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Smoothed nonparametric estimation in window censored semi-Markov processes
- Source :
-
Journal of Statistical Planning & Inference . May2005, Vol. 131 Issue 2, p209-229. 21p. - Publication Year :
- 2005
-
Abstract
- Consider a process that jumps among a finite set of states, with random times spent in between. In semi-Markov processes transitions follow a Markov chain and the sojourn distributions depend only on the connecting states. Suppose that the process started far in the past, achieving stationary. We consider non-parametric estimation by modelling the log-hazard of the sojourn times through linear splines; and we obtain maximum penalized likelihood estimators when data consist of several i.i.d. windows. We prove consistency using Grenander''s method of sieves. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 03783758
- Volume :
- 131
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Journal of Statistical Planning & Inference
- Publication Type :
- Academic Journal
- Accession number :
- 16511820
- Full Text :
- https://doi.org/10.1016/j.jspi.2004.03.003