Finite-time implications of relaxation times for stochastically monotone processes期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

Finite-time implications of relaxation times for stochastically monotone processes

Authors:	David J. Aldous

Affiliation:	(1) Department of Statistics, University of California, 94720 Berkeley, CA, USA;(2) Present address: INSA Toulouse, Tou7louse, France

Abstract:	Summary For a continuous-time finite state Markov process with stationary distribution , it is well-known thatPⁱ(X^t=j)-^j isO(e^-t) ast, for a certain . For a stochastically monotone process for which the reversed process is also stochastically monotone, one can obtain bounds valid for allt. Precisely, $sumlimits_i {pi _j mathop {max \|}limits_j P_i } (X_t leqq j) - pi [0,j]\| leqq 2(lambda t + 2)$ exp(-t). The proof exploits duality for stochastically monotone processes.Research supported by National Science Foundation Grant MCS 84-03239

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