Returns forecasts and other information for user-defined models.

## 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`

## 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

## 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.