Statistical Engineering Division SeminarUsing Sequential Importance Sampling to Speed up MCMC
Dr. Isabel Beichl Abstract The Monte Carlo Markov Chain Method (MCMC) has been written about extensively and there is an extensive theory developed. But getting answers to problems is still difficult because MCMC can be slow. We present two methods for speeding up MCMC for the monomer-dimer problem based on the method of sequential importance sampling (SIS). Our method computes optimal fugacities. The other computes the mixing rate efficiently. NIST Contact: Dr. Charles Hagwood, (301) 975-2846.
Date created: 5/13/2008 |