Algorithms compute robust estimators for loss functions in the concave convex (CC) family by the iteratively reweighted convex optimization (IRCO), an extension of the iteratively reweighted least squares (IRLS). The IRCO reduces the weight of the observation that leads to a large loss; it also provides weights to help identify outliers. Applications include robust (penalized) generalized linear models and robust support vector machines. The package also contains penalized Poisson, negative binomial, zeroinflated Poisson, zeroinflated negative binomial regression models and robust models with nonconvex loss functions. Wang et al. (2014) <doi:10.1002/sim.6314>, Wang et al. (2015) <doi:10.1002/bimj.201400143>, Wang et al. (2016) <doi:10.1177/0962280214530608>, Wang (2021) <doi:10.1007/s11749021007702>, Wang (2020) <arXiv:2010.02848>.
Package details 


Author  Zhu Wang, with contributions from Achim Zeileis, Simon Jackman, Brian Ripley, and Patrick Breheny 
Maintainer  Zhu Wang <wangz1@uthscsa.edu> 
License  GPL2 
Version  0.42.22 
URL  https://github.com/zhuwang46/mpath 
Package repository  View on CRAN 
Installation 
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