An \(M\)-estimation-based procedure for determining the number of regression models in regression clustering
Summary: 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.
scientific article; zbMATH DE number 5304406