The Cluster-Weighted Model (CWM) is a member of the family of the Mixtures of Regression Models and it is referred as Mixture of Regression with Ran- dom Covariates. Currently, the only procedure for estimating these models is R pack- age flexcwm. The aim of this article is to introduce a new software component, the Stata package cwmglm which estimates CWMs based on the most common general- ized linear models. Our software also extends to Stata users the possibility of estimat- ing parsimonious models of Gaussian distributions with alternative specifications of the variance matrix. cwmglm also calculates the the generalized coefficients of de- termination and bootstrap standard errors that are not currently available in flexcwm. We illustrate the use of cwmglm with real data on Covid-19 admissions.
A Stata implementation of Cluster Weighted Models: the CWMGLM Package
Salvatore IngrassiaMethodology
;Giorgio VittadiniMethodology
2023-01-01
Abstract
The Cluster-Weighted Model (CWM) is a member of the family of the Mixtures of Regression Models and it is referred as Mixture of Regression with Ran- dom Covariates. Currently, the only procedure for estimating these models is R pack- age flexcwm. The aim of this article is to introduce a new software component, the Stata package cwmglm which estimates CWMs based on the most common general- ized linear models. Our software also extends to Stata users the possibility of estimat- ing parsimonious models of Gaussian distributions with alternative specifications of the variance matrix. cwmglm also calculates the the generalized coefficients of de- termination and bootstrap standard errors that are not currently available in flexcwm. We illustrate the use of cwmglm with real data on Covid-19 admissions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.