Mean Field Simulation for Monte Carlo Integration

Pierre Del Moral

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Hardback

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English

CRC Press Inc
20 May 2013

Probability & statistics

Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability

In the last three decades, there has been a dramatic increase in the use of interacting particle methods as a powerful tool in real-world applications of Monte Carlo simulation in computational physics, population biology, computer sciences, and statistical machine learning. Ideally suited to parallel and distributed computation, these advanced particle algorithms include nonlinear interacting jump diffusions; quantum, diffusion, and resampled Monte Carlo methods; Feynman-Kac particle models; genetic and evolutionary algorithms; sequential Monte Carlo methods; adaptive and interacting Markov chain Monte Carlo models; bootstrapping methods; ensemble Kalman filters; and interacting particle filters.

Mean Field Simulation for Monte Carlo Integration presents the first comprehensive and modern mathematical treatment of mean field particle simulation models and interdisciplinary research topics, including interacting jumps and McKean-Vlasov processes, sequential Monte Carlo methodologies, genetic particle algorithms, genealogical tree-based algorithms, and quantum and diffusion Monte Carlo methods.

Along with covering refined convergence analysis on nonlinear Markov chain models, the author discusses applications related to parameter estimation in hidden Markov chain models, stochastic optimization, nonlinear filtering and multiple target tracking, stochastic optimization, calibration and uncertainty propagations in numerical codes, rare event simulation, financial mathematics, and free energy and quasi-invariant measures arising in computational physics and population biology.

This book shows how mean field particle simulation has revolutionized the field of Monte Carlo integration and stochastic algorithms. It will help theoretical probability researchers, applied statisticians, biologists, statistical physicists, and computer scientists work better across their own disciplinary boundaries.

By: Pierre Del Moral
Imprint: CRC Press Inc
Country of Publication: United States
Volume: 126
Dimensions: Height: 234mm, Width: 156mm, Spine: 33mm
Weight: 997g
ISBN: 9781466504059
ISBN 10: 1466504056
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Pages: 626
Publication Date: 20 May 2013
Audience: College/higher education , General/trade , Primary , ELT Advanced
Format: Hardback
Publisher's Status: Active

Monte Carlo and Mean Field Models. Theory and Applications. Feynman-Kac Models: Discrete Time Feynman-Kac Models. Four Equivalent Particle Interpretations. Continuous Time Feynman-Kac Models. Nonlinear Evolutions of Intensity Measures. Application Domains: Particle Absorption Models. Signal Processing and Control Systems. Theoretical Aspects: Mean Field Feynman-Kac Models. A General Class of Mean Field Models. Empirical Processes. Feynman-Kac Semigroups. Intensity Measure Semigroups. Particle Density Profiles. Genealogical Tree Models. Particle Normalizing Constants. Backward Particle Markov Models. Bibliography. Index.

Pierre Del Moral is a professor in the School of Mathematics and Statistics at the University of New South Wales in Sydney, Australia.

Reviews for Mean Field Simulation for Monte Carlo Integration

...I found this to be an enjoyable read. Many illustrative examples reveal intriguing paradoxes in statistical theories, some of them are well-known and complemented with a broad informative discussion and others are less obvious. -Journal of the American Statistical Association

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Mean Field Simulation for Monte Carlo Integration

Pierre Del Moral

$305

Hardback

Reviews for Mean Field Simulation for Monte Carlo Integration

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