Forecasting using Structural Time Series models
Returns forecasts and other information for univariate structural time series models.
## S3 method for class 'StructTS' forecast( object, h = ifelse(object$coef["epsilon"] > 1e-10, 2 * object$xtsp[3], 10), level = c(80, 95), fan = FALSE, lambda = NULL, biasadj = NULL, ... )
object |
An object of class " |
h |
Number of periods for forecasting |
level |
Confidence level for prediction intervals. |
fan |
If TRUE, level is set to seq(51,99,by=3). This is suitable for fan plots. |
lambda |
Box-Cox transformation parameter. If |
biasadj |
Use adjusted back-transformed mean for Box-Cox transformations. If transformed data is used to produce forecasts and fitted values, a regular back transformation will result in median forecasts. If biasadj is TRUE, an adjustment will be made to produce mean forecasts and fitted values. |
... |
Other arguments. |
This function calls predict.StructTS and constructs an object of
class "forecast" from the results.
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 forecast.StructTS.
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
fit <- StructTS(WWWusage,"level") plot(forecast(fit))
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