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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.3.2 |
rolling source/ R- | galts_1.3.2.tar.gz |
4.1 KiB |
1.3.2 |
rolling linux/jammy R-4.5 | galts_1.3.2.tar.gz |
24.5 KiB |
1.3.2 |
latest source/ R- | galts_1.3.2.tar.gz |
4.1 KiB |
1.3.2 |
latest linux/jammy R-4.5 | galts_1.3.2.tar.gz |
24.5 KiB |
1.3.2 |
2026-04-23 source/ R- | galts_1.3.2.tar.gz |
4.1 KiB |
1.3.2 |
2026-04-09 windows/windows R-4.5 | galts_1.3.2.zip |
27.1 KiB |
1.3.2 |
2025-04-20 source/ R- | galts_1.3.2.tar.gz |
4.1 KiB |