Rank-Based Estimates and Inference for Linear Models

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Description

Package provides functions for rank-based analyses of linear models. Rank-based estimation and inference offers a robust alternative to least squares.

Details

Package: Rfit
Type: Package
Version: 0.21
Date: 2014-11-05
License: GPL (version 2 or later)
LazyLoad: yes

Author(s)

John Kloke, Joesph McKean

Maintainer: John Kloke <kloke@biostat.wisc.edu>

References

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

Jaeckel, L. A. (1972). Estimating regression coefficients by minimizing the dispersion of residuals. Annal s of Mathematical Statistics, 43, 1449 - 1458.

Jureckova, J. (1971). Nonparametric estimate of regression coefficients. Annals of Mathematical Statistics , 42, 1328 - 1338.

Examples

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data(baseball)
data(wscores)
fit<-rfit(weight~height,data=baseball)
summary(fit)
plot(fitted(fit),rstudent(fit))

### Example of the Reduction (Drop) in dispersion test ###
y<-rnorm(47)
x1<-rnorm(47)
x2<-rnorm(47)
fitF<-rfit(y~x1+x2)
fitR<-rfit(y~x1)
drop.test(fitF,fitR)

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