RobustLinearReg: Robust Linear Regressions

Provides an easy way to compute the Theil Sehn Regression method and also the Siegel Regression Method which are both robust methods base on the median of slopes between all pairs of data. In contrast with the least squared linear regression, these methods are not sensitive to outliers. Theil, H. (1992) <doi:10.1007/978-94-011-2546-8_20>, Sen, P. K. (1968) <doi:10.1080/01621459.1968.10480934>.

Version:	1.2.0
Depends:	R (≥ 3.1.0)
Published:	2020-06-12
Author:	Santiago I. Hurtado
Maintainer:	Santiago I. Hurtado <santih at carina.fcaglp.unlp.edu.ar>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	RobustLinearReg results

Documentation:

Reference manual:

RobustLinearReg.pdf

Downloads:

Package source:	RobustLinearReg_1.2.0.tar.gz
Windows binaries:	r-devel: RobustLinearReg_1.2.0.zip, r-release: RobustLinearReg_1.2.0.zip, r-oldrel: RobustLinearReg_1.2.0.zip
macOS binaries:	r-release (arm64): RobustLinearReg_1.2.0.tgz, r-oldrel (arm64): RobustLinearReg_1.2.0.tgz, r-release (x86_64): RobustLinearReg_1.2.0.tgz, r-oldrel (x86_64): RobustLinearReg_1.2.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=RobustLinearReg to link to this page.