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Essentials of Statistical Inference (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 16) 🔍
G. A. Young, R. L. Smith, G.A YOUNG Cambridge, UK ; New York: Cambridge University Press, Cambridge University Press, Cambridge, 2005
英语 [en] · PDF · 12.2MB · 2005 · 📗 未知类型的图书 · 🚀/ia · Save
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.
备选标题
Essentials of statistical inference : G.A. Young, R.L. Smith
备选作者
Young, G. A. (G. Alastair); Smith, Richard L., 1953-
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
United Kingdom and Ireland, United Kingdom
备用版本
July 25, 2005
元数据中的注释
Includes bibliographical references (p. [218]-222) and index.
备用描述
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
<p><p>concise Account Of Main Approaches; First Textbook To Synthesize Modern Computation With Basic Theory.</p>
备用描述
x, 225 p. ; 27 cm
Includes bibliographical references (p. [218]-222) and index
开源日期
2024-07-01
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