A new method for robust mixture regression

DOI10.1002/cjs.11310zbMath1462.62198OpenAlexW2566526665WikidataQ33744033 ScholiaQ33744033MaRDI QIDQ4960843

Weixin Yao, Chun Yu, Kun Chen

Publication date: 23 April 2020

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc5450514

zbMATH Keywords

EM algorithmoutlier detectionpenalized likelihoodmixture regression models

Mathematics Subject Classification ID

Linear inference, regression (62J99) Robustness and adaptive procedures (parametric inference) (62F35)

Related Items (5)

A Selective Overview and Comparison of Robust Mixture Regression Estimators ⋮ Robust MAVE through nonconvex penalized regression ⋮ Model-based clustering and outlier detection with missing data ⋮ Mixture of multivariate \(t\) nonlinear mixed models for multiple longitudinal data with heterogeneity and missing values ⋮ Weighted likelihood latent class linear regression

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