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\name{sm.survival}
\alias{sm.survival}
\title{
Nonparametric regression with survival data.
}
\description{
This function creates a smooth, nonparametric estimate of the quantile
of the distribution of survival data as a function of a single
covariate. A weighted product-limit estimate of the survivor function
is obtained by smoothing across the covariate scale. A small amount
of smoothing is then also applied across the survival time scale in
order to achieve a smooth estimate of the quantile.
}
\usage{
sm.survival(x, y, status, h , hv = 0.05, p = 0.5, status.code = 1, \dots)
}
\arguments{
\item{x}{
a vector of covariate values.
}
\item{y}{
a vector of survival times.
}
\item{status}{
an indicator of a complete survival time or a censored value. The value of
\code{status.code} defines a complete survival time.
}
\item{h}{
the smoothing parameter applied to the covariate scale. A normal kernel
function is used and \code{h} is its standard deviation.
}
\item{hv}{
a smoothing parameter applied to the weighted to the product-limit
estimate derived from the smoothing procedure in the covariate scale.
This ensures that a smooth estimate is obtained.
}
\item{p}{
the quantile to be estimated at each covariate value.
}
\item{status.code}{
the value of \code{status} which defines a complete survival time.
}
\item{\dots}{
other optional parameters are passed to the \code{sm.options}
function, through a mechanism which limits their effect only to this
call of the function; those relevant for this function are
\code{add},
\code{eval.points},
\code{ngrid},
\code{display},
\code{xlab},
\code{ylab},
\code{lty};
see the documentation of \code{\link{sm.options}} for their
description.
}}
\value{
a list containing the values of the estimate at the evaluation points
and the values of the smoothing parameters for the covariate and survival
time scales.
}
\section{Side Effects}{
a plot on the current graphical device is produced, unless the option
\code{display="none"} is set.
}
\details{
see Section 3.5 of the reference below.
}
\references{
Bowman, A.W. and Azzalini, A. (1997).
\emph{Applied Smoothing Techniques for Data Analysis:}
\emph{the Kernel Approach with S-Plus Illustrations.}
Oxford University Press, Oxford.
}
\seealso{
\code{\link{sm.regression}}, \code{\link{sm.options}}
}
\examples{
x <- runif(50, 0, 10)
y <- rexp(50, 2)
z <- rexp(50, 1)
status <- rep(1, 50)
status[z<y] <- 0
y <- pmin(z, y)
sm.survival(x, y, status, h=2)
}
\keyword{nonparametric}
\keyword{smooth}
\keyword{survival}
% Converted by Sd2Rd version 1.15.
|
