Includes the ga.lts() function that estimates LTS (Least Trimmed Squares) parameters using genetic algorithms and Csteps. ga.lts() constructs a genetic algorithm to form a basic subset and iterates Csteps as defined in Rousseeuw and vanDriessen (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.
Package details 


Author  Mehmet Hakan Satman 
Date of publication  20171124 10:49:11 UTC 
Maintainer  Mehmet Hakan Satman <[email protected]> 
License  GPL 
Version  1.3.1 
Package repository  View on CRAN 
Installation 
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