The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Includes the ga.lts() function that estimates LTS (Least Trimmed Squares) parameters using genetic algorithms and C-steps. ga.lts() constructs a genetic algorithm to form a basic subset and iterates C-steps as defined in Rousseeuw and van-Driessen (2006) to calculate the cost value of the LTS criterion. OLS (Ordinary Least Squares) regression is known to be sensitive to outliers. A single outlying observation can change the values of estimated parameters. LTS is a resistant estimator even the number of outliers is up to half of the data. This package is for estimating the LTS parameters with lower bias and variance in a reasonable time. Version >=1.3 includes the function medmad for fast outlier detection in linear regression.
| Version: | 1.3.2 |
| Depends: | genalg, DEoptim |
| Published: | 2023-08-20 |
| Author: | Mehmet Hakan Satman |
| Maintainer: | Mehmet Hakan Satman <mhsatman at istanbul.edu.tr> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| NeedsCompilation: | no |
| CRAN checks: | galts results |
| Reference manual: | galts.pdf |
| Package source: | galts_1.3.2.tar.gz |
| Windows binaries: | r-devel: galts_1.3.2.zip, r-release: galts_1.3.2.zip, r-oldrel: galts_1.3.2.zip |
| macOS binaries: | r-release (arm64): galts_1.3.2.tgz, r-oldrel (arm64): galts_1.3.2.tgz, r-release (x86_64): galts_1.3.2.tgz, r-oldrel (x86_64): galts_1.3.2.tgz |
| Old sources: | galts archive |
Please use the canonical form https://CRAN.R-project.org/package=galts to link to this page.
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.
Health stats visible at Monitor.