forecast.StructTS

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Forecasting using Structural Time Series models

Returns forecasts and other information for univariate structural time series models.

Keywords
ts
Usage
## 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, ...)
Arguments
object
An object of class "StructTS". Usually the result of a call to StructTS.
h
Number of periods for forecasting
level
Confidence level for prediction intervals.
fan
If TRUE, level is set to seq(50,99,by=1). This is suitable for fan plots.
lambda
Box-Cox transformation parameter. Ignored if NULL. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation.
...
Other arguments.
Details

This function calls predict.StructTS and constructs an object of class "forecast" from the results.

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 forecast.StructTS.

    An object of class "forecast" is a list containing at least the following elements:

  • modelA list containing information about the fitted model
  • methodThe name of the forecasting method as a character string
  • meanPoint forecasts as a time series
  • lowerLower limits for prediction intervals
  • upperUpper limits for prediction intervals
  • levelThe confidence values associated with the prediction intervals
  • xThe original time series (either object itself or the time series used to create the model stored as object).
  • residualsResiduals from the fitted model. That is x minus fitted values.
  • fittedFitted values (one-step forecasts)

See Also

StructTS.

Aliases
  • forecast.StructTS
Examples
fit <- StructTS(WWWusage,"level")
plot(forecast(fit))
Documentation reproduced from package forecast, version 3.18, License: GPL (>= 2)

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