swh:1:snp:16c54c84bc54885e783d4424d714e5cc82f479a1
Tip revision: e68bc7a85a07b3e14413a96d0e472ee5a317a644 authored by Roger Koenker on 24 February 2021, 15:20:02 UTC
version 5.85
version 5.85
Tip revision: e68bc7a
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 = "jack", ...)
}
\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 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, while method
= "Bose" uses the Bose and Chatterjee (2003) weighted resampling
method with exponential weights. The "jack" method is now the default.}
\item{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 default in the
former case it is set to 2 [sqrt(n)], for the latter the default is
n. Obviously mboot should be substantially larger than the column dimension
of x, and should be less than the sample size in both cases.}
\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 "Powell" is done via \code{\link{boot.rq}}. For problems with
\code{n > 3000} a message is printed indicated progress in the resampling.
}
\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 factor 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.
Portnoy, S. (2013) The Jackknife's Edge: Inference for Censored Quantile Regression,
\emph{CSDA}, forthcoming.
}
\author{ Roger Koenker }
\seealso{ \code{\link{summary.crq}}}
\keyword{ regression}