An M-estimation-based procedure for determining the number of regression models in regression clustering

Abstract

In this paper, a procedure based on M-estimation to determine the number of regression models for the problem of regression clustering is proposed. We have shown that the true classification is attained when n increases to infinity under certain mild conditions, for instance, without assuming normality of the distribution of the random errors in each regression model.