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arXiv · 1812.09607

Bayesian semiparametric modelling of phase-varying point processes

Bastian Galasso·Yoav Zemel·Miguel de Carvalho
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Abstract

We propose a Bayesian semiparametric approach for registration of multiple point processes. Our approach entails modelling the mean measures of the phase-varying point processes with a Bernstein-Dirichlet prior, which induces a prior on the space of all warp functions. Theoretical results on the support of the induced priors are derived, and posterior consistency is obtained under mild conditions. Numerical experiments suggest a good performance of the proposed methods, and a climatology real-data example is used to showcase how the method can be employed in practice.

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Bastian Galasso, Yoav Zemel, Miguel de Carvalho. 2018-12-22. Bayesian semiparametric modelling of phase-varying point processes. https://arxiv.org/abs/1812.09607

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