Journal article icon

Journal article

INTERACTING MARKOV CHAIN MONTE CARLO METHODS FOR SOLVING NONLINEAR MEASURE-VALUED EQUATIONS

Abstract:

We present a new class of interacting Markov chain Monte Carlo algorithms for solving numerically discrete-time measure-valued equations. The associated stochastic processes belong to the class of self-interacting Markov chains. In contrast to traditional Markov chains, their time evolutions depend on the occupation measure of their past values. This general methodology allows us to provide a natural way to sample from a sequence of target probability measures of increasing complexity. We dev...

Expand abstract
Publication status:
Published

Actions


Access Document


Publisher copy:
10.1214/09-AAP628

Authors


More by this author
Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Role:
Author
Journal:
ANNALS OF APPLIED PROBABILITY
Volume:
20
Issue:
2
Pages:
593-639
Publication date:
2010-04-05
DOI:
EISSN:
1050-5164
ISSN:
1050-5164
URN:
uuid:7d3765d9-7632-46ac-b527-a346f64a7769
Source identifiers:
172668
Local pid:
pubs:172668

Terms of use


Metrics


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP