Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science Book 106)

Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science Book 106)

Winner of the 2016 De Groot Prize from the International Society for Bayesian AnalysisNow in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors?all leaders in the statistics community?introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice.New to the Third EditionFour new chapters on nonparametric modelingCoverage of weakly informative priors and boundary-avoiding priorsUpdated discussion of cross-validation and predictive information criteriaImproved convergence monitoring and effective sample size calculations for iterative simulationPresentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagationNew and revised software codeThe book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book?s web page.

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Editorial Reviews

Review

The second edition was reviewed. A woman named Jasa. 10 years later, we still have an even more impressive textbook that stands for what data analysis should be. This is the reference book for a graduate course on statistics and data analysis. Christian P. Robert. The American Statistical Association has a journal. September 2014, Vol. A hundred and ninety-nine.

Praise for the second edition. It is the best book about data analysis currently available. When students or colleagues ask me which book they need to start with in order to take them as far as possible down the road toward analyzing their own data, Gelman et al, there is enough important additional material here that those with the first edition should seriously consider updating to the new version. The second edition makes this even more robust. Lawrence Joseph is a doctor at Montreal General Hospital. Statistics in medicine. 2, Vol. 23, 2004.

I am excited to have this book in my possession so that I can offer more sophisticated methods to solve their research problems. John Grego is from the University of South Carolina.

The most comprehensive, scholarly, and thoughtful book on the subject will do a lot to promote the use of Bayesian methods. The University of California, Berkeley is in the USA.

About the Author

Andrew Gelman is Professor of Statistics and Professor of Political Science at Columbia University. He has published over 150 articles in statistical theory, methods, and computation, and in applications areas including decision analysis, survey sampling, political science, public health, and policy. His other books are Bayesian Data Analysis (1995, second edition 2003) and Teaching Statistics: A Bag of Tricks (2002).

Donald B. Rubin is John L. Loeb Professor of Statistics at Harvard University, where he has been professor since 1983 and department chair for thirteen of those years. He has authored or coauthored nearly four hundred publications (including ten books), has four joint patents, and has made important contributions to statistical theory and methodology, particularly in causal inference, design and analysis of experiments and sample surveys, treatment of missing data, and Bayesian data analysis. Rubin has received the Samuel S. Wilks Medal from the American Statistical Association, the Parzen Prize for Statistical Innovation, the Fisher Lectureship, and the George W. Snedecor Award from the Committee of Presidents of Statistical Societies. He was named Statistician of the Year by the American Statistical Association, Boston and Chicago chapters. He is one of the most highly cited authors in mathematics and economics with nearly 150,000 citations to date. –This text refers to an alternate kindle_edition edition.

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#553,454 in Kindle Store (See Top 100 in Kindle Store) #276 in Probability & Statistics (Kindle Store) #1,831 in Probability & Statistics (Books)

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