Propagation Models and Fitting Them for the Boolean Random Sets

In order to study the relationship between random boolean sets and some explanatory variables, this paper introduces a propagation model. this model can be applied when corresponding poisson process of the boolean model is related to explanatory variables and the random grains are not affected by these variables. an approximation for the likelihood is used to find pseudo-maximum likelihood estimates of propagation model parameters when the grains are nonrandom circle with unknown radii.