Space‐time Multi Type Log Gaussian Cox Processes with a View to Modelling Weeds

Abstract

Log Gaussian Cox processes as introduced in Moller et al. (1998) are extended to space‐time models called log Gaussian Cox birth processes. These processes allow modelling of spatial and temporal heterogeneity in time series of increasing point processes consisting of different types of points. The models are shown to be easy to analyse yet flexible enough for a detailed statistical analysis of a particular agricultural experiment concerning the development of two weed species on an organic barley field. Particularly, the aspects of estimation, model validation and intensity surface prediction are discussed.