Exact sampling from anti-monotone systems

نویسندگان

  • Olle Häggström
  • Karin Nelander
چکیده

A new approach to Markov chain Monte Carlo simulation was recently proposed by Propp and Wilson. This approach, unlike traditional ones, yields samples which have exactly the desired distribution. The Proppp Wilson algorithm requires this distribution to have a certain structure called monotonicity. In this paper, it is shown how the algorithm can be extended to the case where monotonicity is replaced by anti-monotonicity. As illustrating examples, simulations of the hard-core model and the random-cluster model are presented.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Exact Sampling from a Continuous State Space

Propp & Wilson (1996) described a protocol, called coupling from the past, for exact sampling from a target distribution using a coupled Markov chain Monte Carlo algorithm. In this paper we extend coupling from the past to various MCMC samplers on a continuous state space; rather than following the monotone sampling device of Propp & Wilson, our approach uses methods related to gamma-coupling a...

متن کامل

An Extension of Fill's Exact Sampling Algorithm to Non-monotone Chains*

We provide an extension of Fill's (1998) exact sampler algorithm. Our algorithm is similar to Fill's, however it makes no assumptions regarding stochastic monotonicity, discreteness of the state space, the existence of densities, etc. We illustrate our algorithm on a simple example.

متن کامل

A Guide to Exact Simulation

Markov Chain Monte Carlo (MCMC) methods are used to sample from complicated multivariate distributions with normalizing constants that may not be computable and from which direct sampling is not feasible. A fundamental problem is to determine convergence of the chains. Propp & Wilson (1996) devised a Markov chain algorithm called Coupling From The Past (CFTP) that solves this problem, as it pro...

متن کامل

Polynomial time perfect sampling algorithm for two-rowed contingency tables

This paper proposes a polynomial time perfect (exact) sampling algorithm for 2 × n contingency tables. The algorithm is based on monotone coupling from the past (monotone CFTP) algorithm. The expected running time is bounded by O(n lnN) where n is the number of columns and N is the total sum of all entries.

متن کامل

MATHEMATICAL ENGINEERING TECHNICAL REPORTS Polynomial Time Perfect Sampling Algorithm for Two-rowed Contingency Tables

This paper proposes a polynomial time perfect (exact) sampling algorithm for 2×n contingency tables. Our algorithm is a Las Vegas type randomized algorithm and the expected running time is bounded by O(n ln N) where n is the number of columns and N is the total sum of whole entries in a table. The algorithm is based on monotone coupling from the past (monotone CFTP) algorithm and new Markov cha...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1997