forecast (version 3.03)

ses: Exponential smoothing forecasts

Description

Returns forecasts and other information for exponential smoothing forecasts applied to x.

Usage

ses(x, h=10, level=c(80,95), fan=FALSE, ...)
holt(x, h=10, damped=FALSE, level=c(80,95), fan=FALSE, ...)
hw(x, h=2*frequency(x), seasonal="additive", damped=FALSE, 
   level=c(80,95), fan=FALSE, ...)

Arguments

x

a numeric vector or time series

h

Number of periods for forecasting.

damped

If TRUE, use a damped trend.

seasonal

Type of seasonality in hw model. "additive" or "multiplicative"

level

Confidence level for prediction intervals.

fan

If TRUE, level is set to seq(50,99,by=1). This is suitable for fan plots.

...

Other arguments passed to ets.

Value

• An object of class "forecast". The function summary is used to obtain and print a summary of the results, while the function plot produces a plot of the forecasts and prediction intervals. The generic accessor functions fitted.values and residuals extract useful features of the value returned by ets and associated functions. An object of class "forecast" is a list containing at least the following elements:
• model
  A list containing information about the fitted model
• method
  The name of the forecasting method as a character string
• mean
  Point forecasts as a time series
• lower
  Lower limits for prediction intervals
• upper
  Upper limits for prediction intervals
• level
  The confidence values associated with the prediction intervals
• x
  The original time series (either object itself or the time series used to create the model stored as object).
• residuals
  Residuals from the fitted model. That is x minus fitted values.
• fitted
  Fitted values (one-step forecasts)

Details

ses, holt and hw are simply convenient wrapper functions for forecast(ets(...)).

References

Hyndman, R.J., Koehler, A.B., Snyder, R.D., Grose, S. (2002) "A state space framework for automatic forecasting using exponential smoothing methods", International J. Forecasting, 18(3), 439--454. Hyndman, R.J., Akram, Md., and Archibald, B. (2008) "The admissible parameter space for exponential smoothing models". Annals of Statistical Mathematics, 60(2), 407--426.

See Also

ets, HoltWinters, rwf, arima.

Examples

fcast <- holt(airmiles)
plot(fcast)
deaths.fcast <- hw(USAccDeaths,h=48)
plot(deaths.fcast)