On Nonparametric Bayesian Hierarchical Modelling PDF Download
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Author | : Liping Liu |
Publisher | : |
Total Pages | : 96 |
Release | : 1996 |
Genre | : Bayesian statistical decision theory |
ISBN | : |
Download On Nonparametric Bayesian Hierarchical Modelling Book in PDF, ePub and Kindle
Author | : Nils Lid Hjort |
Publisher | : Cambridge University Press |
Total Pages | : 309 |
Release | : 2010-04-12 |
Genre | : Mathematics |
ISBN | : 1139484605 |
Download Bayesian Nonparametrics Book 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.
Author | : J.K. Ghosh |
Publisher | : Springer Science & Business Media |
Total Pages | : 311 |
Release | : 2006-05-11 |
Genre | : Mathematics |
ISBN | : 0387226540 |
Download Bayesian Nonparametrics Book 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.
Author | : Kert Viele |
Publisher | : |
Total Pages | : 0 |
Release | : 1996 |
Genre | : |
ISBN | : |
Download Nonparametric Bayesian Methods for Evaluating Fit in Hierarchical Models Book in PDF, ePub and Kindle
Author | : Peter Müller |
Publisher | : Springer |
Total Pages | : 203 |
Release | : 2015-06-17 |
Genre | : Mathematics |
ISBN | : 3319189689 |
Download Bayesian Nonparametric Data Analysis Book 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.
Author | : Dipak D. Dey |
Publisher | : Springer Science & Business Media |
Total Pages | : 376 |
Release | : 2012-12-06 |
Genre | : Mathematics |
ISBN | : 1461217326 |
Download Practical Nonparametric and Semiparametric Bayesian Statistics Book in PDF, ePub and Kindle
A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparametric methods, how to use modern computational tools to summarize inferences, and how to apply these methodologies through the analysis of case studies.
Author | : Michael D. Escobar |
Publisher | : |
Total Pages | : 14 |
Release | : 1992 |
Genre | : Bayesian statistical decision theory |
ISBN | : |
Download Computing Bayesian Nonparametric Hierarchical Models Book in PDF, ePub and Kindle
Author | : Jan Alexander Gasthaus |
Publisher | : |
Total Pages | : |
Release | : 2020 |
Genre | : |
ISBN | : |
Download Hierarchical Bayesian Nonparametric Models for Power-law Sequences Book in PDF, ePub and Kindle
Author | : Andrew Gelman |
Publisher | : CRC Press |
Total Pages | : 677 |
Release | : 2013-11-01 |
Genre | : Mathematics |
ISBN | : 1439840954 |
Download Bayesian Data Analysis, Third Edition Book 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.
Author | : Riten Mitra |
Publisher | : Springer |
Total Pages | : 448 |
Release | : 2015-07-25 |
Genre | : Medical |
ISBN | : 3319195182 |
Download Nonparametric Bayesian Inference in Biostatistics Book in PDF, ePub and Kindle
As chapters in this book demonstrate, BNP has important uses in clinical sciences and inference for issues like unknown partitions in genomics. Nonparametric Bayesian approaches (BNP) play an ever expanding role in biostatistical inference from use in proteomics to clinical trials. Many research problems involve an abundance of data and require flexible and complex probability models beyond the traditional parametric approaches. As this book's expert contributors show, BNP approaches can be the answer. Survival Analysis, in particular survival regression, has traditionally used BNP, but BNP's potential is now very broad. This applies to important tasks like arrangement of patients into clinically meaningful subpopulations and segmenting the genome into functionally distinct regions. This book is designed to both review and introduce application areas for BNP. While existing books provide theoretical foundations, this book connects theory to practice through engaging examples and research questions. Chapters cover: clinical trials, spatial inference, proteomics, genomics, clustering, survival analysis and ROC curve.