This integrated introduction to fundamentals, computation, and software is your key to understanding and using advanced Bayesian methods.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
M. Antónia Amaral Turkman was, until 2013, full-time Professor in the Department of Statistics and Operations Research, Faculty of Sciences, University of Lisbon. Though retired from the university, she is still a member of its Center of Statistics and Applications, where she held the position of scientific coordinator until 2017. Her research interests are Bayesian statistics, medical and environmental statistics, and spatiotemporal modeling, with recent publications on computational methods in Bayesian statistics, with an emphasis on applications in health and forest fires. She has served as vice president of the Portuguese Statistical Society. She has taught courses on Bayesian statistics and computational statistics, among many others.
Carlos Daniel Paulino is senior academic researcher in the Center of Statistics and Applications and was associate professor with habilitation in the Department of Mathematics of the Instituto Superior Técnico, both at the University of Lisbon. He has published frequently on Bayesian statistics and categorical data, with emphasis on applications in biostatistics. He has served as president of the Portuguese Statistical Society. He taught many undergraduate and graduate level courses, notably in mathematical statistics and Bayesian statistics.
Peter Müller is Professor in the Department of Mathematics and the Department of Statistics and Data Science at the University of Texas, Austin. He has published widely on computational methods in Bayesian statistics, non-parametric Bayesian statistics, and decision problems, with emphasis on applications in biostatistics and bioinformatics. He has served as president of the International Society for Bayesian Analysis, and as chair for the Section on Bayesian Statistics of the American Statistical Association. Besides many graduate-level courses he has taught short courses on Bayesian biostatistics, Bayesian clinical trial design, non-parametric Bayesian inference, medical decision making, and more.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
Da: HPB-Red, Dallas, TX, U.S.A.
paperback. Condizione: 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! Codice articolo S_442496507
Quantità: 1 disponibili
Da: Friends of the Multnomah County Library, Portland, OR, U.S.A.
Softcover. Condizione: Good. Front hinge page starting, but otherwise clean pages tightly bound. Codice articolo 301202511
Quantità: 1 disponibili
Da: Big River Books, Powder Springs, GA, U.S.A.
Condizione: good. This book is in good condition. The cover has minor creases or bends. The binding is tight and pages are intact. Some pages may have writing or highlighting. Codice articolo BRV.1108703747.G
Quantità: 1 disponibili
Da: Prior Books Ltd, Cheltenham, Regno Unito
Paperback. Condizione: Like New. First Edition. In nearly new condition: bright, crisp and clean with no creases, strong joints and sharp corners. Looks and feels unread. Just a small publisher 'damaged' stamp at the prelims. Nonetheless not showing any defects. Thus a very nice copy, firm, square and tight, now offered for sale at a very reasonable price. Codice articolo 208713
Quantità: 1 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 33846984
Quantità: Più di 20 disponibili
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
Condizione: New. Codice articolo ABLIING23Mar2317530286373
Quantità: Più di 20 disponibili
Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New. Codice articolo 33846984-n
Quantità: Più di 20 disponibili
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. Meaningful use of advanced Bayesian methods requires a good understanding of the fundamentals. This engaging book explains the ideas that underpin the construction and analysis of Bayesian models, with particular focus on computational methods and schemes. The unique features of the text are the extensive discussion of available software packages combined with a brief but complete and mathematically rigorous introduction to Bayesian inference. The text introduces Monte Carlo methods, Markov chain Monte Carlo methods, and Bayesian software, with additional material on model validation and comparison, transdimensional MCMC, and conditionally Gaussian models. The inclusion of problems makes the book suitable as a textbook for a first graduate-level course in Bayesian computation with a focus on Monte Carlo methods. The extensive discussion of Bayesian software - R/R-INLA, OpenBUGS, JAGS, STAN, and BayesX - makes it useful also for researchers and graduate students from beyond statistics. This book explains the fundamental ideas of Bayesian analysis, with a focus on computational methods such as MCMC and available software such as R/R-INLA, OpenBUGS, JAGS, Stan, and BayesX. It is suitable as a textbook for a first graduate-level course and as a user's guide for researchers and graduate students from beyond statistics. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781108703741
Quantità: 1 disponibili
Da: Revaluation Books, Exeter, Regno Unito
Paperback. Condizione: Brand New. 243 pages. 9.00x6.00x0.75 inches. In Stock. This item is printed on demand. Codice articolo __1108703747
Quantità: 1 disponibili
Da: Ria Christie Collections, Uxbridge, Regno Unito
Condizione: New. In. Codice articolo ria9781108703741_new
Quantità: Più di 20 disponibili