90 citations · 148 across the 8 of their papers we have counts for
6 papers · 1 filter
Robust estimation of mixtures of regressions with random covariates, via trimming and constraints
L. A. Garcia-Escudero, A. Gordaliza, F. Greselin +2
A robust estimator for a wide family of mixtures of linear regression is presented. Robustness is based on the joint adoption of the Cluster Weighted Model and of an estimator base…
Fitting Bivariate Mixed-Type Data via the Generalized Linear Exponential Cluster-Weighted Model
Salvatore Ingrassia, Antonio Punzo
The cluster-weighted model (CWM) is a mixture model with random covariates which allows for flexible clustering and density estimation of a random vector composed by a response var…
Maximum likelihood estimation in constrained parameter spaces for mixtures of factor analyzers
Francesca Greselin, Salvatore Ingrassia
Mixtures of factor analyzers are becoming more and more popular in the area of model based clustering of high-dimensional data. According to the likelihood approach in data modelin…
Generalized Linear Gaussian Cluster-Weighted Modeling
Salvatore Ingrassia, Simona C. Minotti, Antonio Punzo +1
Cluster-Weighted Modeling (CWM) is a flexible mixture approach for modeling the joint probability of data coming from a heterogeneous population as a weighted sum of the products o…
Clustering and Classification via Cluster-Weighted Factor Analyzers
Sanjeena Subedi, Antonio Punzo, Salvatore Ingrassia +1
In model-based clustering and classification, the cluster-weighted model constitutes a convenient approach when the random vector of interest constitutes a response variable Y and…
Local statistical modeling by cluster-weighted
Salvatore Ingrassia, Simona C. Minotti, Giorgio Vittadini
We investigate statistical properties of Cluster-Weighted Modeling, which is a framework for supervised learning originally developed in order to recreate a digital violin with tra…