1 citations · 1 across the 4 of their papers we have counts for
4 papers
Robust Clustering for Time Series Using Spectral Densities and Functional Data Analysis
Diego Rivera-García, Luis Angel García-Escudero, Agustín Mayo-Iscar +1
In this work a robust clustering algorithm for stationary time series is proposed. The algorithm is based on the use of estimated spectral densities, which are considered as functi…
Robust clustering for functional data based on trimming and constraints
Diego Rivera-García, Luis Angel García-Escudero, Agustín Mayo-Iscar +1
Many clustering algorithms when the data are curves or functions have been recently proposed. However, the presence of contamination in the sample of curves can influence the perfo…
Robust estimation for mixtures of Gaussian factor analyzers, based on trimming and constraints
L. A. García-Escudero, A. Gordaliza, F. Greselin +2
Mixtures of Gaussian factors are powerful tools for modeling an unobserved heterogeneous population, offering - at the same time - dimension reduction and model-based clustering. U…
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…