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 1.3 included the function medmad for fast outlier detection in linear regression.
|Author:||Mehmet Hakan Satman|
|Maintainer:||Mehmet Hakan Satman <mhsatman at istanbul.edu.tr>|
|License:||GPL-2 | GPL-3 [expanded from: GPL]|
|CRAN checks:||galts results|
|Windows binaries:||r-devel: galts_1.3.zip, r-release: galts_1.3.zip, r-oldrel: galts_1.3.zip|
|OS X El Capitan binaries:||r-release: galts_1.3.tgz|
|OS X Mavericks binaries:||r-oldrel: galts_1.3.tgz|
|Old sources:||galts archive|
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