https://github.com/cran/fda
Tip revision: 15eef20d327b5d3061081a22e402af16474a5808 authored by J. O. Ramsay on 06 July 2007, 00:00:00 UTC
version 1.2.2
version 1.2.2
Tip revision: 15eef20
sd.Rd
\name{sd.fd}
\alias{sd.fd}
\alias{std.fd}
\alias{stdev.fd}
\alias{stddev.fd}
\title{
Standard Deviation of Functional Data
}
\description{
Evaluate the standard deviation of a set of functions in a functional
data object.
}
\usage{
sd.fd(fdobj)
std.fd(fdobj)
stdev.fd(fdobj)
stddev.fd(fdobj)
}
\arguments{
\item{fdobj}{
a functional data object.
}
}
\details{
The multiple aliases are provided for compatibility with previous
versions and with other languages. The name for the standard
deviation function in R is 'sd'. Matlab uses 'std'. S-Plus and
Microsoft Excal use 'stdev'. 'stddev' was used in a previous version
of the 'fda' package and is retained for compatibility.
}
\value{
a functional data object with a single replication
that contains the standard deviation of the one or several functions in
the object \code{fdobj}.
}
\seealso{
\code{\link{mean.fd}},
\code{\link{sum.fd}},
\code{\link{center.fd}}
}
\examples{
liptime <- seq(0,1,.02)
liprange <- c(0,1)
# ------------- create the fd object -----------------
# use 31 order 6 splines so we can look at acceleration
nbasis <- 51
norder <- 6
lipbasis <- create.bspline.basis(liprange, nbasis, norder)
lipbasis <- create.bspline.basis(liprange, nbasis, norder)
# ------------ apply some light smoothing to this object -------
Lfdobj <- int2Lfd(4)
lambda <- 1e-12
lipfdPar <- fdPar(lipbasis, Lfdobj, lambda)
lipfd <- smooth.basis(liptime, lip, lipfdPar)$fd
names(lipfd$fdnames) = c("Normalized time", "Replications", "mm")
lipstdfd <- sd.fd(lipfd)
plot(lipstdfd)
all.equal(lipstdfd, std.fd(lipfd))
all.equal(lipstdfd, stdev.fd(lipfd))
all.equal(lipstdfd, stddev.fd(lipfd))
}
% docclass is function
\keyword{smooth}