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Theoretical statistics : topics for a core course

Theoretical statistics : topics for a core course (1회 대출)

자료유형
단행본
개인저자
Keener, Robert W.
서명 / 저자사항
Theoretical statistics : topics for a core course / Robert W. Keener.
발행사항
New York :   Springer,   2010.  
형태사항
xvii, 538 p. : ill. ; 24 cm.
총서사항
Springer texts in statistics,1431-875X
ISBN
9780387938387 0387938389 9781461426707 (pbk.)
내용주기
Probability and measure -- Exponential families -- Risk, sufficiency, completeness, and ancillarity -- Unbiased estimation -- Curved exponential families -- Conditional distributions -- Bayesian estimation -- Large-sample theory -- Estimating equations and maximum likelihood -- Equivariant estimation -- Empirical bayes and shrinkage estimators -- Hypothesis testing -- Optimal tests in higher dimensions -- General linear model -- Bayesian inference : modeling and computation -- Asymptotic optimality -- Large-sample theory for likelihood ratio tests -- Nonparametric regression -- Bootstrap methods -- Sequential methods -- Appendix 1: Functions -- Appendix 2: Topology and continuity in Rn -- Appendix 3: Vector spaces and the geometry of Rn -- Appendix 4: Manifolds and tangent spaces -- Appendix 5: Taylor expansion for functions of several variables -- Appendix 6: Inverting a partitioned matrix -- Appendix 7: Central limit theory -- Solutions.
서지주기
Includes bibliographical references (p. [525]-529) and index.
일반주제명
Mathematical statistics. Probabilities.
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020 ▼a 9781461426707 (pbk.)
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082 0 0 ▼a 519.5 ▼2 23
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090 ▼a 519.5 ▼b K26t
100 1 ▼a Keener, Robert W.
245 1 0 ▼a Theoretical statistics : ▼b topics for a core course / ▼c Robert W. Keener.
260 ▼a New York : ▼b Springer, ▼c 2010.
300 ▼a xvii, 538 p. : ▼b ill. ; ▼c 24 cm.
490 1 ▼a Springer texts in statistics, ▼x 1431-875X
504 ▼a Includes bibliographical references (p. [525]-529) and index.
505 0 ▼a Probability and measure -- Exponential families -- Risk, sufficiency, completeness, and ancillarity -- Unbiased estimation -- Curved exponential families -- Conditional distributions -- Bayesian estimation -- Large-sample theory -- Estimating equations and maximum likelihood -- Equivariant estimation -- Empirical bayes and shrinkage estimators -- Hypothesis testing -- Optimal tests in higher dimensions -- General linear model -- Bayesian inference : modeling and computation -- Asymptotic optimality -- Large-sample theory for likelihood ratio tests -- Nonparametric regression -- Bootstrap methods -- Sequential methods -- Appendix 1: Functions -- Appendix 2: Topology and continuity in Rn -- Appendix 3: Vector spaces and the geometry of Rn -- Appendix 4: Manifolds and tangent spaces -- Appendix 5: Taylor expansion for functions of several variables -- Appendix 6: Inverting a partitioned matrix -- Appendix 7: Central limit theory -- Solutions.
650 0 ▼a Mathematical statistics.
650 0 ▼a Probabilities.
830 0 ▼a Springer texts in statistics.
945 ▼a ITMT

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목차

Probability and Measure.- Exponential Families.- Risk, Sufficiency, Completeness, and Ancillarity.- Unbiased Estimation.- Curved Exponential Families.- Conditional Distributions.- Bayesian Estimation.- Large-Sample Theory.- Estimating Equations and Maximum Likelihood.- Equivariant Estimation.- Empirical Bayes and Shrinkage Estimators.- Hypothesis Testing.- Optimal Tests in Higher Dimensions.- General Linear Model.- Bayesian Inference: Modeling and Computation.- Asymptotic Optimality1.- Large-Sample Theory for Likelihood Ratio Tests.- Nonparametric Regression.- Bootstrap Methods.- Sequential Methods.

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