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基本説明
Unique in its presentation of topics from both classical and Bayesian perspectives, this second edition balances both sides elegantly and describes the relative strengths and weaknesses of the different approaches in each case.
Full Description
A Balanced Treatment of Bayesian and Frequentist Inference
Statistical Inference: An Integrated Approach, Second Edition presents an account of the Bayesian and frequentist approaches to statistical inference. Now with an additional author, this second edition places a more balanced emphasis on both perspectives than the first edition.
New to the Second Edition
New material on empirical Bayes and penalized likelihoods and their impact on regression models
Expanded material on hypothesis testing, method of moments, bias correction, and hierarchical models
More examples and exercises
More comparison between the approaches, including their similarities and differences
Designed for advanced undergraduate and graduate courses, the text thoroughly covers statistical inference without delving too deep into technical details. It compares the Bayesian and frequentist schools of thought and explores procedures that lie on the border between the two. Many examples illustrate the methods and models, and exercises are included at the end of each chapter.
Contents
Introduction. Elements of Inference. Prior Distribution. Estimation. Approximating Methods. Hypothesis Testing. Prediction. Introduction to Linear Models. Sketched Solutions to Selected Exercises. List of Distributions. References. Index.
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