boot.crq: Bootstrapping Censored Quantile Regression

Description

Functions used to estimated standard errors, confidence intervals and tests of hypotheses for censored quantile regression models using the Portnoy and Peng-Huang methods.

Usage

boot.crq(x, y, c, taus, method, ctype = "right", R = 100, mboot, bmethod = "jack", ...)

Arguments

The regression design matrix

The regression response vector

The censoring indicator

taus

The quantiles of interest

method

The fitting method: either "P" for Portnoy or "PH" for Peng and Huang.

ctype

Either "right" or "left"

The number of bootstrap replications

bmethod

The bootstrap method to be employed. There are (as yet) three options: method = "jack" uses the delete-d jackknife method described by Portnoy (2013), method = "xy-pair" uses the xy-pair method, that is the usual multinomial resampling of xy-pairs,

mboot

optional argument for the bootstrap method: for bmethod = "jack" it specifies the number, d, of the delete-d jackknife, for method = "xy-pair" it specifies the size of the bootstrap samples, that permits subsampling (m out of n) bootstrap. By def

...

Optional further arguments to control bootstrapping

Value

A matrix of dimension R by p is returned with the R resampled estimates of the vector of quantile regression parameters. When mofn < n for the "xy" method this matrix has been deflated by the fact sqrt(m/n)

Details

There are several refinements that are still unimplemented. Percentile methods should be incorporated, and extensions of the methods to be used in anova.rq should be made. Note that bootstrapping for the Powell method "FP" is done via boot.rq.

References