The Annals of Statistics
- Ann. Statist.
- Volume 12, Number 1 (1984), 142-160.
Nonparametric Inference for a Class of Semi-Markov Processes with Censored Observations
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.
Ann. Statist., Volume 12, Number 1 (1984), 142-160.
First available in Project Euclid: 12 April 2007
Permanent link to this document
Digital Object Identifier
Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Primary: 62G05: Estimation
Secondary: 60K15: Markov renewal processes, semi-Markov processes
Voelkel, Joseph G.; Crowley, John. Nonparametric Inference for a Class of Semi-Markov Processes with Censored Observations. Ann. Statist. 12 (1984), no. 1, 142--160. doi:10.1214/aos/1176346398. https://projecteuclid.org/euclid.aos/1176346398