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## Auteur Congdon, P. |

### Documents disponibles écrits par cet auteur (3)

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Titre : Bayesian statistical modelling Type de document : livre Auteurs : Congdon, P. Mention d'Ã©dition : 2nd ed. Editeur : Hoboken, New Jersey, USA : Wiley AnnÃ©e de publication : 2006 Collection : Wiley series in probability and statistics Importance : 573 p. ISBN/ISSN/EAN : 978-0-470-01875-0 Langues : Anglais ( eng)Mots-clÃ©s : Bayesian statistical decision theory Modeling RÃ©sumÃ© : Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide range of areas. The calculations were previously complex, but it is now possible to routinely apply Bayesian methods due to advances in computing technology and the use of new sampling methods for estimating parameters. Such developments together with the availability of freeware such as WINBUGS and R have facilitated a rapid growth in the use of Bayesian methods, allowing their application in many scientific disciplines, including applied statistics, public health research, medical science, the social sciences and economics. Following the success of the first edition, this reworked and updated book provides an accessible approach to Bayesian computing and analysis, with an emphasis on the principles of prior selection, identification and the interpretation of real data sets. [RÃ©sumÃ© Ã©diteur] En ligne : http://www.loc.gov/catdir/toc/ecip0617/2006023990.html Bayesian statistical modelling [livre] / Congdon, P. . - 2nd ed. . - Hoboken, New Jersey, USA : Wiley, 2006 . - 573 p.. - (Wiley series in probability and statistics) .ISBN: 978-0-470-01875-0

Langues : Anglais (eng)

Mots-clÃ©s : Bayesian statistical decision theory Modeling RÃ©sumÃ© : Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide range of areas. The calculations were previously complex, but it is now possible to routinely apply Bayesian methods due to advances in computing technology and the use of new sampling methods for estimating parameters. Such developments together with the availability of freeware such as WINBUGS and R have facilitated a rapid growth in the use of Bayesian methods, allowing their application in many scientific disciplines, including applied statistics, public health research, medical science, the social sciences and economics. Following the success of the first edition, this reworked and updated book provides an accessible approach to Bayesian computing and analysis, with an emphasis on the principles of prior selection, identification and the interpretation of real data sets. [RÃ©sumÃ© Ã©diteur] En ligne : http://www.loc.gov/catdir/toc/ecip0617/2006023990.html ## Exemplaires (1)

Code-barres Cote Support Localisation Section DisponibilitÃ© 67830 CON_11_67830 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 25/05/2043

Titre : Bayesian models for categorical data Type de document : livre Auteurs : Congdon, P. Editeur : Chichester, U.K. : Wiley AnnÃ©e de publication : 2005 Collection : Wiley series in probability and statistics Importance : 425 p. ISBN/ISSN/EAN : 978-0-470-09237-8 Langues : Anglais ( eng)Mots-clÃ©s : Bayesian statistical decision theory Markov processes Monte Carlo method Multivariate analysis RÃ©sumÃ© : The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods for Categorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike. Emphasizing the use of statistical computing and applied data analysis, this book provides a comprehensive introduction to Bayesian methods of categorical outcomes. * Reviews recent Bayesian methodology for categorical outcomes (binary, count and multinomial data). * Considers missing data models techniques and non-standard models (ZIP and negative binomial). * Evaluates time series and spatio-temporal models for discrete data. * Features discussion of univariate and multivariate techniques. * Provides a set of downloadable worked examples with documented WinBUGS code, available from an ftp site. The author's previous 2 bestselling titles provided a comprehensive introduction to the theory and application of Bayesian models. Bayesian Models for Categorical Data continues to build upon this foundation by developing their application to categorical, or discrete data - one of the most common types of data available. The author's clear and logical approach makes the book accessible to a wide range of students and practitioners, including those dealing with categorical data in medicine, sociology, psychology and epidemiology. [Description Ã©diteur] Note de contenu : Hbk; En ligne : http://www.loc.gov/catdir/toc/ecip058/2005005158.html Bayesian models for categorical data [livre] / Congdon, P. . - Chichester, U.K. : Wiley, 2005 . - 425 p.. - (Wiley series in probability and statistics) .ISBN: 978-0-470-09237-8

Langues : Anglais (eng)

