**Fields Institute Communications**

Volume: 26;
2000;
228 pp;
Hardcover

MSC: Primary 65; 60;
Secondary 81; 82

Print ISBN: 978-0-8218-1992-0

Product Code: FIC/26

List Price: $84.00

Individual Member Price: $67.20

**Electronic ISBN: 978-1-4704-3050-4
Product Code: FIC/26.E**

List Price: $84.00

Individual Member Price: $67.20

# Monte Carlo Methods

Share this page *Edited by *
*Neal Madras*

A co-publication of the AMS and Fields Institute

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.

Titles in this series are co-published with the Fields Institute for Research in Mathematical Sciences (Toronto, Ontario, Canada).

#### Table of Contents

# Table of Contents

## Monte Carlo Methods

- Cover Cover11
- Title page iii4
- Contents v6
- Preface vii8
- Introduction to multicanonical Monte Carlo simulations 110
- MCMC in 𝐼×𝐽×𝐾 contingency tables 2534
- Extension of Fill’s perfect rejection sampling algorithm to general chains (Extended abstract) 3746
- Taming zero modes in lattice QCD with the polynomial hybrid Monte Carlo algorithm 5362
- Monte Carlo algorithms and non-local actions 6574
- Towards a more general Propp-Wilson algorithm: Multistage backward coupling 8594
- On non-reversible Markov chains 95104
- Exact sampling for Bayesian inference: Unbounded state spaces 111120
- Recent progress on computable bounds and the simple slice sampler 123132
- MCMC methods in statistical mechanics: Avoiding quasi-ergodic problems 131140
- Layered multishift coupling for use in perfect sampling algorithms (with a primer on CFTP) 143152
- Introduction to semi Markov chain Monte Carlo 181190
- Accelerated simulation of ATM switching fabrics 193202
- Some stratagems for the estimation of time series using the Metropolis method 207216
- Monte Carlo study of adsorption of interacting self-avoiding walks 221230
- Back Cover Back Cover1238

#### Readership

Graduate students and researchers working in Monte Carlo methods in probability, statistics, theoretical physics, or computer science.