Iterated random functions

被引：420

作者：

Diaconis, P ^{[1
]}

Freedman, D

机构：

[1] Stanford Univ, Dept Math & Stat, Stanford, CA 94305 USA

[2] Univ Calif Berkeley, Dept Stat, Berkeley, CA 94720 USA

来源：

SIAM REVIEW | 1999年 / 41卷 / 01期

关键词：

Markov chains; products of random matrices; iterated function systems; coupling from the past;

D O I：

10.1137/S0036144598338446

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Iterated random functions are used to draw pictures or simulate large Ising models, among other applications. They offer a method for studying the steady state distribution of a Markov chain, and give useful bounds on rates of convergence in a variety of examples. The present paper surveys the field and presents some new examples. There is a simple unifying idea: the iterates of random Lipschitz functions converge if the functions are contracting on the average.

引用

页码：45 / 76

页数：32

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