Bayesian hierarchical models with applications using R / by Peter D. Congdon, University of London, England.

Author/creator Congdon, P.
Format Electronic
EditionSecond edition.
Publication InfoBoca Raton : CRC Press/Taylor & Francis Group, [2020]
Descriptionxii, 579 pages : illustrations ; 27 cm
Supplemental ContentFull text available from Taylor & Francis eBooks
Subjects

Uniform titleApplied Bayesian hierarchical methods
Abstract "The new edition is a revision of the book Applied Bayesian Hierarchical Methods. It maintains a focus on applied modelling and data analysis, but now using entirely R based Bayesian computing options. It has been updated with a new chapter on regression for causal effects, and one on computing options and strategies. This latter chapter is particularly important, due to recent advances in Bayesian computing and estimation, including the development of rjags and rstan. It also features updates throughout with new examples"-- Provided by publisher.
General noteRevised edition of: Applied Bayesian hierarchical methods. c2010.
Bibliography noteIncludes bibliographical references and index.
Access restrictionAvailable only to authorized users.
Technical detailsMode of access: World Wide Web
Genre/formElectronic books.
LCCN 2019024162
ISBN9781498785754 (hardback)
ISBN(ebook)

Availability

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Electronic Resources Access Content Online ✔ Available