LTSevol: Least Trimmed Squares Robust Regression

In RFreak: R/FrEAK interface

Description

Carries out least trimmed squares (LTS) robust regression with an evolutionary algorithm. The LTS regression method minimizes the sum of the h smallest squared residuals. Deprecated. Use robreg.evol instead.

Usage

## Deprecated:
LTSevol(y, x, h = NULL, adjust = FALSE, runs = 1, generations = 10000)

Arguments

y	Vector with the response variables
x	Matrix or data frame containing the explanatory variables
h	Parameter determining the trimming
adjust	Whether to perform intercept adjustment at each step
runs	Number of independent runs
generations	Number of generations after which the algorithm will be stopped

Value

The function LTSevol returns an object of class "ltsEA". This object contains:

summary	Summary of the FrEAK run
best	The best subset found
coefficients	Vector of coefficient estimates
crit	The value of the objective function of the LTS regression method, i.e., the sum of the h smallest squared raw residuals

Author(s)

Robin Nunkesser [e-mail]

References

O. Morell, T. Bernholt, R. Fried, J. Kunert, and R. Nunkesser (2008). An Evolutionary Algorithm for LTS-Regression: A Comparative Study. Proceedings of COMPSTAT 2008. To Appear.

P. J. Rousseeuw (1984), Least Median of Squares Regression. Journal of the American Statistical Association 79, 871–881.

See Also

"ltsEA"

Examples

# load example data
data(stackloss)

# compute LTS regression
LTSevol(stackloss[, 4],stackloss[, 1:3],adjust=TRUE,runs=1,generations=1000)

Example output

OpenJDK 64-Bit Server VM warning: Can't detect initial thread stack location - find_vma failed

Result obtained from FrEAK:
  Run Generation Objective value            Individual
1   1       1000       -2.937893 000000100110000001000

Chosen subset:
 [1] 18  7 17  5 15 12 11 10  6 19  9 16  8

Coefficients:
[1] -37.34389818   0.74092106   0.39152672   0.01113454

Criterion:
[1] 2.937893
Warning message:
system call failed: Resource temporarily unavailable 

RFreak documentation built on May 1, 2019, 10:53 p.m.