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galts
View on CRAN: Click
here
Download and install galts package within the R console
Install from CRAN:
install.packages("galts")
Install from Github:
library("remotes")
install_github("cran/galts") Install by package version:
library("remotes")
install_version("galts", "1.3.2") Attach the package and use:
library("galts")
Maintained by
Mehmet Hakan Satman
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All associated links for this package
First Published: 2010-11-15
Latest Update: 2023-08-20
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.
How to cite:
Mehmet Hakan Satman (2010). galts: Genetic Algorithms and C-Steps Based LTS (Least Trimmed Squares) Estimation. R package version 1.3.2, https://cran.r-project.org/web/packages/galts. Accessed 07 Mar. 2026.
Previous versions and publish date:
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Other R packages that galts depends,
imports, suggests or enhances
Complete documentation for galts
Functions, R codes and Examples using
the galts R package
Some associated functions: ga.lts . galts-package . medmad.cov . medmad .
Some associated R codes: Full galts package functions and examples
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