Title: Unified Algorithm for Non-convex Penalized Estimation for
Description: An efficient unified nonconvex penalized estimation algorithm for
Gaussian (linear), binomial Logit (logistic), Poisson, multinomial Logit,
and Cox proportional hazard regression models.
The unified algorithm is implemented based on the convex concave procedure and
For high-dimensional data (data set with many variables),
(This research is funded by Julian Virtue Professorship from Center for Applied Research at Pepperdine
Graziadio Business School and the National Research Foundation of Korea.)

Title: High-level R Interface to NetCDF Datasets
Description: This package provides a high-level R interface to Unidata's NetCDF
data files. Using this package netCDF datasets, and all their
associated metadata, can be read and written in one go. It is also
easy to create datasets including lots of metadata.
This package supports both the CF and default NetCDF metadata conventions.
supports more general NetCDF files and conventions than the ncdf
package by David Pierce. It uses the low-level NetCDF package

package by David Pierce. It requires the low-level NetCDF package

Package: ncvar
Version: 1.0-4
Date: 2007-10-21
Title: High-level R Interface to NetCDF Datasets
Author:  Juerg Schmidli
Maintainer: ORPHANED
Depends: R (>= 1.7), RNetCDF
Description: This package provides a high-level R interface to Unidata's NetCDF
data files. Using this package netCDF datasets, and all their
associated metadata, can be read and written in one go. It is also
easy to create datasets including lots of metadata.
This package supports both the CF and default NetCDF metadata conventions.
This package
supports more general NetCDF files and conventions than the ncdf
package by David Pierce. It requires the low-level NetCDF package
RNetCDF by Pavel Michna.
License: GPL (>= 2)
Packaged: Sun Oct 21 00:23:18 2007; hornik

Title: Regularization paths for SCAD- and MCP-penalized regression
for linear or logistic regression models penalized by MCP or

linear or logistic regression models penalized by MCP or SCAD,
with optional additional L2 penalty ("Mnet").