Posted by **interes** at Jan. 9, 2019

English | ISBN: 1439895554 | 2012 | 243 pages | PDF | 3 MB

Posted by **naag** at Dec. 28, 2018

MP4 | Video: AVC 1280x720 | Audio: AAC 44KHz 2ch | Duration: 1 Hour 10M | 231 MB

Posted by **insetes** at Nov. 21, 2018

2014 | 396 Pages | ISBN: 1466500794 | PDF | 5 MB

Posted by **AvaxGenius** at Sept. 24, 2018

English | EPUB | 2018 | 193 Pages | ISBN : 3319927469 | 10.72 MB

The current textbook has been written as a help to medical / health professionals and students for the study of modern Bayesian statistics, where posterior and prior odds have been replaced with posterior and prior likelihood distributions. Why may likelihood distributions better than normal distributions estimate uncertainties of statistical test results? Nobody knows for sure, and the use of likelihood distributions instead of normal distributions for the purpose has only just begun, but already everybody is trying and using them.

Posted by **Maks_tir** at Sept. 21, 2018

English | 4 May 2018 | ISBN: 1473916356, 1473916364 | 520 Pages | EPUB | 19.18 MB

Posted by **ksveta6** at Aug. 29, 2018

2018 | ISBN: 1138575429 | English | 486 pages | PDF | 22 MB

Posted by **insetes** at Aug. 23, 2018

2017 | 322 Pages | ISBN: 1316642216 | PDF | 12 MB

Posted by **AvaxGenius** at July 2, 2018

English | EPUB | 2014 | 305 Pages | ISBN : 1461486866 | 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 called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications.

Posted by **step778** at June 6, 2018

2006 | pages: 350 | ISBN: 1584885440 | PDF | 3,7 mb

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

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