An Introduction to Bayesian Analysis pdf epub mobi txt 電子書下載2025

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出版者:Springer

作者:Jayanta K. Ghosh

出品人:

頁數:372

译者:

出版時間:2006-7-27

價格:GBP 72.50

裝幀:Hardcover

isbn號碼:9780387400846

叢書系列:Springer Texts in Statistics

圖書標籤:

機器學習
統計學
Bayesian
計算機科學
計算
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tangrui9105的計算機科學
Springer

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This is a graduate-level textbook on Bayesian analysis blending modern Bayesian theory, methods, and applications. Starting from basic statistics, undergraduate calculus and linear algebra, ideas of both subjective and objective Bayesian analysis are developed to a level where real-life data can be analyzed using the current techniques of statistical computing. Advances in both low-dimensional and high-dimensional problems are covered, as well as important topics such as empirical Bayes and hierarchical Bayes methods and Markov chain Monte Carlo (MCMC) techniques. Many topics are at the cutting edge of statistical research. Solutions to common inference problems appear throughout the text along with discussion of what prior to choose. There is a discussion of elicitation of a subjective prior as well as the motivation, applicability, and limitations of objective priors. By way of important applications the book presents microarrays, nonparametric regression via wavelets as well as DMA mixtures of normals, and spatial analysis with illustrations using simulated and real data. Theoretical topics at the cutting edge include high-dimensional model selection and Intrinsic Bayes Factors, which the authors have successfully applied to geological mapping. The style is informal but clear. Asymptotics is used to supplement simulation or understand some aspects of the posterior.