By Steve Brooks,Andrew Gelman,Galin Jones,Xiao-Li Meng
Since their popularization within the Nineties, Markov chain Monte Carlo (MCMC) tools have revolutionized statistical computing and feature had a particularly profound influence at the perform of Bayesian records. in addition, MCMC tools have enabled the improvement and use of problematic types in an astounding array of disciplines as different as fisheries technology and economics. The wide-ranging functional value of MCMC has sparked an expansive and deep research into primary Markov chain theory.
The Handbook of Markov Chain Monte Carlo presents a reference for the wide viewers of builders and clients of MCMC method attracted to maintaining with state-of-the-art thought and functions. the 1st 1/2 the booklet covers MCMC foundations, technique, and algorithms. the second one part considers using MCMC in numerous useful functions together with in academic learn, astrophysics, mind imaging, ecology, and sociology.
The in-depth introductory portion of the booklet permits graduate scholars and training scientists new to MCMC to develop into completely conversant in the fundamental concept, algorithms, and functions. The booklet provides distinctive examples and case stories of reasonable clinical difficulties proposing the range of tools utilized by the wide-ranging MCMC neighborhood. these conversant in MCMC equipment will locate this publication an invaluable refresher of present thought and up to date developments.
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Additional info for Handbook of Markov Chain Monte Carlo (Chapman & Hall/CRC Handbooks of Modern Statistical Methods)
Handbook of Markov Chain Monte Carlo (Chapman & Hall/CRC Handbooks of Modern Statistical Methods) by Steve Brooks,Andrew Gelman,Galin Jones,Xiao-Li Meng