camel: Calibrated Machine Learning

The package "camel" provides the implementation of a family of high-dimensional calibrated machine learning tools, including (1) LAD, SQRT Lasso and Calibrated Dantzig Selector for estimating sparse linear models; (2) Calibrated Multivariate Regression for estimating sparse multivariate linear models; (3) Tiger, Calibrated Clime for estimating sparse Gaussian graphical models. We adopt the combination of the dual smoothing and monotone fast iterative soft-thresholding algorithm (MFISTA). The computation is memory-optimized using the sparse matrix output, and accelerated by the path following and active set tricks.

Version: 0.2.0
Depends: R (≥ 2.15.0), lattice, igraph, MASS, Matrix
Published: 2013-09-09
Author: Xingguo Li, Tuo Zhao, and Han Liu
Maintainer: Xingguo Li <xingguo.leo at>
License: GPL-2
NeedsCompilation: yes
CRAN checks: camel results


Reference manual: camel.pdf
Package source: camel_0.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: camel_0.2.0.tgz, r-oldrel: camel_0.2.0.tgz
OS X Mavericks binaries: r-release: camel_0.2.0.tgz
Old sources: camel archive