Semi-parametric estimation for a semi-Markov process with left-truncated and right-censored observations

A semi-Markov process is characterized by the transition probabilities between the states and the distribution functions of the duration times between the occurrence of consecutive states. We present estimators of the transition probabilities and the cumulative hazard functions of the duration times...

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Veröffentlicht in:	Statistics & probability letters 2006-05, Vol.76 (9), p.952-958
1. Verfasser:	Pons, Odile
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science Exact sciences and technology Hazard function Left-truncation Mathematics Nonparametric inference Probability and statistics Probability theory and stochastic processes Right-censoring Sciences and techniques of general use Semi-Markov process Semi-Markov process Transition probability Hazard function Right-censoring Left-truncation Special processes (renewal theory, markov renewal processes, semi-markov processes, statistical mechanics type models, applications) Statistics Transition probability
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Beschreibung
Zusammenfassung:	A semi-Markov process is characterized by the transition probabilities between the states and the distribution functions of the duration times between the occurrence of consecutive states. We present estimators of the transition probabilities and the cumulative hazard functions of the duration times when n i.i.d. right-censored sample paths of a process are observed, with left-truncated and right-censored sojourn times.
ISSN:	0167-7152 1879-2103
DOI:	10.1016/j.spl.2005.10.030