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Proportional intensities and strong ergodicity for Markov processes

Published online by Cambridge University Press:  14 July 2016

Mark Scott*
Affiliation:
Mayo Clinic
Dean L. Isaacson*
Affiliation:
Iowa State University
*
Postal address: Department of Medical Statistics and Epidemiology, Mayo Clinic, Rochester, MN 55901, U.S.A.
∗∗ Postal address: Departments of Mathematics and Statistics, Iowa State University, Ames, IA 50011, U.S.A.

Abstract

By assuming the proportionality of the intensity functions at each time point for a continuous-time non-homogeneous Markov process, strong ergodicity for the process is determined through strong ergodicity of a related discrete-time Markov process. For processes having proportional intensities, strong ergodicity implies having the limiting matrix L satisfy L · P(s, t) = L, where P(s, t) is the matrix of transition functions.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1983 

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