By Topic

The rejection Gibbs coupler: A perfect sampling algorithm and its application to truncated multivariate Gaussian distributions

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Yufei Huang ; Dept. of Electr. & Comput. Eng., State Univ. of New York, Stony Brook, NY, USA ; T. Ghirmai ; P. M. Djuric

A new Markov chain based algorithm for drawing samples from a desired distribution has been proposed. This algorithm, also known as the perfect sampling algorithm, can determine exactly when a Markov chain enters the equilibrium, and hence can output exact samples. We introduce a perfect sampling algorithm called the rejection Gibbs coupler for perfect sampling from bounded multivariate distributions. We demonstrate an application of the rejection coupler for generation of samples from truncated multivariate Gaussian distributions

Published in:

Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on

Date of Conference: