Zhu Wang <https://orcid.org/0000-0002-0773-0052>, with contributions from Achim Zeileis, Simon Jackman, Brian Ripley, Trevor Hastie, Rob Tibshirani, Balasubramanian Narasimhan, Gil Chu and Patrick Breheny

MASS, numDeriv, foreach, doParallel, bst

Algorithms for fitting model-based penalized coefficient paths. Currently the models include penalized Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial regression models. The penalties include least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP), and each possibly combining with L_2 penalty. See 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>.

Zhu Wang, with contributions from Achim Zeileis, Simon Jackman, Brian Ripley, and Patrick Breheny
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 contain penalized Poisson, negative binomial, zero-inflated Poisson, zero-inflated negative binomial regression models and robust models with non-convex loss functions. See 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>.
MASS, pscl, numDeriv, foreach, doParallel, bst, WeightSVM
zic, R.rsp, knitr, rmarkdown, gdata, e1071

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. See 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>.
zic, R.rsp, knitr, rmarkdown, gdata, e1071, SparseM, slam