Regularization paths for SCAD- and MCP-penalized regression
models
Efficient algorithms for fitting the regularization path
for linear or logistic regression models penalized by MCP or
SCAD.

Efficient algorithms for fitting regularization paths for
linear or logistic regression models penalized by MCP or SCAD,
with optional additional L2 penalty ("Mnet").

Efficient algorithms for fitting regularization paths for linear or logistic regression models penalized by MCP or SCAD, with optional additional L2 penalty ("Mnet").

Regularization Paths for SCAD and MCP Penalized Regression
Models
Efficient algorithms for fitting regularization paths for linear or
logistic regression models penalized by MCP or SCAD, with optional additional
L2 penalty.

person("Patrick", "Breheny", role=c("aut","cre"), email="patrick-breheny@uiowa.edu", comment=c(ORCID="000-0002-0650-1119"))
Fits regularization paths for linear regression, GLM, and Cox regression models using lasso or nonconvex penalties, in particular the minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD) penalty, with options for additional L2 penalties (the "elastic net" idea).  Utilities for carrying out cross-validation as well as post-fitting visualization, summarization, inference, and prediction are also provided.
Patrick Breheny [aut, cre] (<https://orcid.org/000-0002-0650-1119>)

person("Patrick", "Breheny", role=c("aut","cre"),
email="patrick-breheny@uiowa.edu", comment=c(ORCID="000-0002-0650-1119"))
Fits regularization paths for linear regression, GLM, and Cox
regression models using lasso or nonconvex penalties, in particular the
minimax concave penalty (MCP) and smoothly clipped absolute deviation (SCAD)
penalty, with options for additional L2 penalties (the "elastic net" idea).
Utilities for carrying out cross-validation as well as post-fitting
visualization, summarization, inference, and prediction are also provided.

person("Patrick", "Breheny", role=c("aut","cre"),
email="patrick-breheny@uiowa.edu", comment=c(ORCID="0000-0002-0650-1119"))
Patrick Breheny [aut, cre] (<https://orcid.org/0000-0002-0650-1119>)