Robust Mixture of Linear Regression Models

DOI10.1080/03610926.2011.558655zbMath1296.62111OpenAlexW2025691140MaRDI QIDQ3167868

Shaheena Bashir, Edward M. Carter

Publication date: 29 October 2012

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2011.558655

zbMATH Keywords

EM algorithmS-estimatorsmixture modelsbiweight function

Mathematics Subject Classification ID

Nonparametric robustness (62G35) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Linear regression; mixed models (62J05)

Related Items (12)

Robust fitting of mixtures of GLMs by weighted likelihood ⋮ Robust mixture regression using the \(t\)-distribution ⋮ Robust estimation of the number of components for mixtures of linear regression models ⋮ Mixtures of regression models with incomplete and noisy data ⋮ Robust mixture regression modeling based on the generalized M (GM)-estimation method ⋮ Robust mixture regression modeling using the least trimmed squares (LTS)-estimation method ⋮ Robust mixture multivariate linear regression by multivariate Laplace distribution ⋮ A Selective Overview and Comparison of Robust Mixture Regression Estimators ⋮ Robust multivariate mixture regression models with incomplete data ⋮ Outlier detection and robust mixture modeling using nonconvex penalized likelihood ⋮ Robust estimation of mixtures of regressions with random covariates, via trimming and constraints ⋮ Weighted likelihood latent class linear regression

Uses Software

• R
• flexmix

Cites Work

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• A maximum likelihood methodology for clusterwise linear regression
• Some recent research in the analysis of mixture distributions
• Robust Statistics

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