Bayesian methods for data analysis Carlin, Bradley P.
By: Carlin, Bradley P
Contributor(s): Louis, Thomas A
Series: Chapman and Hall/CRC texts in statistical science seriesPublisher: Boca Raton Chapman and Hall/CRC Press 2009Description: xv, 535 p.ISBN: 9781584886976Subject(s): Bayesian statistical decision theoryDDC classification: 519.542 Summary: 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. Source: http://search.barnesandnoble.com
| Item type | Current location | Item location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
| Books | Vikram Sarabhai Library | Slot 1675 (2 Floor, East Wing) | 519.542 C2B2 (Browse shelf) | Available | 167122 |
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| 519.542 B6B2 Bayesian epistemology | 519.542 B7B2 Bayesian methods for repeated measures | 519.542 C2 Case studies in Bayesian statistical modelling and analysis | 519.542 C2B2 Bayesian methods for data analysis | 519.542 C6A7 Applied bayesian hierarchical methods | 519.542 C6A7 Applied bayesian statistics: with R and OpenBUGS examples | 519.542 C6B2 Bayesian statistical modelling |
Includes bibliographical references (p. [487]-520) and indexes
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. Source: http://search.barnesandnoble.com
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