https://github.com/cran/gss
Tip revision: 9924457bfed29635cbc74e54959beb6a433c8123 authored by Chong Gu on 23 September 2004, 00:00:00 UTC
version 0.9-3
version 0.9-3
Tip revision: 9924457
rkpk.Rd
\name{rkpk}
\alias{sspreg}
\alias{mspreg}
\alias{getcrdr}
\alias{getsms}
\alias{sspregpoi}
\alias{mspregpoi}
\title{Interface to RKPACK}
\description{
Call RKPACK routines for numerical calculations for fitting and
predicting from Smoothing Spline ANOVA models.
}
\usage{
sspreg(s, q, y, method="v", varht=1)
mspreg(s, q, y, method="v", varht=1, prec=1e-7, maxiter=30)
sspregpoi(family, s, q, y, wt, offset, method="u",
varht=1, nu, prec=1e-7, maxiter=30)
mspregpoi(family, s, q, y, wt, offset, method="u",
varht=1, nu, prec=1e-7, maxiter=30)
getcrdr(obj, r)
getsms(obj)
}
\details{
\code{sspreg} is used by \code{\link{ssanova}} to fit Gaussian
models with a single smoothing parameter. \code{mspreg} is used to
fit Gaussian models with multiple single smoothing parameters.
\code{sspregpoi} is used by \code{\link{gssanova}} to fit non
Gaussian models with a single smoothing parameter. \code{mspregpoi}
is used to fit non Gaussian models with multiple single smoothing
parameters.
\code{getcrdr} and \code{getsms} are used by
\code{\link{predict.ssanova}} to calculate standard errors of the
fitted terms.
}
\arguments{
\item{s}{Design matrix of unpenalized terms.}
\item{q}{Penalty matrices of penalized terms.}
\item{y}{Model response.}
\item{method}{Method for smoothing parameter selection.}
\item{varht}{Assumed dispersion parameter, needed only for
\code{method="u"}.}
\item{prec}{Precision requirement for iterations.}
\item{maxiter}{Maximum number of iterations allowed.}
\item{family}{Error family.}
\item{wt}{Model weights.}
\item{offset}{Model offset.}
\item{obj}{Object returned from a call to \code{sspreg},
\code{mspreg}, \code{sspregpoi}, or \code{mspregpoi}.}
\item{nu}{Optional argument for nbinomial, weibull, lognorm, and
loglogis families.}
\item{r}{Inputs for standard error calculation.}
}
\references{
Gu, C. (1989), RKPACK and its applications: Fitting smoothing spline
models. In \emph{ASA Proceedings of Statistical Computing Section},
pp. 42--51.
}
\keyword{smooth}