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Essentials of Statistical Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 16) 🔍
Young, G. A., G. A. Young, R. L. Smith Cambridge : Cambridge University Press, 2005., Cambridge Series in Statistical and Probabilistic Mathematics 16, 1, 2005
英语 [en] · PDF · 3.1MB · 2005 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/upload/zlib · Save
描述
This engaging textbook presents the concepts and results underlying the Bayesian, frequentist and Fisherian approaches to statistical inference, with particular emphasis on the contrasts between them. Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, it covers in a concise treatment both basic mathematical theory and more advanced material, including such contemporary topics as Bayesian computation, higher-order likelihood theory, predictive inference, bootstrap methods and conditional inference. It contains numerous extended examples of the application of formal inference techniques to real data, as well as historical commentary on the development of the subject. Throughout, the text concentrates on concepts, rather than mathematical detail, while maintaining appropriate levels of formality. Each chapter ends with a set of accessible problems. Some prior knowledge of probability is assumed, while some previous knowledge of the objectives and main approaches to statistical inference would be helpful but is not essential.
备用文件名
nexusstc/Essentials of Statistical Inference/67b7728fa1c402fa64f1aa2deda78133.pdf
备用文件名
lgli/_341752.67b7728fa1c402fa64f1aa2deda78133.pdf
备用文件名
lgrsnf/_341752.67b7728fa1c402fa64f1aa2deda78133.pdf
备用文件名
zlib/Mathematics/G. A. Young, R. L. Smith/Essentials of Statistical Inference_1269630.pdf
备选标题
Essentials of statistical inference : G.A. Young, R.L. Smith
备选标题
Essentials_of_statistical_inference_a02
备选作者
Young, G. A., R. L. Smith, G. A. Young
备选作者
G. A. Young, R. L. Smith, Young, G. A
备选作者
G. A. Young, R. L. Smith, G.A YOUNG
备选作者
G. A. Young and R. L. Smith
备选作者
Young, G. A., Smith, R. L.
备选作者
G A Young; Richard L Smith
备选作者
G. Alastair Young
备用出版商
Cambridge University Press (Virtual Publishing)
备用出版商
Greenwich Medical Media Ltd
备用版本
Cambridge series in statistical and probabilistic mathematics, Cambridge series on statistical and probabilistic mathematics, 1st pbk. ed., Cambridge, UK, England, 2010
备用版本
Cambridge series in statistical and probabilistic mathematics, Cambridge series on statistical and probabilistic mathematics, Cambridge, UK, New York, England, 2005
备用版本
Cambridge series on statistical and probabilistic mathematics, 16, Cambridge, UK ; New York, 2005
备用版本
CAMBRIDGE SERIES IN STATISTICAL AND PROBABILISTIC MATHEMATICS; 16, NEW YORK, Unknown
备用版本
Cambridge University Press, Cambridge, 2005
备用版本
United Kingdom and Ireland, United Kingdom
备用版本
Illustrated, 1, PT, 2010
备用版本
July 25, 2005
元数据中的注释
0
元数据中的注释
lg831900
元数据中的注释
producers:
Acrobat Distiller 5.0.5 for Macintosh
元数据中的注释
{"edition":"1","isbns":["0511126166","0511755392","0521548667","0521839718","9780511126161","9780511755392","9780521548663","9780521839716"],"last_page":238,"publisher":"Cambridge University Press","series":"Cambridge Series in Statistical and Probabilistic Mathematics 16"}
元数据中的注释
Includes bibliographical references (p. [218]-222) and index.
元数据中的注释
Includes bibliographical references (p. [218-222) and index.
备用描述
Aimed At Advanced Undergraduate And Graduate Students In Mathematics And Related Disciplines, This Book Presents The Concepts And Results Underlying The Bayesian, Frequentist And Fisherian Approaches, With Particular Emphasis On The Contrasts Between Them. Computational Ideas Are Explained, As Well As Basic Mathematical Theory. Written In A Lucid And Informal Style, This Concise Text Provides Both Basic Material On The Main Approaches To Inference, As Well As More Advanced Material On Developments In Statistical Theory, Including: Material On Bayesian Computation, Such As Mcmc, Higher-order Likelihood Theory, Predictive Inference, Bootstrap Methods And Conditional Inference. It Contains Numerous Extended Examples Of The Application Of Formal Inference Techniques To Real Data, As Well As Historical Commentary On The Development Of The Subject. Throughout, The Text Concentrates On Concepts, Rather Than Mathematical Detail, While Maintaining Appropriate Levels Of Formality. Each Chapter Ends With A Set Of Accessible Problems. G. A. Young, R. L. Smith. Title From Publisher's Bibliographic System (viewed On 01 Jun 2016). Mode Of Access: World Wide Web.
备用描述
"Written in an informal style, this concise text provides both basic material on the main approaches to inference, as well as more advanced material on modern developments in statistical theory, including: contemporary material on Bayesian computation, such as MCMC, higher-order likelihood theory, predictive inference, bootstrap methods and conditional inference. It contains numerous extended examples of the application of formal inference techniques to real data, as well as historical commentary on the development of the subject. Throughout, the text concentrates on concepts, rather than mathematical detail, while maintaining appropriate levels of formality. Each chapter ends with a set of accessible problems." "Based to a large extent on lectures given at the University of Cambridge over a number of years, the material has been polished by student feedback. Some prior knowledge of probability is assumed, while some previous knowledge of the objectives and main approaches to statistical inference would be helpful but is not essential."--BOOK JACKET
备用描述
Cover
......Page 1
Title Page
......Page 5
Contents
......Page 7
Preface
......Page 11
Ch 1. Introduction
......Page 13
Ch 2. Decision Th
eory......Page 16
Ch 3. Bayesian methods
......Page 34
Ch 4. Hypothesis testing
......Page 77
Ch 5. Special models
......Page 93
Ch 6. Sufficiency and completeness
......Page 102
Ch 7. Two-sided tests and conditional inference
......Page 110
Ch 8. Likelihood theory
......Page 133
Ch 9. Higher-order theory
......Page 153
Ch 10. Predictive inference
......Page 182
Ch 11. Bootstrap methods
......Page 203
Bibliography
......Page 231
Index
......Page 236
备用描述
This textbook presents the concepts and results underlying the Bayesian, frequentist, and Fisherian approaches to statistical inference, with particular emphasis on the contrasts between them. Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, it covers basic mathematical theory as well as more advanced material, including such contemporary topics as Bayesian computation, higher-order likelihood theory, predictive inference, bootstrap methods, and conditional inference.
备用描述
Aimed at advanced undergraduates and graduate students in mathematics and related disciplines, this engaging textbook gives a concise account of the main approaches to inference, with particular emphasis on the contrasts between them. It is the first textbook to synthesize contemporary material on computational topics with basic mathematical theory
备用描述
<p><p>concise Account Of Main Approaches; First Textbook To Synthesize Modern Computation With Basic Theory.</p>
开源日期
2012-03-17
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