| thetaf {forecast} | R Documentation |
Returns forecasts and prediction intervals for a theta method forecast.
thetaf(x, h=10, level=c(80,95), fan=FALSE)
x |
a numeric vector or time series |
h |
Number of periods for forecasting |
level |
Confidence levels for prediction intervals. |
fan |
If TRUE, level is set to seq(50,99,by=1). This is suitable for fan plots. |
The theta method of Assimakopoulos and Nikolopoulos (2000) is equivalent to simple exponential smoothing with drift. This is demonstrated in Hyndman and Billah (2003). Prediction intervals are computed using the underlying state space model.
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 rwf.
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 |
residuals |
Residuals from the fitted model. That is x minus fitted values. |
fitted |
Fitted values (one-step forecasts) |
Rob J Hyndman
Assimakopoulos, V. and Nikolopoulos, K. (2000). The theta model: a decomposition approach to forecasting. International Journal of Forecasting 16, 521-530.
Hyndman, R.J., and Billah, B. (2003) Unmasking the Theta method. International J. Forecasting, 19, 287-290.
nile.fcast <- thetaf(Nile) plot(nile.fcast)