Fitting Growth Regression Model to the Boolean Random Sets

One of the models that can be used to study the relationship between Boolean random sets and explanatory variables is growth regression model which is defined by generalization of Boolean model and permitting its grains distribution to be dependent on the values of explanatory variables. This model can be used in the study of behavior of Boolean random sets when their coverage regions variation is associated with the variation of grains size. In this paper we make possible the identification and fitting suitable growth model using available information in Boolean model realizations and values of explanatory variables. Also, a suitable method for fitting growth regression model is presented and properties of its obtained estimators are studied by a simulation study.