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Double Periodic Non–Homogeneous Poisson Models for Hurricanes Data


Double Periodic Non–Homogeneous Poisson Models for Hurricanes Data

Lu, Yi and Garrido, Jose (2004) Double Periodic Non–Homogeneous Poisson Models for Hurricanes Data. Technical Report. Concordia University. Department of Mathematics & Statistics, Montreal, Quebec.

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4_04_Lu_Garrido.pdf - Published Version


Non–homogenous Poisson processes with periodic claim intensity rate have been proposed as claim counts in risk theory. Here a doubly periodic Poisson model with short and long–term trends is studied. Beta–type intensity functions are presented as illustrations. The likelihood function and
the maximum likelihood estimates of the model parameters are derived.

Double periodic Poisson models are appropriate when the seasonality does not repeat the exact same short–term pattern every year, but has a peak intensity that varies over a longer period. This reflects periodic environments like those forming hurricanes, in alternating El Nino/La Nina years. An application of the model to the dataset of Atlantic Hurricanes Affecting the United States (1899-2000) is discussed in detail.

Divisions:Concordia University > Faculty of Arts and Science > Mathematics and Statistics
Item Type:Monograph (Technical Report)
Authors:Lu, Yi and Garrido, Jose
Series Name:Department of Mathematics & Statistics. Technical Report No. 4/04
Corporate Authors:Concordia University. Department of Mathematics & Statistics
Institution:Concordia University
Date:September 2004
Keywords:Non–homogeneous Poisson process, Claim intensity function, Periodicity, Double periodic Poisson model, Maximum likelihood estimation, Hurricanes, El Nino/La Nina.
ID Code:6639
Deposited On:03 Jun 2010 19:32
Last Modified:18 Jan 2018 17:29
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