Regression trees and forests for non-homogeneous Poisson processes

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.

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Year of publication:	2015
Authors:	Mathlouthi, Walid ; Fredette, Marc ; Larocque, Denis
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 96.2015, C, p. 204-211
Publisher:	Elsevier
Subject:	Non-homogeneous Poisson processes \| Poisson tree \| Random forests \| Maximum likelihood \| Recursive partitioning \| Recurrent events

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011115944