Rfit: Rank-based Estimation for Linear Models

Authors

John D. Kloke, University of Wisconsin-Madison
Joseph W. McKeen, Western Michigan University

Date of this Version

12-2012

Document Type

Article

Citation

The R Journal (December 2012) 4(2)

Comments

Copyright 2012, The R Foundation. Open access material. License: CC BY 3.0 Unported

Abstract

In the nineteen seventies, Jureĉková and Jaeckel proposed rank estimation for linear models. Since that time, several authors have developed inference and diagnostic methods for these estimators. These rank-based estimators and their associated inference are highly efficient and are robust to outliers in response space. The methods include estimation of standard errors, tests of general linear hypotheses, confidence intervals, diagnostic procedures including studentized residuals, and measures of influential cases. We have developed an R package, Rfit, for computing of these robust procedures. In this paper we highlight the main features of the pack age. The package uses standard linear model syntax and includes many of the main inference and diagnostic functions.