Outlying observations and their influence on maximum pseudo-likelihood estimates of Gibbs point processes

Abstract

Maximum pseudo-likelihood estimation method is an attractive method to estimate interaction parameters of Gibbs point processes. A drawback of the method is that it tends to overestimate interaction if there is strong repulsion between the points. We assumed that one reason for overestimation is that the method is sensitive to outlying points. Several techniques were used to detect outlying observations for the data of amacrine cells for which overestimation is suspected. Some strategies were then tested to take outliers into account in maximum pseudo-likelihood estimation.