Applications of Semi-Regenerative Theory to Computations of Stationary Distributions of Markov Chains.

Abstract

Arguments from Regenerative Theory have been used by a number of authors to solve equilibrium equations in queueing problems. In this paper we use Semi-Regenerative Theory, which is a generalization and sophistication of Regenerative Theroy. We believe that this is the first paper which uses Semi-Regenerative Theory for developing numerical (nonsimulation) algorithms to find the steady-state distribution of a Markov chain. The algorithm obtained is a modifications of the Gauss-Jordan method, in which all the elements used in computations are always nonnegative, which makes the algorithm numerically stable.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1982
Accession Number
ADA131640

Entities

People

  • Michael I. Taksar
  • W. K. Grassmann

Organizations

  • Stanford University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Band Structures
  • Complex Systems
  • Computations
  • Equations
  • Equations Of State
  • Markov Chains
  • Markov Processes
  • Military Research
  • Probability
  • Random Variables
  • Simultaneous Equations
  • Social Sciences
  • Stationary
  • Steady State
  • United States
  • Universities

Fields of Study

  • Mathematics

Readers

  • Calculus or Mathematical Analysis
  • Statistical inference.