A fixed point approach to the classification of Markov chains with a tree structure

被引:4
作者
He, QM [1 ]
机构
[1] Dalhousie Univ, Dept Ind Engn, Halifax, NS B3J 2X4, Canada
关键词
Markov chains; ergodicity; tree structure; matrix analytic methods; fixed point theory; degree theory;
D O I
10.1081/STM-120018140
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 [统计学]; 070103 [概率论与数理统计]; 0714 [统计学];
摘要
In this paper, we study the classification problem of discrete time and continuous time Markov processes with a tree structure. We first show some useful properties associated with the fixed points of a nondecreasing mapping. Mainly we find the conditions for a fixed point to be the minimal fixed point by using fixed point theory and degree theory. We then use these results to identify conditions for Markov chains of M/G/1 type or G1/M/1 type with a tree structure to be positive recurrent, null recurrent. or transient. The results are generalized to Markov chains of matrix M/G/1 type with a tree structure. For all these cases, a relationship between a certain fixed point, the matrix of partial differentiation (Jacobian) associated with the fixed point, and the classification of the Markov chain with a tree structure is established, More specifically, we show that the Perron-Frobenius eigenvalue of the matrix of partial differentiation associated with a certain fixed point provides information for a complete classification of the Markov chains of interest.
引用
收藏
页码:75 / 111
页数:37
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