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.

Package details

AuthorXingguo Li, Tuo Zhao, and Han Liu
MaintainerXingguo Li <xingguo.leo@gmail.com>
LicenseGPL-2
Version0.2.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("camel")

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camel documentation built on May 29, 2017, 10:32 p.m.