MTE: Maximum Tangent Likelihood and Other Robust Estimation for High-Dimensional Regression

Provides several robust estimators for linear regression and variable selection. They are Maximum tangent likelihood estimator (Qin, et al. (2017) <arXiv:1708.05439>), least absolute deviance estimator, and Huber loss. The penalized version of each of these estimator incorporates L1 penalty function, i.e., LASSO and Adaptive Lasso. They are able to produce consistent estimates for both fixed and high-dimensional settings.

Version: 1.0.0
Depends: R (≥ 3.1.0)
Imports: stats, quantreg, parcor
Published: 2017-08-29
Author: Shaobo Li and Yichen Qin
Maintainer: Shaobo Li <lis6 at mail.uc.edu>
License: GPL-3
NeedsCompilation: no
CRAN checks: MTE results

Downloads:

Reference manual: MTE.pdf
Package source: MTE_1.0.0.tar.gz
Windows binaries: r-devel: MTE_1.0.0.zip, r-release: MTE_1.0.0.zip, r-oldrel: MTE_1.0.0.zip
OS X El Capitan binaries: r-release: MTE_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: MTE_1.0.0.tgz

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