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Testing Statistical Hypotheses
Langbeschreibung
Testing Statistical Hypotheses, 4th Edition updates and expands upon the classic graduate text, now a two-volume work. The first volume covers finite-sample theory, while the second volume discusses large-sample theory. A definitive resource for graduate students and researchers alike, this work grows to include new topics of current relevance. 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.
Hauptbeschreibung
Testing Statistical Hypotheses, 4th Edition updates and expands upon the classic graduate text, now a two-volume work. The first volume covers finite sample theory, while the second volume discusses large sample theory. A definitive resource for graduate students and researchers alike, this work grows to include new topics of current relevance. New additions include and 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 volume.
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.
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).
ISBN-13:
9783030705770
Veröffentl:
2022
Erscheinungsdatum:
24.06.2022
Seiten:
1048
Autor:
Joseph P. Romano
Gewicht:
1891 g
Format:
241x160x68 mm
Serie:
Springer Texts in Statistics
Sprache:
Englisch
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