Parameter estimation for a two-state semi-Markov model of a univariate point process.

Using the convenient second-order interval properties of a two-state semi-Markov model for a univariate point process, an automated technique for the estimation of the parameters in the model was researched and discussed. The power spectral density of intervals was estimated by the periodogram and a Kolmogorov-Smirnov test of fit was conducted. The asymtotic exponential distribution and independence of the periodogram points were used to calculate an approximate likelihood function. A system of equations was then formed to find the maximum likelihood estimates of the parameters. Since closed-form solutions for the estimates could not be found, an iterative method to stabilize initial guesses of the parameter values was attempted with only limited success. Results on using Kolmogorov-Smirnov type statistics and the spectrum of intervals to test the fit of stochastic process models to data have also been obtained.

Department dc:contributor.department

Operations Research and Administrative Sciences

Grantor dc:publisher

Monterey, California. Naval Postgraduate School

Year dc:date.issued

1974

Author dc:creator

• Hornback, James Leroy

Advisor dc:contributor.advisor

• Lewis, Peter A.W.

Statement dc:rights

• This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.

Language dc:language.iso

en_US

Handle dc:identifier.uri

https://hdl.handle.net/10945/17163

OAI identifier oai:identifier

oai:calhoun.nps.edu:10945/17163