Handbook of Markov Chain Monte Carlo

1. Auflage 2011
ISBN: 978-1-4200-7941-8
Verlag: Chapman and Hall/CRC

Buch, Englisch, 618 Seiten, Format (B × H): 183 mm x 260 mm, Gewicht: 1344 g

Reihe: Chapman & Hall/CRC Handbooks of Modern Statistical Methods

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. The wide-ranging practical importance of MCMC has sparked an expansive and deep investigation into fundamental Markov chain theory.

The Handbook of Markov Chain Monte Carlo provides a reference for the broad audience of developers and users of MCMC methodology interested in keeping up with cutting-edge theory and applications. The first half of the book covers MCMC foundations, methodology, and algorithms. The second half considers the use of MCMC in a variety of practical applications including in educational research, astrophysics, brain imaging, ecology, and sociology.

The in-depth introductory section of the book allows graduate students and practicing scientists new to MCMC to become thoroughly acquainted with the basic theory, algorithms, and applications. The book supplies detailed examples and case studies of realistic scientific problems presenting the diversity of methods used by the wide-ranging MCMC community. Those familiar with MCMC methods will find this book a useful refresher of current theory and recent developments.

Zielgruppe

Professional and Professional Practice & Development

Autoren/Hrsg.

Brooks, Steve

Gelman, Andrew

Jones, Galin

Meng, Xiao-Li

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Naturwissenschaften Physik Angewandte Physik Statistische Physik, Dynamische Systeme
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

Foundations, Methodology, and Algorithms. Applications.

Über Autor(innen)

Steve Brooks, Andrew Gelman, Galin Jones, Xiao-Li Meng