Approximating Point Process Likelihoods with GLIM

This paper shows how approximate maximum likelihood estimation for fairly general point processes on the line can be performed with GLIM. The approximation is based on a weighted sum approximation to an integral in the likelihood. Various weighting schemes are briefly examined. The methodology is illustrated with an example, and its extension to Poisson processes in higher dimensions is briefly described.