Optimality of estimators for misspecified semi-Markov models
| dc.creator | Müller, Ursula U. | |
| dc.creator | Schick, Anton | |
| dc.creator | Wefelmeyer, Wolfgang | |
| dc.date | 2007-12-20 | |
| dc.date.accessioned | 2026-07-07T08:50:38Z | |
| dc.date.available | 2026-07-07T08:50:38Z | |
| dc.description | Suppose we observe a geometrically ergodic semi-Markov process and have a parametric model for the transition distribution of the embedded Markov chain, for the conditional distribution of the inter-arrival times, or for both. The first two models for the process are semiparametric, and the parameters can be estimated by conditional maximum likelihood estimators. The third model for the process is parametric, and the parameter can be estimated by an unconditional maximum likelihood estimator. We determine heuristically the asymptotic distributions of these estimators and show that they are asymptotically efficient. If the parametric models are not correct, the (conditional) maximum likelihood estimators estimate the parameter that maximizes the Kullback--Leibler information. We show that they remain asymptotically efficient in a nonparametric sense. | |
| dc.description | To appear in a Special Volume of Stochastics: An International Journal of Probability and Stochastic Processes (http://www.informaworld.com/openurl?genre=journal%26issn=1744-2508) edited by N.H. Bingham and I.V. Evstigneev which will be reprinted as Volume 57 of the IMS Lecture Notes Monograph Series (http://imstat.org/publications/lecnotes.htm) | |
| dc.identifier | https://arxiv.org/abs/0712.3451 | |
| dc.identifier | http://arxiv.org/abs/0712.3451 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/144664 | |
| dc.subject | Statistics Theory | |
| dc.subject | 62M09 (Primary) 62F12, 62G20 (Secondary) | |
| dc.title | Optimality of estimators for misspecified semi-Markov models | |
| dc.type | text |