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基本信息·出版社：世界图书出版公司

·页码：617 页

·出版日期：2004年

·ISBN：7506271818

·条形码：9787506271813

·包装版本：第2版

·装帧：精装

·开本：24开

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内容简介The relationships （both conceptual and mathematical） between Bayesian analysis and statistical decision theory are so strong that it is somewhat unnatural to learn one without the other. Nevertheless, major portions of each have developed separately. On the Bayesian side, there is an extensively developed Bayesian theory of statistical inference （both subjective and objective versions）. This theory recognizes the importance of viewing statistical analysis conditionally （i.e., treating observed data as known rather than unknown）, even when no loss function is to be incorporated into the analysis. There is also a well-developed （frequentist） decision theory, which avoids formal utilization of prior distributions and seeks to provide a foundation for frequentist statistical theory. Although the central thread of the book will be Bayesian decision theory, both Bayesian inference and non-Bayesian decision theory will be extensively discussed. Indeed, the book is written so as to allow, say, the teaching of a course on either subject separately.

目录

CHAPTER 1

Basic Concepts

1.1 Introduction

1.2 Basic Elements

1.3 Expected Loss, Decision Rules, and Risk

1.3.1 Bayesian Expected Loss

……[看更多目录]

 

 

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