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):

Report Date:

1987-04-01

Pagination or Media Count:

10.0

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 PxT y-bar-0 x piy, 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.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE