Title
Smooth flexible models of nonhomogeneous poisson processes using one or more process realizations
Abstract
We develop and evaluate a semiparametric method to estimate the mean-value function of a nonhomogeneous Poisson process (NHPP) using one or more process realizations observed over a fixed time interval. To approximate the mean-value function, the method exploits a specially formulated polynomial that is constrained in least-squares estimation to be nondecreasing so the corresponding rate function is nonnegative and smooth (continuously differentiable). An experimental performance evaluation for two typical test problems demonstrates the method¿s ability to yield an accurate fit to an NHPP based on a single process realization. A third test problem shows how the method can estimate an NHPP based on multiple realizations of the process.
Year
DOI
Venue
2008
10.1109/WSC.2008.4736088
Winter Simulation Conference
Keywords
DocType
ISBN
least squares approximations,modelling,stochastic processes,formulated polynomial,least-squares estimation,mean-value function,nonhomogeneous Poisson processes,process realizations,smooth flexible models
Conference
978-1-4244-2708-6
Citations 
PageRank 
References 
4
0.58
8
Authors
3
Name
Order
Citations
PageRank
Michael E. Kuhl118834.82
Shalaka C. Deo240.58
James R. Wilson3840143.42