pawls: Penalized Adaptive Weighted Least Squares Regression

Efficient algorithms for fitting weighted least squares regression with \eqn{L_{1}}{L1} regularization on both the coefficients and weight vectors, which is able to perform simultaneous variable selection and outliers detection efficiently.

Version: 1.0.0
Suggests: mvtnorm
Published: 2017-05-11
Author: Bin Luo, Xiaoli Gao
Maintainer: Bin Luo <b_luo at uncg.edu>
License: GPL-2
NeedsCompilation: yes
CRAN checks: pawls results

Downloads:

Reference manual: pawls.pdf
Package source: pawls_1.0.0.tar.gz
Windows binaries: r-devel: pawls_1.0.0.zip, r-release: pawls_1.0.0.zip, r-oldrel: pawls_1.0.0.zip
OS X El Capitan binaries: r-release: pawls_1.0.0.tgz
OS X Mavericks binaries: r-oldrel: pawls_1.0.0.tgz

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