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galts  

Genetic Algorithms and C-Steps Based LTS (Least Trimmed Squares) Estimation
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
[Scholar Profile | Author Map]
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 06 Apr. 2025.
Previous versions and publish date:
1.0 (2010-11-15 08:28), 1.1 (2011-02-05 18:08), 1.2 (2012-01-07 07:51), 1.3.1 (2017-11-24 11:49), 1.3 (2013-02-07 09:27)
Other packages that cited galts R package
View galts citation profile
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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