unbiasedness: Applications to Normal Distributions.- 6. Invariance.- 7. Linear Hypotheses.- 8. The Minimax Principle.- 9. Multiple Testing and Simultaneous Inference.- 10. Conditional Inference.- 11. Basic Large Sample Theory.- 12. Extensions of the CLT to Sums of Dependent Random Variables.- 13. Applications to Inference.- 14. Quadratic Mean Differentiable Families.- 15. Large Sample Optimality.- 16. Testing Goodness of Fit.- 17. Permutation and Randomization Tests.- 18. Bootstrap and Subsampling Methods.- A. Auxiliary Results.mehr

Autor



E.L. Lehmann (1917 - 2009) was an American statistician and professor of statistics at the University of California, Berkeley. He made significant contributions to nonparametric hypothesis testing, and he is one of the eponyms of the Lehmann-Scheffé theorem and of the Hodges-Lehmann estimator. Dr. Lehmann was a member of the National Academy of Sciences and the American Academy of Arts and Sciences, and the recipient of honorary degrees from the University of Leiden, The Netherlands and the University of Chicago. He was the author of Elements of Large-Sample Theory (Springer 1999) and Theory of Point Estimation, Second Edition (Springer 1998, with George Casella).