Mots-clÃ©s : Bayesian statistical decision theory Markov processes Monte Carlo method Multivariate analysis RÃ©sumÃ© : The use of Bayesian methods for the analysis of data has grown substantially in areas as diverse as applied statistics, psychology, economics and medical science. Bayesian Methods for Categorical Data sets out to demystify modern Bayesian methods, making them accessible to students and researchers alike. Emphasizing the use of statistical computing and applied data analysis, this book provides a comprehensive introduction to Bayesian methods of categorical outcomes. * Reviews recent Bayesian methodology for categorical outcomes (binary, count and multinomial data). * Considers missing data models techniques and non-standard models (ZIP and negative binomial). * Evaluates time series and spatio-temporal models for discrete data. * Features discussion of univariate and multivariate techniques. * Provides a set of downloadable worked examples with documented WinBUGS code, available from an ftp site. The author's previous 2 bestselling titles provided a comprehensive introduction to the theory and application of Bayesian models. Bayesian Models for Categorical Data continues to build upon this foundation by developing their application to categorical, or discrete data - one of the most common types of data available. The author's clear and logical approach makes the book accessible to a wide range of students and practitioners, including those dealing with categorical data in medicine, sociology, psychology and epidemiology. [Description Ã©diteur] Note de contenu : Hbk; En ligne : http://www.loc.gov/catdir/toc/ecip058/2005005158.html ## Exemplaires (1)

Code-barres Cote Support Localisation Section DisponibilitÃ© 68368 Con_11_68368 Livre Salle des ouvrages 11_Mathématiques Disponible

Titre : Applied Bayesian modelling Type de document : livre Auteurs : Congdon, P. Editeur : Chichester, U.K. : Wiley AnnÃ©e de publication : 2003 Collection : Wiley series in probability and statistics Importance : 457 p. ISBN/ISSN/EAN : 978-0-471-48695-4 Langues : Anglais ( eng)Mots-clÃ©s : Bayesian statistical decision theory Mathematical statistics RÃ©sumÃ© : The use of Bayesian statistics has grown significantly in recent years, and will undoubtedly continue to do so. Applied Bayesian Modelling is the follow-up to the author's best selling book, Bayesian Statistical Modelling, and focuses on the potential applications of Bayesian techniques in a wide range of important topics in the social and health sciences. The applications are illustrated through many real-life examples and software implementation in WINBUGS - a popular software package that offers a simplified and flexible approach to statistical modelling. The book gives detailed explanations for each example - explaining fully the choice of model for each particular problem. The book provides a good introduction to Bayesian modelling and data analysis for a wide range of people involved in applied statistical analysis, including researchers and students from statistics, and the health and social sciences. The wealth of examples makes this book an ideal reference for anyone involved in statistical modelling and analysis. [RÃ©sumÃ© Ã©diteur] En ligne : http://www.loc.gov/catdir/toc/wiley031/2002035732.html Applied Bayesian modelling [livre] / Congdon, P. . - Chichester, U.K. : Wiley, 2003 . - 457 p.. - (Wiley series in probability and statistics) .ISBN: 978-0-471-48695-4

Langues : Anglais (eng)

Mots-clÃ©s : Bayesian statistical decision theory Mathematical statistics RÃ©sumÃ© : The use of Bayesian statistics has grown significantly in recent years, and will undoubtedly continue to do so. Applied Bayesian Modelling is the follow-up to the author's best selling book, Bayesian Statistical Modelling, and focuses on the potential applications of Bayesian techniques in a wide range of important topics in the social and health sciences. The applications are illustrated through many real-life examples and software implementation in WINBUGS - a popular software package that offers a simplified and flexible approach to statistical modelling. The book gives detailed explanations for each example - explaining fully the choice of model for each particular problem. The book provides a good introduction to Bayesian modelling and data analysis for a wide range of people involved in applied statistical analysis, including researchers and students from statistics, and the health and social sciences. The wealth of examples makes this book an ideal reference for anyone involved in statistical modelling and analysis. [RÃ©sumÃ© Ã©diteur] En ligne : http://www.loc.gov/catdir/toc/wiley031/2002035732.html ## Exemplaires (1)

Code-barres Cote Support Localisation Section DisponibilitÃ© 67829 CON_11_67829 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 25/05/2043