Package: galts
Type: Package
Title: Genetic Algorithms and C-Steps Based LTS (Least Trimmed Squares)
        Estimation
Version: 1.3.2
Date: 2023-08-20
Author: Mehmet Hakan Satman
Maintainer: Mehmet Hakan Satman <mhsatman@istanbul.edu.tr>
Description: 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.
Depends: genalg, DEoptim
Repository: CRAN
License: GPL
LazyLoad: yes
Packaged: 2023-08-20 08:08:43 UTC; hako
Date/Publication: 2023-08-20 08:42:32 UTC
NeedsCompilation: no
Built: R 4.3.3; ; 2025-01-24 07:48:18 UTC; unix
