APPROXIMATE MAXIMUM LIKELIHOOD ESTIMATION FOR A SPATIAL POINT PATTERN⋆

Several authors have proposed stochastic and non-stochastic approxima-tions to the maximum likelihood estimate for a spatial point pattern. This approximation is necessary because of the difficulty of evaluating the nor-malizing constant. However, it appears to be neither a general theory which provides grounds for preferring a particular method, nor any extensive em-pirical comparisons. In this paper, we review five general methods based on approximations to the maximum likelihood estimate which have been proposed in the literature. We also present the results of a comparative simulation study developed for the Strauss model