Revision 2ea67f3ec1c11c6450ae48c65249aef5c0e34a24 authored by Han Lin Shang on 31 March 2011, 00:00:00 UTC, committed by Gabor Csardi on 31 March 2011, 00:00:00 UTC
1 parent ac6723e
fbootstrap.Rd
\name{fbootstrap}
\alias{fbootstrap}
\title{Bootstrap independent and identically distributed functional data}
\description{
Computes bootstrap or smoothed bootstrap samples based on independent and identically distributed functional data.
}
\usage{
fbootstrap(data, estad = func.mean, alpha = 0.05, nb = 200, suav = 0,
media.dist = FALSE, graph = FALSE, ...)
}
\arguments{
\item{data}{An object of class \code{\link[rainbow]{fds}} or \code{fts}.}
\item{estad}{Estimate function of interest. Default is to estimate the mean function. Other options are \code{func.mode} or \code{func.var}.}
\item{alpha}{Significance level used in the smooth bootstrapping.}
\item{nb}{Number of bootstrap samples.}
\item{suav}{Smoothing parameter.}
\item{media.dist}{Estimate mean function.}
\item{graph}{Graphical output.}
\item{\dots}{Other arguments.}
}
\value{
A list containing the following components is returned.
\item{estimate}{Estimate function.}
\item{max.dist}{Max distance of bootstrap samples.}
\item{rep.dist}{Distances of bootstrap samples.}
\item{resamples}{Bootstrap samples.}
\item{center}{Functional mean.}
}
\references{
M. Febrero and P. Galeano and W. Gonzalez-Manteiga (2007) "A functional analysis of NOx levels: location and scale estimation and outlier detection", \emph{Computational Statistics}, \bold{22}(3), 411-427.
M. Febrero and P. Galeano and W. Gonzalez-Manteiga (2008) "Outlier detection in functional data by depth measures, with application to identify abnormal NOx levels", \emph{Environmetrics}, \bold{19}(4), 331-345.
M. Febrero and P. Galeano and W. Gonzalez-Manteiga (2009) "Measures of influence for the functional linear model with scalar response", \emph{Journal of Multivariate Analysis}, \bold{forthcoming}.
}
\author{Han Lin Shang}
\examples{
fbootstrap(data = ElNino)
}
\keyword{multivariate}
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