v1.0 of the forecasting bundle of packages is now on CRAN and will
propagate to mirrors shortly.
The forecasting bundle of R packages provides new forecasting methods,
and graphical tools for displaying and analysing forecasts. It comprises
the following packages:
* forecast: Functions and methods for forecasting.
* fma: All data sets from Makridakis, Wheelwright and Hyndman
(1998) Forecasting: methods and applications, Wiley & Sons: New
York.
* Mcomp: All data from the M1 and M3 forecast competitions.
Key features:
* a "forecast" method and class which can be applied to Arima,
StructTS,
HoltWinters and other time series models. This is preferred to predict()
as it provides output in a consistent format (the "forecast" class)
that
can be used by other functions.
* automatic univariate time series forecasting based on exponential
smoothing state space models. This is much more general and flexible
than HoltWinters().
* automatic ARIMA forecasting based on minimizing the AIC or BIC.
* several new forecasting methods and time series graphics.
Some features of the forecast package were the subject of my talk at
UseR! in Vienna in June. Slides of the talk are at
http://www.robhyndman.info/talks/Hyndman_UseR.pdf
Anyone who has been using earlier versions of the packages from my web
pages should check out the list of changes at
http://www.robhyndman.info/Rlibrary/forecast/
__________________________________________________
Professor Rob J Hyndman
Department of Econometrics & Business Statistics,
Monash University, VIC 3800, Australia
http://www.robhyndman.info/
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