Regularization paths for SCAD- and MCP-penalized regression models

Description

Efficient algorithms for fitting regularization paths for a variety of regression models (linear, logistic, Poisson, survival) penalized by MCP or SCAD, with optional additional L2 penalty.

Details

Accepts a design matrix X and vector of responses y, produces the regularization path over a grid of values for the tuning parameter lambda. Also provides methods for plotting, cross-validation-based inference, and for determining locally convex regions of the coefficients paths.

See the "Quick start guide" for a brief overview of how the package works.

Author(s)

Patrick Breheny <patrick-breheny@uiowa.edu>

References

Breheny, P. and Huang, J. (2011) Coordinate descent algorithms for nonconvex penalized regression, with applications to biological feature selection. Ann. Appl. Statist., 5: 232-253.

Examples

vignette("quick-start", package="ncvreg")

Results