2018/12/22 by Bastian Galasso, Galasso, Bastian, Yoav Zemel +3
Mathematics · #60G55 #62F15 #62G99 #FOS: Computer and information sciences #Methodology (stat.ME) #Morphological variations and asymmetry
paper · doi:10.48550/arxiv.1812.09607
openalex publication_date 2018/12/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.