nnfor (version 0.9.9)

forecast.mlp: Forecast using MLP neural network.

Description

Create forecasts using MLP neural networks.

Usage

# S3 method for mlp
forecast(object, h = NULL, y = NULL, xreg = NULL, ...)

Value

An object of classes "forecast.net" and "forecast". The function plot produces a plot of the forecasts. An object of class "forecast.net" is a list containing the following elements:

• method - The name of the forecasting method as a character string.

• mean - Point forecasts as a time series.

• all.mean - An array h x reps of all ensemble members forecasts, where reps are the number of ensemble members.

• x - The original time series used to create the network.

• fitted - Fitted values.

• residuals - Residuals from the fitted network.

Arguments

object

MLP network object, produced using mlp.

h

Forecast horizon. If NULL then h is set to match frequency of time series.

y

Optionally forecast using different data than what the network was trained on. Expected to create havoc and do really bad things!

xreg

Exogenous regressors. Each column is a different regressor and the sample size must be at least as long as the target in-sample set plus the forecast horizon, but can be longer. Set it to NULL if no xreg inputs are used.

...

Unused argument.

Author

Nikolaos Kourentzes,

See Also

mlp, mlp.thief, elm.

Examples

# \dontshow{
 fit <- mlp(AirPassengers,reps=1)
 frc <- forecast(fit,h=36)
 print(frc)
 plot(frc)
# }
if (FALSE) {
 fit <- mlp(AirPassengers)
 plot(fit)
 frc <- forecast(fit,h=36)
 plot(frc)
}