Inhaltsangabe
Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis
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.
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Über die Autorin bzw. den Autor
Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Doanld B. Rubin
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
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Bayesian Data Analysis, 3rd edition (Chapman & Hall/CRC Texts in Statistical Science)
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U.S.A.: Chapman and Hall/CRC, 2013
ISBN 10: 1439840954
ISBN 13: 9781439840955
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Soft cover. Zustand: New. Zustand des Schutzumschlags: New. 3rd Edition, International Edition. **INTERNATIONAL EDITION** Read carefully before purchase: This book is the international edition in mint condition with the different ISBN and book cover design, the major content is printed in full English as same as the original North American edition. The book printed in black and white, generally send in twenty-four hours after the order confirmed. All shipments go through via USPS/UPS/DHL with tracking numbers. Great professional textbook selling experience and expedite shipping service. Bestandsnummer des Verkäufers ABE-8693184296589653654
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Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)
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Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)
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Hardcover. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Bestandsnummer des Verkäufers S_449273436
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Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)
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Bayesian Data Analysis
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Zustand: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers. Bestandsnummer des Verkäufers 13005338-5
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Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)
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hardcover. Zustand: New. 3rd Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes). Bestandsnummer des Verkäufers 001059885N
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Bayesian Data Analysis, Third Edition (Chapman & Hall/CRC Texts in Statistical Science)
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Zustand: New. New Book. Bestandsnummer des Verkäufers 1439840954-TUX
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Bayesian Data Analysis
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Bayesian Data Analysis (Hardcover)
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Hardcover. Zustand: new. Hardcover. 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 authorsall leaders in the statistics communityintroduce 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 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 books web page. "Preface This book is intended to have three roles and to serve three associated audiences: an introductory text on Bayesian inference starting from first principles, a graduate text on effective current approaches to Bayesian modeling and computation in statistics and related fields, and a handbook of Bayesian methods in applied statistics for general users of and researchers in applied statistics. Although introductory in its early sections, the book is definitely not elementary in the sense of a first text in statistics. The mathematics used in our book is basic probability and statistics, elementary calculus, and linear algebra. A review of probability notation is given in Chapter 1 along with a more detailed list of topics assumed to have been studied. The practical orientation of the book means that the reader's previous experience in probability, statistics, and linear algebra should ideally have included strong computational components. To write an introductory text alone would leave many readers with only a taste of the conceptual elements but no guidance for venturing into genuine practical applications, beyond those where Bayesian methods agree essentially with standard non-Bayesian analyses. On the other hand, we feel it would be a mistake to present the advanced methods without first introducing the basic concepts from our data-analytic perspective. Furthermore, due to the nature of applied statistics, a text on current Bayesian methodology would be incomplete without a variety of worked examples drawn from real applications. To avoid cluttering the main narrative, there are bibliographic notes at the end of each chapter and references at the end of the book"-- This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781439840955
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Bayesian Data Analysis (Chapman & Hall / CRC Texts in Statistical Science)
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Condition: Excellent (See the picture. Just a small bump on the left-down corner of the back cover. Not important). "Bayesian Data Analysis, Third Edition" is the leading graduate textbook on applied Bayesian inference and statistical modeling, offering an accessible and practical approach to real-world data analysis problems. This comprehensive reference covers fundamental concepts like prior and posterior distributions and hierarchical models, and then progresses to advanced computational methods including Hamiltonian Monte Carlo (HMC) using Stan and Markov Chain Monte Carlo (MCMC) simulation. This edition features expanded content on nonparametric Bayesian modeling techniques such as Gaussian processes and Dirichlet process mixtures, along with updated discussions on Bayesian model checking and comparison using cross-validation and predictive information criteria. It's an essential resource for statistics students and researchers seeking to perform modern applied Bayesian statistics with up-to-date software code. Bestandsnummer des Verkäufers ABE-1760355457420
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