Maximum spacing estimation for continuous time Markov chains and semi-Markov processes
type: Item
instance of: scholarly article
title: Maximum spacing estimation for continuous time Markov chains and semi-Markov processes
zbMATH Open document ID: 1473.62293
author: K. Kuljus
author: B. Ranneby
published in: Statistical Inference for Stochastic Processes
publication date: 2021-08-17T00:00:00Z
review text: Maximum spacing (MSP) method was introduced for parameter estimation by \textit{B. Ranneby} [Scand. J. Stat. 11, 93--112 (1984; Zbl 0545.62006)] and independently by \textit{R. C. H. Cheng} and \textit{N. A. K. Amin} [J. R. Stat. Soc., Ser. B 45, 394--403 (1983; Zbl 0528.62017)]. The authors extend the method to continous time Markov chains and semi-Markov processes and consistency of the MSP estimator is proved. The authors present simulated examples to study the performance of the MSP estimator as compared to the maximum likelihood (ML) estimator and observe that the asymptotic behaviour of the MSP estimator and the ML estimator are equivalent.
Mathematics Subject Classification ID: 62M05
Mathematics Subject Classification ID: 62M09
Mathematics Subject Classification ID: 60J27
zbMATH DE Number: 7382649
zbMATH Keywords: maximum spacing method
zbMATH Keywords: parameter estimation
zbMATH Keywords: continuous time Markov chain
zbMATH Keywords: semi-Markov process
reviewed by: B. L. S. Prakasa Rao
MaRDI profile type: Publication
full work available at URL: s11203-021-09238-4
OpenAlex ID: W3132092300
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DOI: 10.1007/S11203-021-09238-4
description: scientific article; zbMATH DE number 7382649