Spatial Mixture Modelling for Unobserved Point Processes: Examples in Immunofluorescence Histology.

ABSTRACT: We discuss Bayesian modelling and computational methods in analysis of indirectly observed spatial point processes. The context involves noisy measurements on an underlying point process that provide indirect and noisy data on locations of point outcomes. We are interested in problems in which the spatial intensity function may be highly heterogenous, and so is modelled via flexible nonparametric Bayesian mixture models. Analysis aims to estimate the underlying intensity function and the abundance of realized but unobserved points. Our motivating applications involve immunological studies of multiple fluorescent intensity images in sections of lymphatic tissue where the point processes represent geographical configurations of cells. We are interested in estimating intensity functions and c

SUBMITTER: Ji C 

PROVIDER: S-EPMC2965046 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature