\name{boot.crq} \alias{boot.crq} \title{ 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 = "Bose", ...) } \arguments{ \item{x}{ The regression design matrix} \item{y}{ The regression response vector} \item{c}{ The censoring indicator} \item{taus}{ The quantiles of interest} \item{method}{ The fitting method: either "P" for Portnoy or "PH" for Peng and Huang.} \item{ctype}{ Either "right" or "left"} \item{R}{ The number of bootstrap replications} \item{bmethod}{ The method to be employed. There are (as yet) two options: method = "xy-pair" uses the xy-pair method, that is the usual multinomial resampling of xy-pairs, while method = "Bose" uses the Bose and Chatterjee (2003) weighted resampling method with exponential weights. This is now the default.} \item{mboot}{ optional argument for the bootstrap method "xy-pair" that permits subsampling (m out of n) bootstrap. Obviously mboot should be substantially larger than the column dimension of x, and should be less than the sample size.} \item{...}{ Optional further arguments to control bootstrapping} } \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 \code{\link{boot.rq}}. } \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) } \references{ Bose, A. and S. Chatterjee, (2003) Generalized bootstrap for estimators of minimizers of convex functions, \emph{J. Stat. Planning and Inf}, 117, 225-239. } \author{ Roger Koenker } \seealso{ \code{\link{summary.crq}}} \keyword{ regression}