glmlep-package {glmlep} | R Documentation |
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.
Author(s)
Canhong Wen, Hao Lin, Shaoli Wang and Xueqin Wang.
Maintainer: Canhong Wen <wencanhong@gmail.com>
References
Wen, C., Wang, X., & Wang, S. (2013). Laplace Error Penalty based variable selection in ultra high-dimension. In press.
Examples
## 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")
[Package glmlep version 0.2 Index]