Davison, A.C. and Ramesh, N.I. ORCID: 0000-0001-6373-2557 (1996) Some models for discretized series of events. Journal of the American Statistical Association, 91 (434). pp. 601-609. ISSN 0162-1459 (Print), 1537-274X (Online) (doi:https://doi.org/10.1080/01621459.1996.10476929)

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Abstract

A discretized series of events is a binary time series that indicates whether or not events of a point process in the line occur in successive intervals. Such data are common in environmental applications. We describe a class of models for them, based on an unobserved continuous-time discrete-state Markov process, which determines the rate of a doubly stochastic Poisson process, from which the binary time series is constructed by discretization. We discuss likelihood inference for these processes and their second-order properties and extend them to multiple series. An application involves modeling the times of exposures to air pollution at a number of receptors in Western Europe.

Item Type:	Article
Uncontrolled Keywords:	discretized series of events, models
Subjects:	Q Science > QA Mathematics
Pre-2014 Departments:	School of Computing & Mathematical Sciences School of Computing & Mathematical Sciences > Department of Mathematical Sciences School of Computing & Mathematical Sciences > Statistics & Operational Research Group
Related URLs:	Publisher
Last Modified:	27 Oct 2020 14:50
URI:	http://gala.gre.ac.uk/id/eprint/71

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