Several recent papers have suggested using a product estimator in Monte Carlo Markov chain sampling for estimating the volume of a convex body, the ...

Several recent papers have suggested using a product estimator in Monte Carlo Markov chain sampling for estimating the volume of a convex body, ...

Dec 1, 1994 · In particular, it describes a procedure for determining optimal warm-up intervals and optimal sample sizes to achieve a specified level of ...

In particular, it describes a procedure for determining optimal warm-up intervals and optimal sample sizes to achieve a specified level of statistical accuracy ...

Our estimator refutes the folk theorem that it is hard to estimate with MCMC generated samples from the original Markov chain alone. This might obviate the need.

Bibliographic details on Markov Chain Sampling and the Product Estimator.

Aug 6, 2020 · Our estimator satisfies a central limit theorem and improves on error per CPU cycle, often to a large extent. As a by-product it enables ...

The use of Markov chain Monte Carlo for max- imum likelihood estimation is explained, and its per- formance is compared with maximum pseudo likelihood.

This is an introduction to probability and Bayesian modeling at the undergraduate level. It assumes the student has some background with calculus.

In this work we present a novel estimator applicable to these methods, dubbed Markov chain importance sampling (MCIS), which efficiently makes use of rejected ...