\Header{predict.HoltWinters}{prediction function for fitted Holt-Winters models}
\keyword{ts}{predict.HoltWinters}
\begin{Description}\relax
Computes predictions and prediction intervals for models fitted by
the Holt-Winters method.\end{Description}
\begin{Usage}
\begin{verbatim}
predict(object, n.ahead=1, prediction.interval = FALSE,
                    quantile = qnorm(0.975), ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{object}] An object of class \code{HoltWinters}
\item[\code{n.ahead}] Number of future periods to predict
\item[\code{prediction.interval}] logical. If \code{TRUE}, the lower and
upper bounds of the corresponding prediction intervals are computed
\item[\code{quantile}] Quantile used for each one-sided prediction interval
(default: the 0.975 quantile to give a two-sided 0.95 interval)
\item[\code{...}] arguments passed to or from other methods.
\end{ldescription}
\end{Arguments}
\begin{Value}
A time series of the predicted values. If prediction intervals are
requested, a multiple time series is returned with columns \code{fit},
\code{lwr} and \code{upr} for the predicted values and the lower and
upper bounds respectively.\end{Value}
\begin{Author}\relax
David Meyer \email{david.meyer@ci.tuwien.ac.at}\end{Author}
\begin{References}\relax
C.C Holt (1957)
Forecasting seasonals and trends by exponentially weighted
moving averages,
ONR Research Memorandum, Carnigie Institute 52.

P.R Winters (1960)
Forecasting sales by exponentially weighted moving averages,
\emph{Management Science} \bold{6}, 324--342.\end{References}
\begin{SeeAlso}\relax
\code{\Link{HoltWinters}}\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(co2)
m <- HoltWinters(co2)
p <- predict(m, 50, prediction.interval = TRUE)
plot(m, p)
\end{ExampleCode}
\end{Examples}

