Graphical and Computational Tools to Guide Parameter Choice for the Cluster Weighted Robust Model

Andrea Cappozzo, Luis Angel García-Escudero, Francesca Greselin & Agustín Mayo-Iscar
The Cluster Weighted Robust Model (CWRM) is a recently introduced methodology to robustly estimate mixtures of regressions with random covariates. The CWRM allows users to flexibly perform regression clustering, safeguarding it against data contamination and spurious solutions. Nonetheless, the resulting solution depends on the chosen number of components in the mixture, the percentage of impartial trimming, the degree of heteroscedasticity of the errors around the regression lines and of the clusters in the explanatory variables....

Registration Year

  • 2023

Resource Types

  • Dataset


  • Politecnico di Milano