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" A graduate course on statistical inference / "
Bing Li, G. Jogesh Babu.
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BL
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| Record Number
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851779
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| Main Entry
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Li, Bing,1960-
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| Title & Author
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A graduate course on statistical inference /\ Bing Li, G. Jogesh Babu.
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| Publication Statement
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New York :: Springer,, [2019]
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, ©2019
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| Series Statement
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Springer texts in statistics,
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| Page. NO
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1 online resource :: illustrations
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| ISBN
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1493997602
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: 1493997610
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: 9781493997602
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: 9781493997619
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1493997599
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9781493997596
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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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.
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| Abstract
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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.
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| Subject
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Mathematical statistics.
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Mathematical statistics.
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| Dewey Classification
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519.5/4
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| LC Classification
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QA276.L5 2019eb
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| Added Entry
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Babu, Gutti Jogesh,1949-
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