DESCRIPTION

Package: picasso
Type: Package
Title: Pathwise Calibrated Sparse Shooting Algorithm
Version: 1.1.0
Date: 2017-09-09
Author: Jason Ge, Xingguo Li, Mengdi Wang, Tong Zhang, Han Liu and Tuo Zhao
Maintainer: Jason Ge <jiange@princeton.edu>
Depends: R (>= 2.15.0), MASS, Matrix
Imports: methods
Description: Computationally efficient tools for fitting generalized linear model with convex or non-convex penalty. Users can enjoy the superior statistical property of non-convex penalty such as SCAD and MCP which has significantly less estimation error and overfitting compared to convex penalty such as lasso and ridge. Computation is handled by multi-stage convex relaxation and the PathwIse CAlibrated Sparse Shooting algOrithm (PICASSO) which exploits warm start initialization, active set updating, and strong rule for coordinate preselection to boost computation, and attains a linear convergence to a unique sparse local optimum with optimal statistical properties. The computation is memory-optimized using the sparse matrix output.
License: GPL-3 
Repository: CRAN
Packaged: 2017-09-09 12:00:00 UTC; Jason
NeedsCompilation: yes