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Computational and estimation procedures in multidimensional right-shift processes and some applications

Published online by Cambridge University Press:  01 July 2016

Richard J. Kryscio  and
Norman C. Severo
Richard J. Kryscio
Affiliation:
Northern Illinois University
Norman C. Severo
Affiliation:
State University of New York at Buffalo
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Abstract

A right-shift process is a Markov process with multidimensional finite state space on which the infinitesimal transition movement is a shifting of one unit from one coordinate to some other to its right. A multidimensional right-shift process consists of v ≧ 1 concurrent and dependent right-shift processes. In this paper applications of multidimensional right-shift processes to some well-known examples from epidemic theory, queueing theory and the Beetle probblem due to Lucien LeCam are discussed. A transformation which orders the Kolmogorov forward equations into a triangular array is provided and some computational procedures for solving the resulting system of equations are presented. One of these procedures is concerned with the problem of evaluating a given transition probability function rather than obtaining the solution to the complete system of forward equations. This particular procedure is applied to the problem of estimating the parameters of a multidimensional right-shift process which is observed at only a finite number of fixed timepoints.

Keywords

TRANSITION PROBABILITY FUNCTIONSMAXIMUM LIKELIHOOD ESTIMATIONEPIDEMIC MODELSLECAM'S BEETLE PROBLEMQUEUES IN TANDEM

Information

Type
Research Article
Information
Advances in Applied Probability , Volume 7 , Issue 2 , June 1975 , pp. 349 - 382
Copyright
Copyright © Applied Probability Trust 1975 

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