Posted by **BUGSY** at May 21, 2015

English | 2001 | ISBN: 0387952772 | 494 Pages | DJVU | 22 MB

Survival analysis arises in many fields of study including medicine, biology, engineering, public health, epidemiology, and economics. This book provides a comprehensive treatment of Bayesian survival analysis. It presents a balance between theory and applications, and for each class of models discussed…

Posted by **Grev27** at March 30, 2018

English | 2 Oct. 2015 | ISBN: 0133902838 | 250 Pages | PDF (True) | 19.4 MB

Posted by **exLib** at July 4, 2013

World Scientific Publishing | 2001 | ISBN: 9810248652 9789810248659 9789812799548 | 438 pages | PDF | 15 MB

This volume is a collection of articles on system and Bayesian reliability analysis. The book is dedicated to Emeritus Professor Richard E. Barlow, who is well known for his pioneering research on reliability theory and Bayesian reliability analysis.

Posted by **Jeembo** at May 21, 2018

English | 2017 | ISBN: 3319542737 | 275 Pages | PDF | 13.0 MB

In this book, we provide an easy introduction to Bayesian inference using MCMC techniques, making most topics intuitively reasonable and deriving to appendixes the more complicated matters.

Posted by **arundhati** at May 10, 2018

2018 | ISBN-10: 1482238063 | 330 pages | PDF | 6 MB

Posted by **exLib** at May 2, 2018

ITExLi | 2018 | ISBN: 1789230934 9781789230932 1789230926 9781789230925 | 131 pages | PDF | 11 MB

This book is an introduction to the mathematical analysis of Bayesian decision-making when the state of the problem is unknown but further data about it can be obtained.

Posted by **DZ123** at Feb. 4, 2018

English | 2005 | ISBN: 0471679321 | PDF | pages: 323 | 3.0 mb

Posted by **nebulae** at Feb. 4, 2018

English | ISBN: 1420077473 | 2018 | 616 pages | PDF | 10 MB

Posted by **Grev27** at Jan. 21, 2018

English | ISBN: 1785883801 | 2016 | EPUB/MOBI+Code files | 282 pages | 43 MB

Posted by **hill0** at Jan. 19, 2018

English | 29 Oct. 2013 | ISBN: 1461486866 | 312 Pages | EPUB | 5.34 MB

This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package