Affiliation:
1. McGill University, Montreal, Canada
2. Hong Kong University of Science and Technology, Kowloon, Hong Kong
Abstract
We consider the problem of the exact simulation of random variables
Z
that satisfy the distributional identity
Z
=
L
VY
+ (1-
V
)
Z
, where
V
∈ [0,1] and
Y
are independent, and =
L
denotes equality in distribution. Equivalently,
Z
is the limit of a Markov chain driven by that map. We give an algorithm that can be automated under the condition that we have a source capable of generating independent copies of
Y
, and that
V
has a density that can be evaluated in a black-box format. The method uses a doubling trick for inducing coalescence in coupling from the past. Applications include exact samplers for many Dirichlet means, some two-parameter Poisson--Dirichlet means, and a host of other distributions related to occupation times of Bessel bridges that can be described by stochastic fixed point equations.
Funder
Hungkuang University
Research Grants Council, University Grants Committee, Hong Kong
Natural Sciences and Engineering Research Council of Canada
Publisher
Association for Computing Machinery (ACM)
Subject
Computer Science Applications,Modeling and Simulation
Cited by
10 articles.
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