Monte Carlo Methods ( Fields Institute Communications )

Publication series :Fields Institute Communications

Author: Neal Madras  

Publisher: American Mathematical Society‎

Publication year: 2000

E-ISBN: 9781470430504

P-ISBN(Hardback):  9780821819920

Subject: O1 Mathematics

Keyword: 暂无分类

Language: ENG

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Monte Carlo Methods

Description

This volume contains the proceedings of the Workshop on Monte Carlo Methods held at The Fields Institute for Research in Mathematical Sciences (Toronto, 1998). The workshop brought together researchers in physics, statistics, and probability. The papers in this volume—of the invited speakers and contributors to the poster session—represent the interdisciplinary emphasis of the conference. Monte Carlo methods have been used intensively in many branches of scientific inquiry. Markov chain methods have been at the forefront of much of this work, serving as the basis of many numerical studies in statistical physics and related areas since the Metropolis algorithm was introduced in 1953. Statisticians and theoretical computer scientists have used these methods in recent years, working on different fundamental research questions, yet using similar Monte Carlo methodology. This volume focuses on Monte Carlo methods that appear to have wide applicability and emphasizes new methods, practical applications and theoretical analysis. It will be of interest to researchers and graduate students who study and/or use Monte Carlo methods in areas of probability, statistics, theoretical physics, or computer science.

Chapter

Title page

Contents

Preface

Introduction to multicanonical Monte Carlo simulations

MCMC in 𝐼×𝐽×𝐾 contingency tables

Extension of Fill’s perfect rejection sampling algorithm to general chains (Extended abstract)

Taming zero modes in lattice QCD with the polynomial hybrid Monte Carlo algorithm

Monte Carlo algorithms and non-local actions

Towards a more general Propp-Wilson algorithm: Multistage backward coupling

On non-reversible Markov chains

Exact sampling for Bayesian inference: Unbounded state spaces

Recent progress on computable bounds and the simple slice sampler

MCMC methods in statistical mechanics: Avoiding quasi-ergodic problems

Layered multishift coupling for use in perfect sampling algorithms (with a primer on CFTP)

Introduction to semi Markov chain Monte Carlo

Accelerated simulation of ATM switching fabrics

Some stratagems for the estimation of time series using the Metropolis method

Monte Carlo study of adsorption of interacting self-avoiding walks

Back Cover

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