https://github.com/cran/cobs
Tip revision: 4719166ac96865c6f3b3511be87177f70b244656 authored by Martin Maechler on 11 August 2010, 00:00:00 UTC
version 1.2-1
version 1.2-1
Tip revision: 4719166
predict.cobs.Rd
\name{predict.cobs}
\alias{predict.cobs}
\title{Predict method for COBS Fits}
\description{
Compute predicted values and simultaneous or pointwise confidence
bounds for \code{\link{cobs}} objects.
}
\usage{
\method{predict}{cobs}(object,
z, minz = knots[1], maxz = knots[nknots], nz = 100,
interval = c("none", "confidence", "simultaneous", "both"),
level = 0.95, \dots)
}
\arguments{
\item{object}{object of class \code{cobs}.}
\item{z}{vector of grid points at which the fitted values are
evaluated; defaults to an equally spaced grid with \code{nz} grid
points between \code{minz} and \code{maxz}. Note that now \code{z}
may lie outside of the knots interval which was not allowed originally.}
\item{minz}{numeric needed if \code{z} is not specified; defaults to
\code{min(x)} or the first knot if \code{knots} are given.}
\item{maxz}{analogous to \code{minz}; defaults to \code{max(x)} or the
last knot if \code{knots} are given.}
\item{nz}{number of grid points in \code{z} if that is not given;
defaults to 100.}
\item{interval}{type of interval calculation, see below}
\item{level}{confidence level}
\item{\dots}{further arguments passed to and from methods.}
}
% \details{
% }
\value{
a matrix of predictions and bounds if \code{interval} is set (not
"none"). The columns are named \code{z}, \code{fit}, further
\code{cb.lo} and \code{cb.up} for the \code{simultaneous} confidence
band, and \code{ci.lo} and \code{ci.up} the pointwise
\code{confidence} intervals according to specified \code{level}.
If \code{z} has been specified, it is unchanged in the result.
}
\author{Martin Maechler, based on He and Ng's code in \code{cobs()}.}
\seealso{\code{\link{cobs}} the model fitting function.}
\examples{
example(cobs) # continuing :
(pRbs <- predict(Rbs))
#str(pSbs <- predict(Sbs, xx, interval = "both"))
str(pSbs <- predict(Sbs, xx, interval = "none"))
plot(x,y, xlim = range(xx), ylim = range(y, pSbs[,2], finite = TRUE),
main = "COBS Median smoothing spline, automatical lambda")
lines(pSbs, col = "red")
lines(spline(x,f.true), col = "gray40")
#matlines(pSbs[,1], pSbs[,-(1:2)],
# col= rep(c("green","blue"),c(2,2)), lty=2)
}
\keyword{regression}