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March, 1984 Nonparametric Inference for a Class of Semi-Markov Processes with Censored Observations
Joseph G. Voelkel, John Crowley
Ann. Statist. 12(1): 142-160 (March, 1984). DOI: 10.1214/aos/1176346398

Abstract

A class of semi-Markov models, those which have proportional hazards and which are forward-going (if state $j$ can be reached from $i$, then $i$ cannot be reached from $j$), are shown to fit into the multiplicative intensity model of counting processes after suitable random time changes. Standard large-sample results for counting processes following this multiplicative model can therefore be used to make inferences on the above class of semi-Markov models, including the case where observations may be censored. Large-sample results for a four-state model used in clinical trials are presented.

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Joseph G. Voelkel. John Crowley. "Nonparametric Inference for a Class of Semi-Markov Processes with Censored Observations." Ann. Statist. 12 (1) 142 - 160, March, 1984. https://doi.org/10.1214/aos/1176346398

Information

Published: March, 1984
First available in Project Euclid: 12 April 2007

zbMATH: 0552.62020
MathSciNet: MR733505
Digital Object Identifier: 10.1214/aos/1176346398

Subjects:
Primary: 62G05
Secondary: 60K15

Rights: Copyright © 1984 Institute of Mathematical Statistics

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Vol.12 • No. 1 • March, 1984
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