glmlep (version 0.2)

glmlep-package: Regularization paths for LEP-penalized regression models

Description

Efficient algorithms for fitting regularization paths for linear or logistic regression models penalized by LEP.

Details

Package:	glmlep
Type:	Package
Version:	0.1
Date:	2013-06-05
License:	GPL-2

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 and for determining locally convex regions of the coefficients paths.

References

Wen, C., Wang, X., & Wang, S. (2013). Laplace Error Penalty based variable selection in ultra high-dimension. In press.

Examples

# NOT RUN {
## generate data
require(mvtnorm)
n <- 100;
beta <- c(3,1.5,0,0,2,0,0,0)

set.seed(100)
p <- length(beta);
corr_data <- diag(rep(1,p));

x <- as.matrix(rmvnorm(n,rep(0,p),corr_data))
noise <- rnorm(n)

y <- tcrossprod(x,t(beta)) + noise;
fit <- glmlep(x,y,family="gaussian")
# }