Estimating the transition probabilities from censored Markov renewal processes

Michael J. Phelan

Statistics & Probability Letters, 1990, vol. 10, issue 1, 43-47

Abstract: The problem of estimating the transition probabilities for the Markov chain associated to a Markov renewal process is considered. The estimators are to be based on censored observations of the Markov renewal process. For a class of Markov renewal processes whose transition distributions factor, nonparametric estimators are defined. They are shown to be consistent and to converge weakly go Gaussian random variables. The result builds upon those in Gill (1980) for nonparametric estimation in this setting.

Keywords: Markov; renewal; process; Markov; chain; censoring; martingale (search for similar items in EconPapers)
Date: 1990
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0167-7152(90)90110-S
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:10:y:1990:i:1:p:43-47

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().