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M值随机变量序列与Markov链的比较及其强偏差定理
The comparison between M - valued random variables and markow Chain and a strong deviation theorem
【摘要】 设{Sn,n≥O}是在S={1,2,…,m}中取值的随机变量序列,i,j S,Sn(i,j,w)是序偶列{X0,Xi},(X1,X2),…,(Xn-1,Xn)中序偶(i,j)出现的次数,本文利用似然比[1]这一概念,作为{Xn,n≥0}与Markov链偏差的一种度量,并通过限制似然比,给出样本空间的一个子集D(C),在此子集上得到一类与Markov链有关的强偏差定理。
【Abstract】 Let { Xn, n0} be a sequence of random variables taking values in S{ 1, 2, m} i, j S, Sn(i, j; w) he the number of occurrence of ordered couple (i, j)of states in the sequence of ordered couples(X0,X1 ), (X1, X2), (Xn-1 , Xn). In this paper, the concept likelihood ratio is used as the measure of deviationbetween { Xn, n 1 } and Markow Chain, and a subset of D(C) of sampling space is given. A class of strongdeviation theorem relative to Markov Chain are obtained on the set.
- 【文献出处】 华东冶金学院学报 ,JOURNAL OF EAST CHINA UNIVERSITY OF METALLARGY , 编辑部邮箱 ,2000年01期
- 【分类号】O211.6
- 【被引频次】2
- 【下载频次】13