Structural equation modeling: a bayesian approach / Lee, S.-Y. (2007)

Public ISBD Titre : Structural equation modeling: a bayesian approach Type de document : livre Auteurs : Lee, S.-Y. Editeur : Chichester, U.K. : Wiley Année de publication : 2007 Collection : Wiley series in probability and statistics Importance : 432 p. ISBN/ISSN/EAN : 978-0-470-02423-2 Note générale : Inventaire 2007: Pointé et emprunté le 05/07/2007 Langues : Anglais (eng) Mots-clés : Bayesian statistical decision theory  Modeling Résumé : Structural equation modeling (SEM) is a powerful multivariate method allowing the evaluation of a series of simultaneous hypotheses about the impacts of latent and manifest variables on other variables, taking measurement errors into account. As SEMs have grown in popularity in recent years, new models and statistical methods have been developed for more accurate analysis of more complex data. A Bayesian approach to SEMs allows the use of prior information resulting in improved parameter estimates, latent variable estimates, and statistics for model comparison, as well as offering more reliable results for smaller samples. Note de contenu : Hbk; Structural equation modeling: a bayesian approach [livre] / Lee, S.-Y. . - Chichester, U.K. : Wiley, 2007 . - 432 p.. - (Wiley series in probability and statistics) . ISBN : 978-0-470-02423-2 Inventaire 2007: Pointé et emprunté le 05/07/2007 Langues : Anglais (eng) Mots-clés : Bayesian statistical decision theory  Modeling Résumé : Structural equation modeling (SEM) is a powerful multivariate method allowing the evaluation of a series of simultaneous hypotheses about the impacts of latent and manifest variables on other variables, taking measurement errors into account. As SEMs have grown in popularity in recent years, new models and statistical methods have been developed for more accurate analysis of more complex data. A Bayesian approach to SEMs allows the use of prior information resulting in improved parameter estimates, latent variable estimates, and statistics for model comparison, as well as offering more reliable results for smaller samples. Note de contenu : Hbk;

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
67831	Lee_11_67831	Livre	Salle des ouvrages	11_Mathématiques	Disponible

Bayesian models for categorical data / Congdon, P. (2005)  

Public ISBD Titre : Bayesian models for categorical data Type de document : livre Auteurs : Congdon, P. Editeur : Chichester, U.K. : Wiley Année 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-clés : Bayesian statistical decision theory  Markov processes  Monte Carlo method  Multivariate analysis Résumé : 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 éditeur] 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-clés : Bayesian statistical decision theory  Markov processes  Monte Carlo method  Multivariate analysis Résumé : 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 éditeur] Note de contenu : Hbk; En ligne : http://www.loc.gov/catdir/toc/ecip058/2005005158.html

Exemplaires (1)

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

Applied Bayesian modelling / Congdon, P. (2003)  

Public ISBD Titre : Applied Bayesian modelling Type de document : livre Auteurs : Congdon, P. Editeur : Chichester, U.K. : Wiley Année 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-clés : Bayesian statistical decision theory  Mathematical statistics Résumé : 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. [Résumé éditeur] 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-clés : Bayesian statistical decision theory  Mathematical statistics Résumé : 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. [Résumé éditeur] En ligne : http://www.loc.gov/catdir/toc/wiley031/2002035732.html

Exemplaires (1)

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

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