Posted by **Underaglassmoon** at Dec. 23, 2015

Springer | Statistical Physics & Dynamical Systems | January 20, 2016 | ISBN-10: 3319248758 | 195 pages | pdf | 5.6 mb

Authors: Banisch, Sven

Self-contained presentation and introductory level

Useful as advanced text and as self-study guide

Posted by **leonardo78** at Jan. 15, 2016

Publisher: Chapman and Hall/CRC | 2011 | ISBN: 1420079417 | 619 pages | PDF | 15,1 MB

Since their popularization in the 1990s, Markov chain Monte Carlo (MCMC) methods have revolutionized statistical computing and have had an especially profound impact on the practice of Bayesian statistics. Furthermore, MCMC methods have enabled the development and use of intricate models in an astonishing array of disciplines as diverse as fisheries science and economics.

Posted by **fdts** at Oct. 29, 2014

by Faming Liang, Chuanhai Liu, Raymond Carroll

English | 2010 | ISBN: 0470748265 | 378 pages | PDF | 5.3 MB

Posted by **enmoys** at July 20, 2014

2014 | 135 Pages | ISBN: 4431545166 | PDF | 4 MB

Posted by **bookwyrm** at May 4, 2014

2014 | 135 Pages | ISBN: 4431545166 | PDF | 4 MB

Posted by **interes** at May 3, 2014

English | 2004 | ISBN: 9812389350 | 380 pages | PDF | 14,7 MB

This book teaches modern Markov chain Monte Carlo (MC) simulation techniques step by step. The material should be accessible to advanced undergraduate students and is suitable for a course.

Posted by **interes** at May 3, 2014

English | 2006 | ISBN: 9812564276 | 240 pages | PDF | 3,5 MB

Markov Chain Monte Carlo (MCMC) originated in statistical physics, but has spilled over into various application areas, leading to a corresponding variety of techniques and methods. That variety stimulates new ideas and developments from many different places, and there is much to be gained from cross-fertilization.

Posted by **advisors** at Dec. 26, 2013

2014 | 135 Pages | ISBN: 4431545166 | PDF | 4 MB

Posted by **tika12** at Nov. 8, 2007

Chapman & Hall/CRC; 1 edition (December 1, 1995) | ISBN:0412055511 | 512 pages | Djvu | 4,4 Mb

Posted by **libr** at Sept. 25, 2014

English | 2012 | ISBN-10: 1461437180 | PDF | 309 pages | 3,5 MB

Algebraic statistics is a rapidly developing field, where ideas from statistics and algebra meet and stimulate new research directions. One of the origins of algebraic statistics is the work by Diaconis and Sturmfels in 1998 on the use of GrÃ¶bner bases for constructing a connected Markov chain for performing conditional tests of a discrete exponential family.