forecast: forecast.modelAR – R documentation

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forecast

forecast.modelAR

Forecasting using user-defined model

Description

Returns forecasts and other information for user-defined models.

Usage

## S3 method for class 'modelAR'
forecast(
  object,
  h = ifelse(object$m > 1, 2 * object$m, 10),
  PI = FALSE,
  level = c(80, 95),
  fan = FALSE,
  xreg = NULL,
  lambda = object$lambda,
  bootstrap = FALSE,
  npaths = 1000,
  innov = NULL,
  ...
)

Arguments

`object`	An object of class "`modelAR`" resulting from a call to `modelAR`.
`h`	Number of periods for forecasting. If `xreg` is used, `h` is ignored and the number of forecast periods is set to the number of rows of `xreg`.
`PI`	If TRUE, prediction intervals are produced, otherwise only point forecasts are calculated. If `PI` is FALSE, then `level`, `fan`, `bootstrap` and `npaths` are all ignored.
`level`	Confidence level for prediction intervals.
`fan`	If `TRUE`, level is set to `seq(51,99,by=3)`. This is suitable for fan plots.
`xreg`	Future values of external regressor variables.
`lambda`	Box-Cox transformation parameter. If `lambda="auto"`, then a transformation is automatically selected using `BoxCox.lambda`. The transformation is ignored if NULL. Otherwise, data transformed before model is estimated.
`bootstrap`	If `TRUE`, then prediction intervals computed using simulations with resampled residuals rather than normally distributed errors. Ignored if `innov` is not `NULL`.
`npaths`	Number of sample paths used in computing simulated prediction intervals.
`innov`	Values to use as innovations for prediction intervals. Must be a matrix with `h` rows and `npaths` columns (vectors are coerced into a matrix). If present, `bootstrap` is ignored.
`...`	Additional arguments passed to `simulate.nnetar`

Details

Prediction intervals are calculated through simulations and can be slow. Note that if the model is too complex and overfits the data, the residuals can be arbitrarily small; if used for prediction interval calculations, they could lead to misleadingly small values.

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.nnetar.

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`).
`xreg`	The external regressors used in fitting (if given).
`residuals`	Residuals from the fitted model. That is x minus fitted values.
`fitted`	Fitted values (one-step forecasts)
`...`	Other arguments

Author(s)

Rob J Hyndman and Gabriel Caceres