Rank-Based Estimates and Inference for Linear Models
Rank-Based Estimates and Inference for Linear Models
Package provides functions for rank-based analyses of linear models. Rank-based estimation and inference offers a robust alternative to least squares.
package
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
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)