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.
|Author||Xingguo Li, Tuo Zhao, and Han Liu|
|Date of publication||2013-09-09 15:49:04|
|Maintainer||Xingguo Li <firstname.lastname@example.org>|
|Package repository||View on CRAN|
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