New estimation in mixture of experts models using the Pearson type VII distribution

DOI10.1080/03610918.2018.1485943OpenAlexW2943516823MaRDI QIDQ5087949

Lin Dai, Hanchi Lu, Junhui Yin, Liu-Cang Wu

Publication date: 4 July 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2018.1485943

zbMATH Keywords

EM algorithmmixture of expertsrobust estimationPearson type VII distribution

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Robustness and adaptive procedures (parametric inference) (62F35)

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Cites Work

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• Semiparametric mixtures of regressions
• Identifiability of models for clusterwise linear regression
• Robust mixture regression using the \(t\)-distribution
• Laplace mixture of linear experts
• Distributed variational Bayesian algorithms for Gaussian mixtures in sensor networks
• Robust mixture of experts modeling using the \(t\) distribution
• New estimation and feature selection methods in mixture-of-experts models
• Penalized logistic regression for detecting gene interactions
• Finite mixture models

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