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

Loading...
Thumbnail Image
Authors
Hornback, James Leroy
Subjects
univariate point process
two-state semi-Markov model
parameter estimation
multiprogrammed computers
page exceptions
page exception processes
power spectral density
periodogram
page reference patterns
demand paged computer system
Advisors
Lewis, Peter A.W.
Date of Issue
1974-03
Date
March 1974
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
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.
Type
Thesis
Description
Series/Report No
Department
Operations Research and Administrative Sciences
Organization
Naval Postgraduate School (U.S.)
Identifiers
NPS Report Number
Sponsors
Funder
Format
Citation
Distribution Statement
Approved for public release; distribution is unlimited.
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.
Collections