A Graduate Course on Statistical Inference. 1st ed. 2019
- 種類:
- 電子ブック
- 責任表示:
- by Bing Li, G. Jogesh Babu
- 出版情報:
- New York, NY : Springer New York : Imprint: Springer, 2019
- 著者名:
- シリーズ名:
- Springer Texts in Statistics ;
- ISBN:
- 9781493997619 [1493997610]
- 注記:
- 1. Probability and Random Variables -- 2. Classical Theory of Estimation -- 3. Testing Hypotheses in the Presence of Nuisance Parameters -- 4. Testing Hypotheses in the Presence of Nuisance Parameters -- 5. Basic Ideas of Bayesian Methods -- 6. Bayesian Inference -- 7. Asymptotic Tools and Projections -- 8. Asymptotic Theory for Maximum Likelihood Estimation -- 9. Estimating Equations -- 10. Convolution Theorem and Asymptotic Efficiency -- 11. Asymptotic Hypothesis Test -- References -- Index.
This textbook offers an accessible and comprehensive overview of statistical estimation and inference that reflects current trends in statistical research. It draws from three main themes throughout: the finite-sample theory, the asymptotic theory, and Bayesian statistics. The authors have included a chapter on estimating equations as a means to unify a range of useful methodologies, including generalized linear models, generalized estimation equations, quasi-likelihood estimation, and conditional inference. They also utilize a standardized set of assumptions and tools throughout, imposing regular conditions and resulting in a more coherent and cohesive volume. Written for the graduate-level audience, this text can be used in a one-semester or two-semester course. - ローカル注記:
- 学内専用E-BOOKS (local access only)
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Springer Science+Business Media, Inc. |
Springer Science+Business Media, Inc. |
Springer International Publishing : Imprint: Springer |
Springer International Publishing : Imprint: Springer |
Springer New York : Imprint: Springer |
Springer-Verlag New York |
Springer Berlin Heidelberg : Imprint: Springer |
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電子ブック
A History of Parametric Statistical Inference from Bernoulli to Fisher, 1713–1935 [e-books]
Springer Science+Business Media, LLC |