Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed Over Bounded Regions
R. Smith. Operations Research, 32 (6):
pp. 1296-1308(1984)
Abstract
We consider the Monte Carlo problem of generating points uniformly distributed within an arbitrary bounded (measurable) region. The class of Markovian methods considered generate points asymptotically uniformly distributed within the region. Computational experience suggests the methods are potentially superior to conventional rejection techniques for large dimensional regions.
Description
Describes how to sample the feasible region of an underdetermined linear problem in a uniform way.
%0 Journal Article
%1 smith1984montecarlo
%A Smith, Robert L.
%D 1984
%I INFORMS
%J Operations Research
%K MCMC inverse_problems
%N 6
%P pp. 1296-1308
%T Efficient Monte Carlo Procedures for Generating Points Uniformly Distributed Over Bounded Regions
%U http://www.jstor.org/stable/170949
%V 32
%X We consider the Monte Carlo problem of generating points uniformly distributed within an arbitrary bounded (measurable) region. The class of Markovian methods considered generate points asymptotically uniformly distributed within the region. Computational experience suggests the methods are potentially superior to conventional rejection techniques for large dimensional regions.