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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 |
| DOI: | 10.32614/CRAN.package.RobustLinearReg |
| Author: | Santiago I. Hurtado |
| Maintainer: | Santiago I. Hurtado <santih at carina.fcaglp.unlp.edu.ar> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | RobustLinearReg results |
| Reference manual: | RobustLinearReg.pdf |
| 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 |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.