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\name{cdssden}
\alias{cdssden}
\alias{cpssden}
\alias{cqssden}
\title{Evaluating Conditional PDF, CDF, and Quantiles of Smoothing
Spline Density Estimates}
\description{
Evaluate conditional pdf, cdf, and quantiles for smoothing spline
density estimates.
}
\usage{
cdssden(object, x, cond, int=NULL)
cpssden(object, q, cond)
cqssden(object, p, cond)
}
\arguments{
\item{object}{Object of class \code{"ssden"}.}
\item{x}{Data frame or vector of points on which conditional density
is to be evaluated.}
\item{cond}{One row data frame of conditioning variables.}
\item{int}{Normalizing constant.}
\item{q}{Vector of points on which conditional cdf is to be
evaluated.}
\item{p}{Vector of probabilities for which conditional quantiles are
to be calculated.}
}
\value{
\code{cdssden} returns a list object with the following components.
\item{pdf}{Vector of conditional pdf.}
\item{int}{Normalizing constant.}
\code{cpssden} and \code{cqssden} return a vector of conditional cdf
or quantiles.
}
\details{
The argument \code{x} in \code{cdssden} is of the same form as the
argument \code{newdata} in \code{\link{predict.lm}}, but can take a
vector for 1-D conditional densities.
\code{cpssden} and \code{cqssden} naturally only work for 1-D
conditional densities of a numerical variable.
}
\note{
If variables other than factors or numerical vectors are involved in
\code{x}, the normalizing constant can not be computed.
}
\seealso{
Fitting function \code{\link{ssden}} and \code{\link{dssden}}.
}
\keyword{models}
\keyword{distribution}
\keyword{smooth}
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