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How to Combine Fast Heuristic Markov Chain Monte Carlo with
 

Summary: How to Combine Fast Heuristic
Markov Chain Monte Carlo with
Slow Exact Sampling
(with Antar Bandyopadhyay).
See www.stat.berkeley.edu/users/aldous for slides
and preprint.
MCMC is huge field, many different aspects of
theory and of applications. We will ``zoom in''
to describe a very special question -- one point
on the boundary between rigour and heuristics.
1

MCMC
Target prob. dist. on space S.
Seek to sample from .
Design a Markov transition matrix P (x; y) to
have as its stationary distribution. Use the
Markov chain X t to get samples; naively, take
large t 0 and regard
X t 0

  

Source: Aldous, David J. - Department of Statistics, University of California at Berkeley

 

Collections: Mathematics