hbrfit-package: High Breakdown Rank-based (HBR) fitting and inference for...

In kloke/hbrfit: High breakdown rank-based (HBR) estimation for linear models

High Breakdown Rank-based (HBR) fitting and inference for linear regression models

Description

High breakdown rank-based (HBR) estimates are robust to outliers in both X & Y spaces. They are based on a weighted Wilcoxon pseudo-norm. Data points which are outliers in both X & Y space are downweighted. HBR estimates achieve 50

This package is based on the weighted Wilcoxon (ww) code developed by Terpstra and McKean (2005) under GPL.

Details

Package:	hbrfit
Type:	Package
Version:	0.2.6
Date:	2023-11-14
License:	GPL (>= 2)

Author(s)

Jeff Terpstra, Joe McKean, John Kloke

References

Chang, W. McKean, J.W., Naranjo, J.D., and Sheather, S.J. (1999), High breakdown rank-based regression, Journal of the American Statistical Association, 94, 205-219.

Hettmansperger, T.P. and McKean J.W. (2011), Robust Nonparametric Statistical Methods, 2nd ed., New York: Chapman-Hall.

Terpstra, J. and McKean, J.W. (2005), Rank-based analyses of linear models using R, Journal of Statistical Software, 14(7).

Examples

data(stars)
plot(stars)
fit<-hbrfit(light~temperature,data=stars)
abline(fit)
summary(fit)

kloke/hbrfit documentation built on Nov. 17, 2023, 2:33 p.m.