Accession Number : ADA180541

Title :   Conditions Under Which A Markov Chain Converges to Its Steady-State in Finite Time.

Descriptive Note : Technical rept.,

Corporate Author : STANFORD UNIV CA DEPT OF OPERATIONS RESEARCH

Personal Author(s) : Glynn,Peter W. ; Iglehart,Donald L.

Report Date : APR 1987

Pagination or Media Count : 10

Abstract : Analysis of the initial transient problem of Monte Carlo steady state simulation motivates the following question for Markov chains: when does there exist a deterministic T such that P(x(T) = y-bar-(0) = x) = pi(y), where pi is the stationary distribution of X? We show that this can essentially never happen for a continuous time Markov chain; in discrete-time, such processes are basically i.i.d. Keywords: Initial transient; Markov chains.

Descriptors :   *CONVERGENCE, *MARKOV PROCESSES, TIME, TRANSIENTS, STEADY STATE

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE