\name{drkpk}
\alias{sspdsty}
\alias{mspdsty}
\title{Numerical Engine for ssden}
\description{
    Calculate penalized likelihood density estimates via the Newton
    iteration and evaluate the cross-validation score, as implemented in
    the RATFOR routine \code{dnewton.r}, and minimize the
    cross-validation score using \code{\link{nlm}}.
}
\usage{
sspdsty(s,r,q,cnt,qd.s,qd.r,qd.wt,prec,maxiter,alpha)
mspdsty(s,r,q,cnt,qd.s,qd.r,qd.wt,prec,maxiter,alpha)
}
\details{
    \code{sspdsty} is used by \code{\link{ssden}} to compute
    cross-validated density estimate with a single smoothing
    parameter. \code{mspdsty} is used by \code{\link{ssden}} to compute
    cross-validated density estimate with a multiple smoothing
    parameters.
}
\arguments{
    \item{s}{Fixed effects evaluated at data points.}
    \item{r}{Basis of random effects evaluated at data points.}
    \item{q}{Penalty matrix.}
    \item{cnt}{Bin-counts for histogram data.}
    \item{qd.s}{Fixed effects evaluated at quadrature nodes.}
    \item{qd.r}{Basis of random effects evaluated at quadrature nodes.}
    \item{qd.wt}{Quadrature weights.}
    \item{prec}{Precision requirement for internal iterations.}
    \item{maxiter}{Maximum number of iterations allowed for
        internal iterations.}
    \item{alpha}{Parameter defining cross-validation score for smoothing
        parameter selection.}
}
\references{
    Gu, C. and Wang, J. (2002), \emph{Penalized Likelihood Density
    Estimation: Direct Cross-Validation and Scalable Approximation}.
    Available at \url{stat.purdue.edu/~chong/manu.html}.
}
\keyword{smooth}