Independent component models for replicated point processes

We propose a semiparametric independent-component model for the intensity functions of replicated point processes. We show that the maximum likelihood estimators of the model parameters are consistent and asymptotically normal when the number of replications goes to infinity. The finite-sample behav...

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Bibliographic Details
Published in:Spatial statistics 2016-11, Vol.18, p.474-488
Main Author: Gervini, Daniel
Format: Article
Language:English
Subjects:
Doubly-stochastic process
Functional data analysis
Latent-variable model
Poisson process
Spline smoothing
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Summary:We propose a semiparametric independent-component model for the intensity functions of replicated point processes. We show that the maximum likelihood estimators of the model parameters are consistent and asymptotically normal when the number of replications goes to infinity. The finite-sample behavior of the estimators is studied by simulation. As an example of application, we analyze the temporal variation in the spatial distribution of street robberies in Chicago.
ISSN:2211-6753
2211-6753
DOI:10.1016/j.spasta.2016.09.006