Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 67,30
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 72,92
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
EUR 69,31
Cantidad disponible: 3 disponibles
Añadir al carritoCondición: New.
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 66,70
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 66,69
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 67,42
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
EUR 86,21
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. 2nd edition NO-PA16APR2015-KAP.
EUR 77,16
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Idioma: Inglés
Publicado por Chapman & Hall 2021-09-30, 2021
ISBN 10: 1032177152 ISBN 13: 9781032177151
Librería: Chiron Media, Wallingford, Reino Unido
EUR 74,38
Cantidad disponible: Más de 20 disponibles
Añadir al carritoPaperback. Condición: New.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 105,76
Cantidad disponible: 2 disponibles
Añadir al carritoPaperback. Condición: Brand New. 2nd edition. 580 pages. 10.00x7.00x1.34 inches. In Stock.
Librería: preigu, Osnabrück, Alemania
EUR 63,10
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Bayesian Hierarchical Models | With Applications Using R, Second Edition | Peter D. Congdon | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2021 | Chapman and Hall/CRC | EAN 9781032177151 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 55,04
Cantidad disponible: 5 disponibles
Añadir al carritoPaperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
EUR 85,21
Cantidad disponible: Más de 20 disponibles
Añadir al carritoPAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
EUR 78,19
Cantidad disponible: Más de 20 disponibles
Añadir al carritoPAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Idioma: Inglés
Publicado por Chapman And Hall/CRC Sep 2021, 2021
ISBN 10: 1032177152 ISBN 13: 9781032177151
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 63,60
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods.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.The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities.Features:Provides a comprehensive and accessible overview of applied Bayesian hierarchical modellingIncludes many real data examples to illustrate different modelling topicsR code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementationSoftware options and coding principles are introduced in new chapter on computingPrograms and data sets available on the book's website 594 pp. Englisch.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 85,36
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND.
Librería: moluna, Greven, Alemania
EUR 57,92
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Peter Congdon is Research Professor in Quantitative Geography and Health Statistics at Queen Mary, University of London.An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demo.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 75,53
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An intermediate-level treatment of Bayesian hierarchical models and their applications, this book demonstrates the advantages of a Bayesian approach to data sets involving inferences for collections of related units or variables, and in methods where parameters can be treated as random collections. Through illustrative data analysis and attention to statistical computing, this book facilitates practical implementation of Bayesian hierarchical methods.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.The examples exploit and illustrate the broader advantages of the R computing environment, while allowing readers to explore alternative likelihood assumptions, regression structures, and assumptions on prior densities.Features:Provides a comprehensive and accessible overview of applied Bayesian hierarchical modellingIncludes many real data examples to illustrate different modelling topicsR code (based on rjags, jagsUI, R2OpenBUGS, and rstan) is integrated into the book, emphasizing implementationSoftware options and coding principles are introduced in new chapter on computingPrograms and data sets available on the book's website.