# galts: Genetic algorithms and C-steps based LTS (Least Trimmed Squares) estimation

This package 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 included the function medmad for fast outlier detection in linear regression.

- Author
- Mehmet Hakan Satman
- Date of publication
- 2013-02-07 09:27:39
- Maintainer
- Mehmet Hakan Satman <mhsatman@istanbul.edu.tr>
- License
- GPL
- Version
- 1.3

## Man pages

- ga.lts
- Function for estimating the LTS (Least Trimmed Squares)...
- galts-package
- Genetic algorithms and C-steps based LTS (Least Trimmed...
- medmad
- Function for detecting regression outliers
- medmad.cov
- Function for robust covariance matrix estimation.

## Files in this package

galts |

galts/MD5 |

galts/man |

galts/man/medmad.cov.Rd |

galts/man/galts-package.Rd |

galts/man/ga.lts.Rd |

galts/man/medmad.Rd |

galts/NAMESPACE |

galts/DESCRIPTION |

galts/R |

galts/R/medmad.r |

galts/R/galts.r |