Statistical Inference (2nd Ed.) An Integrated Approach, Second Edition Chapman & Hall/CRC Texts in Statistical Science Series
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.
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.
Date de parution : 10-2014
Ouvrage de 366 p.
15.6x23.4 cm
Thème de Statistical Inference :
Mots-clés :
HPD Interval; HPD Credibility Interval; Empirical Bayes And Penalized Likelihoods; Intrinsic Bayes Factor; Comparative Approach To Inference; Posterior Distribution; Method Of Moments; Non-informative Prior; Bayesian And Frequentist Inference; Maximum Likelihood Estimator; Regression Models; Bayes Factor; Hypothesis Testing; Minimal Training Sample; Standard Inference Courses; Minimal Sufficient Statistics; Bias Correction; Maximum Likelihood Ratio Test; Prior Distribution; Predictive Distribution; Fisher Information Measures; Pivotal Quantity; Ump Test; Empirical Bayes Estimators; Conditional Expectation; Credibility Interval; Em Algorithm; Asymptotic Confidence Region; Minimal Sufficient; Jeffreys Prior; Poisson Exponential Distribution; Marginal Likelihood; UMVU Estimator