\name{Fstat.fd}
\alias{Fstat.fd}
\title{
F-statistic for functional linear regression.
}
\description{
Fstat.fd calculates a pointwise F-statistic for functional linear regression.
}
\usage{ Fstat.fd(y,yhat,argvals=NULL)}
\arguments{
\item{y}{
the dependent variable object. It may be:
\itemize{
\item a vector if the dependent variable is scalar.
\item a functional data object if the dependent variable is functional.
}
}
\item{yhat}{
The predicted values corresponding to \code{y}. It must be of the same class.
}
\item{argvals}{
If \code{yfdPar} is a functional data object, the points at which to evaluate
the pointwise F-statistic.
}
}
\details{
An F-statistic is calculated as the ratio of residual variance to predicted
variance.
If \code{argvals} is not specified and \code{yfdPar} is a \code{fd} object,
it defaults to 101 equally-spaced points on the range of \code{yfdPar}.
}
\value{
A list with components
\item{F}{the calculated pointwise F-statistics.}
\item{argvals}{
argument values for evaluating the F-statistic if \code{yfdPar} is
a functional data object.
}
}
\source{
Ramsay, James O., and Silverman, Bernard W. (2006), \emph{Functional
Data Analysis, 2nd ed.}, Springer, New York.
}
\seealso{
\code{\link{fRegress}}
\code{\link{Fstat.fd}}
% \code{\link{tstat.fd}}
}
%\examples{}
\keyword{smooth}