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galts: Genetic Algorithms and C-Steps Based LTS (Least Trimmed Squares) Estimation
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.
Getting started
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Package details |
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| Author | Mehmet Hakan Satman |
| Maintainer | Mehmet Hakan Satman <mhsatman@istanbul.edu.tr> |
| License | GPL |
| Version | 1.3.2 |
| Package repository | View on CRAN |
| Installation |
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