Package: galts 1.3.2
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.
Authors:
galts_1.3.2.tar.gz
galts_1.3.2.zip(r-4.5)galts_1.3.2.zip(r-4.4)galts_1.3.2.zip(r-4.3)
galts_1.3.2.tgz(r-4.4-any)galts_1.3.2.tgz(r-4.3-any)
galts_1.3.2.tar.gz(r-4.5-noble)galts_1.3.2.tar.gz(r-4.4-noble)
galts_1.3.2.tgz(r-4.4-emscripten)galts_1.3.2.tgz(r-4.3-emscripten)
galts.pdf |galts.html✨
galts/json (API)
| # Install 'galts' in R: |
| install.packages('galts', repos = c('https://jbytecode.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jbytecode/galts/issues
Last updated 1 years agofrom:5b5f466773. Checks:OK: 1 ERROR: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 09 2024 |
| R-4.5-win | ERROR | Nov 09 2024 |
| R-4.5-linux | ERROR | Nov 09 2024 |
| R-4.4-win | ERROR | Nov 09 2024 |
| R-4.4-mac | ERROR | Nov 09 2024 |
| R-4.3-win | ERROR | Nov 09 2024 |
| R-4.3-mac | ERROR | Nov 09 2024 |
Exports:ga.ltsmedmadmedmad.cov
