mpath: Regularized Linear Models

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, zero-inflated Poisson, zero-inflated negative binomial regression models and robust models with non-convex 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/s11749-021-00770-2>, Wang (2024) <doi:10.1111/anzs.12409>.

Version:	0.4-2.25
Depends:	R (≥ 3.5.0), methods, glmnet, pamr
Imports:	MASS, pscl, numDeriv, foreach, doParallel, bst, WeightSVM
Suggests:	zic, R.rsp, knitr, rmarkdown, openxlsx, e1071, SparseM, slam
Published:	2024-03-09
Author:	Zhu Wang, with contributions from Achim Zeileis, Simon Jackman, Brian Ripley, and Patrick Breheny
Maintainer:	Zhu Wang <zwang145 at uthsc.edu>
BugReports:	https://github.com/zhuwang46/mpath
License:	GPL-2
Copyright:	see file COPYRIGHTS
URL:	https://github.com/zhuwang46/mpath
NeedsCompilation:	yes
Citation:	mpath citation info
Materials:	NEWS
In views:	MachineLearning
CRAN checks:	mpath results

Documentation:

Reference manual:

mpath.pdf

Vignettes:

Classification of Cancer Patients with Penalized Robust Nonconvex Loss Functions (with Results) Variable Selection for Zero-inflated and Overdispersed Data with Application to Health Care Demand in Germany Robust Generalized Linear Models Robust Support Vector Machines Classification of Cancer Patients with Penalized Robust Nonconvex Loss Functions (without Results) KKT Conditions for Zero-Inflated Regression

Downloads:

Package source:	mpath_0.4-2.25.tar.gz
Windows binaries:	r-devel: mpath_0.4-2.25.zip, r-release: mpath_0.4-2.25.zip, r-oldrel: mpath_0.4-2.25.zip
macOS binaries:	r-release (arm64): mpath_0.4-2.25.tgz, r-oldrel (arm64): mpath_0.4-2.25.tgz, r-release (x86_64): mpath_0.4-2.25.tgz, r-oldrel (x86_64): mpath_0.4-2.25.tgz
Old sources:	mpath archive

Reverse dependencies:

Reverse depends:	NBtsVarSel
Reverse imports:	bujar, irboost, nbfar

Linking:

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