Algorithms compute concave convex (CC) estimators including robust (penalized) generalized linear models and robust support vector machines via the COCO - composite optimization by conjugation operator. 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 (2019) <arXiv:1912.11119>, Wang (2020) <arXiv:2010.02848>.
Version: | 0.4-2.18 |
Depends: | R (≥ 3.5.0), methods, glmnet, pamr |
Imports: | MASS, pscl, numDeriv, foreach, doParallel, bst, WeightSVM |
Suggests: | zic, R.rsp, knitr, rmarkdown, gdata, e1071, SparseM, slam |
Published: | 2021-02-15 |
Author: | Zhu Wang, with contributions from Achim Zeileis, Simon Jackman, Brian Ripley, and Patrick Breheny |
Maintainer: | Zhu Wang <wangz1 at uthscsa.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 |
CRAN checks: | mpath results |
Reference manual: | mpath.pdf |
Vignettes: |
Classification of Cancer Patients with Penalized Robust Nonconvex Loss Functions (with Results) Robust Generalized Linear Models Robust Support Vector Machines Variable Selection for Zero-inflated and Overdispersed Data with Application to Health Care Demand in Germany Classification of Cancer Patients with Penalized Robust Nonconvex Loss Functions (without Results) KKT Conditions for Zero-Inflated Regression |
Package source: | mpath_0.4-2.18.tar.gz |
Windows binaries: | r-devel: mpath_0.4-2.18.zip, r-release: mpath_0.4-2.18.zip, r-oldrel: mpath_0.4-2.18.zip |
macOS binaries: | r-release: mpath_0.4-2.18.tgz, r-oldrel: mpath_0.4-2.18.tgz |
Old sources: | mpath archive |
Reverse imports: | bujar, ccboost |
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