swh:1:snp:16c54c84bc54885e783d4424d714e5cc82f479a1
Tip revision: 2f2f1b1baacd9c4f4e8e77aa46a209dff6bbe628 authored by Roger Koenker on 04 September 2012, 00:00:00 UTC
version 4.90
version 4.90
Tip revision: 2f2f1b1
boot.crq.Rd
\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}