galts: Genetic Algorithms and C-Steps Based LTS (Least Trimmed Squares) Estimation
Version 1.3.1

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.

Package details

AuthorMehmet Hakan Satman
Date of publication2017-11-24 10:49:11 UTC
MaintainerMehmet Hakan Satman <[email protected]>
LicenseGPL
Version1.3.1
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("galts")

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galts documentation built on Nov. 24, 2017, 5:03 p.m.