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\name{summary.ssanova}
\alias{summary.ssanova}
\alias{summary.ssanova0}
\alias{summary.ssanova9}
\title{Assessing Smoothing Spline ANOVA Fits}
\description{
Calculate various summaries of smoothing spline ANOVA fits.
}
\usage{
\method{summary}{ssanova}(object, diagnostics=FALSE, ...)
\method{summary}{ssanova0}(object, diagnostics=FALSE, ...)
\method{summary}{ssanova9}(object, diagnostics=FALSE, ...)
}
\arguments{
\item{object}{Object of class \code{"ssanova"}.}
\item{diagnostics}{Flag indicating if diagnostics are required.}
\item{...}{Ignored.}
}
\value{
\code{summary.ssanova} returns a list object of \code{\link{class}}
\code{"summary.ssanova"} consisting of the following components.
The entries \code{pi}, \code{kappa}, \code{cosines}, and
\code{roughness} are only calculated if \code{diagnostics=TRUE}; see
the reference below for details concerning the diagnostics.
\item{call}{Fitting call.}
\item{method}{Method for smoothing parameter selection.}
\item{fitted}{Fitted values.}
\item{residuals}{Residuals.}
\item{sigma}{Assumed or estimated error standard deviation.}
\item{r.squared}{Fraction of "explained variance" by the fitted model.}
\item{rss}{Residual sum of squares.}
\item{penalty}{Roughness penalty associated with the fit.}
\item{pi}{"Percentage decomposition" of "explained variance" into
model terms.}
\item{kappa}{Concurvity diagnostics for model terms. Virtually the
square roots of variance inflation factors of a retrospective
linear model.}
\item{cosines}{Cosine diagnostics for practical significance of
model terms.}
\item{roughness}{Percentage decomposition of the roughness penalty
\code{penalty} into model terms.}
}
\author{Chong Gu, \email{chong@stat.purdue.edu}}
\references{
Gu, C. (1992), Diagnostics for nonparametric regression models with
additive terms. \emph{Journal of the American Statistical
Association}, \bold{87}, 1051--1058.
}
\seealso{
Fitting functions \code{\link{ssanova}}, \code{\link{ssanova0}} and
methods \code{\link{predict.ssanova}},
\code{\link{project.ssanova}}, \code{\link{fitted.ssanova}}.
}
\keyword{models}
\keyword{regression}
\keyword{smooth}
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