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.
||R (≥ 2.15.0), lattice, igraph, MASS, Matrix
||Xingguo Li, Tuo Zhao, and Han Liu
||Xingguo Li <xingguo.leo at gmail.com>
Please use the canonical form
to link to this page.