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Statistical inference for point-process models of rainfall
Published online by Cambridge University Press: 01 July 2016
Extract
In this paper we develop maximum likelihood procedures for parameter estimation and hypothesis testing for three classes of point processes that have been used to model rainfall occurrences; renewal processes, Neyman-Scott processes, and RCM processes (which are members of the family of Cox processes). The statistical inference procedures developed in this paper are based on the intensity process
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- Applied Probability in Biology and Engineering. An ORSA/TIMS Special Interest Meeting
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- Copyright © Applied Probability Trust 1984
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