galts: Genetic algorithms and C-steps based LTS (Least Trimmed Squares) estimation

This package 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: 1.2
Depends: genalg, DEoptim
Published: 2012-01-07
Author: Mehmet Hakan Satman
Maintainer: Mehmet Hakan Satman <mhsatman at istanbul.edu.tr>
License: GPL
CRAN checks: galts results

Downloads:

Package source: galts_1.2.tar.gz
MacOS X binary: galts_1.2.tgz
Windows binary: galts_1.2.zip
Reference manual: galts.pdf
Old sources: galts archive
Mirror sponsored by mercure eSales Online-Shops: Pro-Colors Bob Ross, Erzgebirgskunst-Shop Weihnachten, Fitness-Master Bodybuilding