## 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.

Version: |
1.3 |

Depends: |
genalg, DEoptim |

Published: |
2013-02-07 |

Author: |
Mehmet Hakan Satman |

Maintainer: |
Mehmet Hakan Satman <mhsatman at istanbul.edu.tr> |

License: |
GPL-2 | GPL-3 [expanded from: GPL] |

NeedsCompilation: |
no |

CRAN checks: |
galts results |

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