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 pISBN: 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 |
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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