Some Asymptotic Formulas for Markov Chains with Applications to Simulation.
Abstract
Various techniques have been proposed for determination of confidence intervals associated with steady-state quantities in simulation. Evaluation of such procedures requires comparison of their performance on stochastic systems with known characteristics. In this paper, the authors therefore derive computable formulas for the initial bias, variance and spectrum of the sample mean in finite state Markov chains, and discuss their relevance to the steady-state simulation problem.
Document Details
- Document Type
- Technical Report
- Publication Date
- Mar 01, 1983
- Accession Number
- ADA128074
Entities
People
- Peter W. Glynn
Organizations
- University of Wisconsin–Madison