Description Details Author(s) References Examples

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.

Package: | hbrfit |

Type: | Package |

Version: | 0.01 |

Date: | 2013-10-30 |

License: | GPL |

Jeff Terpstra, Joe McKean, John Kloke Maintainer: John Kloke [email protected]

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).

1 2 3 4 5 |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.