Regression trees and forests for non-homogeneous Poisson processes

Walid Mathlouthi, Marc Fredette and Denis Larocque

Statistics & Probability Letters, 2015, vol. 96, issue C, 204-211

Abstract: We propose tree and random forest methods for non-homogeneous Poisson processes. The splitting criterion is derived from a model with a piecewise constant rate function. A simulation study shows that the new method performs well.

Keywords: Non-homogeneous Poisson processes; Poisson tree; Random forests; Maximum likelihood; Recursive partitioning; Recurrent events (search for similar items in EconPapers)
Date: 2015
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DOI: 10.1016/j.spl.2014.09.025

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