ITERATIVE SIMULATION METHODS

被引：12

作者：

RIPLEY, BD ^{[1
]}

KIRKLAND, MD ^{[1
]}

机构：

[1] UNIV STRATHCLYDE,DEPT STAT,GLASGOW G1 1XH,SCOTLAND

来源：

JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS | 1990年 / 31卷 / 01期

关键词：

Gibbs sampler; iterative simulation; Markov random field; Metropolis' method; rates of convergence;

D O I：

10.1016/0377-0427(90)90347-3

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

The standard methods of generating sample from univariate distributions often become hopelessly inefficient when applied to realizations of stochastic processes. Iterative methods are not widely known amongst statisticians, but some are standard practice in statistical physics and chemistry. The methods are surveyed and compared, with particular reference to their convergence properties. © 1990.

引用

页码：165 / 172

页数：8

共 20 条

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