Regenerative Simulation of Harris Recurrent Markov Chains.

Abstract

If the steady-state simulation problem associated with a general discrete-event simulation is well-posed, then the corresponding Markov chain is Harris recurrent. For Harris chains, it is possible to develop a simulation methodology, closely related to the regenerative method, for obtaining confidence intervals associated with estimation of steady-state parameters. The passage-time problem for Harris chains is also studied, and an estimation approach for the steady-state simulation problem is outlined. Finally, it is shown that a certain family of nonlinear storage processes is Harris recurrent--the family provides an example of a Harris chain for which the classical regenerative method is inapplicable. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1982
Accession Number
ADA119251

Entities

People

  • Peter W. Glynn

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Convergence
  • Data Science
  • Distribution Functions
  • Embedding
  • Information Science
  • Markov Chains
  • Markov Processes
  • Probability
  • Random Variables
  • Simulations
  • Stationary Processes
  • Statistical Analysis
  • Steady State
  • Transitions
  • United States
  • Weak Convergence

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Software Verification and Validation.
  • Statistical inference.