quantreg (version 4.77)

ranks: Quantile Regression Ranks

Description

Function to compute ranks from the dual (regression rankscore) process.

Usage

ranks(v, score="wilcoxon", tau=0.5, trim = NULL)

Arguments

v

object of class "rq.process" generated by rq()

score

The score function desired. Currently implemented score functions are "wilcoxon", "normal", and "sign" which are asymptotically optimal for the logistic, Gaussian and Laplace location shift models re

tau

the optional value of tau if the "tau" score function is used.

trim

optional trimming proportion parameter(s) -- only applicable for the Wilcoxon score function -- when one value is provided there is symmetric trimming of the score integral to the interval (trim, 1-trim), when there are two values provided

Value

• The function returns two components. One is the ranks, the other is a scale factor which is the $L_2$ norm of the score function. All score functions should be normalized to have mean zero.

Details

See GJKP(1993) for further details.

References

Gutenbrunner, C., J. Jureckova, Koenker, R. and Portnoy, S. (1993) Tests of linear hypotheses based on regression rank scores, Journal of Nonparametric Statistics, (2), 307--331.

Koenker, R. Rank Tests for Heterogeneous Treatment Effects with Covariates, preprint.

See Also

rq, rq.test.rank anova

Examples

data(stackloss)
ranks(rq(stack.loss ~ stack.x, tau=-1))