A0351
Title: Bayesian nonparametric nonhomogeneous Poisson process with applications
Authors: Guanyu Hu - University of Missouri Columbia (United States) [presenting]
Abstract: Intensity estimation is a common problem in statistical analysis of spatial point pattern data. A nonparametric Bayesian method is proposed for estimating the spatial point process intensity based on mixture of finite mixture (MFM) model. The MFM approach leads a consistent estimate on the intensity of spatial point patterns in different areas while considering heterogeneity. An efficient Markov chain Monte Carlo (MCMC) algorithm is proposed for our methods. Extensive simulation studies are carried out to examine empirical performance of the proposed methods. The usage of our proposed methods is further illustrated with the analysis of the Earthquake Hazards Program of United States Geological Survey (USGS) earthquake data.
