Contemporary Mathematics Coupling from the Past: a User's Guide Export

@misc{citeulike:3563803, abstract = {Abstract. The Markov chain Monte Carlo method is a general technique for obtaining samples from a probability distribution. In earlier work, we showed that for many applications one can modify the Markov chain Monte Carlo method so as to remove all bias in the output resulting from the biased choice of an initial state for the chain; we have called this method Coupling From The Past (CFTP). Here we describe this method in a fashion that should make our ideas accessible to researchers from diverse areas. Our expository strategy is to avoid proofs and focus on sample applications. 1.}, author = {Wilson, David}, citeulike-article-id = {3563803}, citeulike-linkout-0 = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.40.365}, keywords = {mcmc, mixing\_time}, posted-at = {2008-11-18 05:16:39}, priority = {2}, title = {Contemporary Mathematics Coupling from the Past: a User\&\#039;s Guide}, url = {http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.40.365} }

TY - ELEC ID - citeulike:3563803 L3 - citeulike-article-id:3563803 N2 - Abstract. The Markov chain Monte Carlo method is a general technique for obtaining samples from a probability distribution. In earlier work, we showed that for many applications one can modify the Markov chain Monte Carlo method so as to remove all bias in the output resulting from the biased choice of an initial state for the chain; we have called this method Coupling From The Past (CFTP). Here we describe this method in a fashion that should make our ideas accessible to researchers from diverse areas. Our expository strategy is to avoid proofs and focus on sample applications. 1. TI - Contemporary Mathematics Coupling from the Past: a User's Guide KW - mcmc KW - mixing_time AU - Wilson, David UR - http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.40.365 ER -