RobMixReg: an R package for robust, flexible and high dimensional mixture regression

Author:

Chang Wennan,Wan Changlin,Yu Chun,Yao Weixin,Zhang Chi,Cao Sha

Abstract

AbstractMotivationMixture regression has been widely used as a statistical model to untangle the latent subgroups of the sample population. Traditional mixture regression faces challenges when dealing with: 1) outliers and versatile regression forms; and 2) the high dimensionality of the predictors. Here, we develop an R package called RobMixReg, which provides comprehensive solutions for robust, flexible as well as high dimensional mixture modeling.Availability and ImplementationRobMixReg R package and associated documentation is available at CRAN: https://CRAN.R-project.org/package=RobMixReg.

Publisher

Cold Spring Harbor Laboratory

Reference12 articles.

1. Robust fitting of mixture regression models

2. Böhning, D. Computer-assisted analysis of mixtures and applications: meta-analysis, disease mapping and others. CRC press; 1999.

3. Supervised clustering of high dimensional data using regularized mixture modeling;arXiv preprint,2020

4. A New Algorithm using Component-wise Adaptive Trimming For Robust Mixture Regression;arXiv preprint,2020

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