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Statistical analysis on Markov-modulated Poisson processes

Statistical analysis on Markov-modulated Poisson processes

Ramesh, N. I. (1995) Statistical analysis on Markov-modulated Poisson processes. Environmetrics, 6 (2). pp. 165-179. ISSN 1180-4009 (Print), 1099-095X (Online) (doi:https://doi.org/10.1002/env.3170060207)

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Abstract

A class of doubly stochastic Poisson processes, which is termed a Markov-modulated Poisson process, is studied. The maximum likelihood method is used to make inferences about the Markov-modulated Poisson process. Expressions are derived for the likelihood function and for second-order properties of both counts and intervals. A simple two-state model is applied to a set of exposure data and to simulated data. Bivariate generalization of this process is also studied.

Item Type: Article
Uncontrolled Keywords: Conditional intensity; Doubly stochastic Poisson process; maximum likelihood; Point process; Spectral density
Subjects: Q Science > QA Mathematics
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Department of Mathematical Sciences
Last Modified: 17 Nov 2017 17:01
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/18021

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