Bayesian Nonparametric Data Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Bayesian Nonparametric Data Analysis write by Peter Müller. This book was released on 2015-06-17. Bayesian Nonparametric Data Analysis available in PDF, EPUB and Kindle. This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.
Bayesian Nonparametrics
Bayesian Nonparametrics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Bayesian Nonparametrics write by Nils Lid Hjort. This book was released on 2010-04-12. Bayesian Nonparametrics available in PDF, EPUB and Kindle. Bayesian nonparametrics works - theoretically, computationally. The theory provides highly flexible models whose complexity grows appropriately with the amount of data. Computational issues, though challenging, are no longer intractable. All that is needed is an entry point: this intelligent book is the perfect guide to what can seem a forbidding landscape. Tutorial chapters by Ghosal, Lijoi and Prünster, Teh and Jordan, and Dunson advance from theory, to basic models and hierarchical modeling, to applications and implementation, particularly in computer science and biostatistics. These are complemented by companion chapters by the editors and Griffin and Quintana, providing additional models, examining computational issues, identifying future growth areas, and giving links to related topics. This coherent text gives ready access both to underlying principles and to state-of-the-art practice. Specific examples are drawn from information retrieval, NLP, machine vision, computational biology, biostatistics, and bioinformatics.
Bayesian Nonparametrics
Bayesian Nonparametrics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Bayesian Nonparametrics write by J.K. Ghosh. This book was released on 2006-05-11. Bayesian Nonparametrics available in PDF, EPUB and Kindle. This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian non-parametrics.
Bayesian Data Analysis, Third Edition
Bayesian Data Analysis, Third Edition - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Bayesian Data Analysis, Third Edition write by Andrew Gelman. This book was released on 2013-11-01. Bayesian Data Analysis, Third Edition available in PDF, EPUB and Kindle. Now 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 Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The 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.
Fundamentals of Nonparametric Bayesian Inference
Fundamentals of Nonparametric Bayesian Inference - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Fundamentals of Nonparametric Bayesian Inference write by Subhashis Ghosal. This book was released on 2017-06-26. Fundamentals of Nonparametric Bayesian Inference available in PDF, EPUB and Kindle. Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.
