Accession Number:

AD0725565

Title:

Statistical Inference for Markov Renewal Processes.

Descriptive Note:

Technical rept.,

Corporate Author:

SOUTHERN METHODIST UNIV DALLAS TEX DEPT OF STATISTICS

Personal Author(s):

Report Date:

1971-04-15

Pagination or Media Count:

68.0

Abstract:

A Markov Renewal Process is one which records at each time t the number of times a system visits each of a finite number m of states up to time t. The system moves from state to state according to a Markov chain, and the time required for each move sojourn time is a random variable whose distribution function may depend on the two states between which the move is made. In this paper the author develops a test for the goodness of fit of a hypothetical transition probability matrix for a Markov Renewal Process. The author illustrates this procedure numerically by applying it to a realization of a two-state Markov Renewal Process artificially generated on a computer. In addition, the author considers some Bayesian analysis for Markov Renewal Processes by assuming a matrix beta prior distribution for the transition probability matrix. The report also discusses a special case of this topic and gives an illustration for a two-state Markov Renewal Process. In the final chapter a summary of results is given and some possible future research proglems are indicated. Author

Subject Categories:

  • Statistics and Probability
  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE