Bayesian methods for data analysis / Bradley P. Carlin, Thomas A. Louis
Tipo de material:
TextoSeries Texts in statistical science ; 78Detalles de publicación: Boca Raton (Florida) : CRC Press, 2008 Edición: 3rd ed.Descripción: XV, 535 p. : il. ; 25 cmISBN: 978-1-58488-697-6Tema(s): Estadística bayesiana | Estadística matemáticaResumen: The third edition of "Bayesian Methods for Data Analysis" has been updated to provide a more accessible introduction to the foundations of Bayesian analysis along with a stronger focus on applications, including case studies in biostatistics, epidemiology, and genetics. This edition features a new chapter on Bayesian design that presents Bayesian clinical trials and special topics such as missing data and causality. With an emphasis on computation, there is also expanded coverage of WinBUGS, R, and BRugs. The book also contains additional exercises and solutions for courses on Bayesian data analysis and to assist in self-study for undergraduate students, graduate students, and researchers in statistics and biostatistics.Resumen: Índice: Approaches for statistical inference. The Bayes approach. Bayesiancomputation. Model criticism and selection. The empirical Bayes approach. Bayesian design. Special methods and models. Biostatistical methods. Case studies. Appendices
| Tipo de ítem | Biblioteca de origen | Signatura | URL | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems |
|---|---|---|---|---|---|---|---|
| Monografías | 07. BIBLIOTECA CIENCIAS SOCIALES Y JURÍDICAS | 519.816/CAR/bay (Navegar estantería(Abre debajo)) | Texto completo | Prestado | 31/01/2025 | 3743150624 |
Bibliografía: p. [487]-520
The third edition of "Bayesian Methods for Data Analysis" has been updated to provide a more accessible introduction to the foundations of Bayesian analysis along with a stronger focus on applications, including case studies in biostatistics, epidemiology, and genetics. This edition features a new chapter on Bayesian design that presents Bayesian clinical trials and special topics such as missing data and causality. With an emphasis on computation, there is also expanded coverage of WinBUGS, R, and BRugs. The book also contains additional exercises and solutions for courses on Bayesian data analysis and to assist in self-study for undergraduate students, graduate students, and researchers in statistics and biostatistics.
Índice: Approaches for statistical inference. The Bayes approach. Bayesiancomputation. Model criticism and selection. The empirical Bayes approach. Bayesian design. Special methods and models. Biostatistical methods. Case studies. Appendices
No hay comentarios en este titulo.