mlp.thief: MLP network for THieF.

In nnfor: Time Series Forecasting with Neural Networks

MLP network for THieF.

Description

Function for MLP forecasting with Temporal Hierarchies.

Usage

mlp.thief(y, h = NULL, ...)

Arguments

y	Input time series. Can be ts or msts object.
h	Forecast horizon. If NULL then h is set to match frequency of time series.
...	Additional arguments passed to mlp.

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 (either fit used to create the network.

• fitted - Fitted values. Any values not fitted for the initial period of the time series are imputted with NA.

• residuals - Residuals from the fitted network.

Note

This function is created to work with Temporal Hierarchied (thief package). For conventional MLP networks use mlp.

Author(s)

Nikolaos Kourentzes, [e-mail]

References

• For forecasting with temporal hierarchies see: Athanasopoulos G., Hyndman R.J., Kourentzes N., Petropoulos F. (2017) Forecasting with Temporal Hierarchies. European Journal of Operational research, 262(1), 60-74.

• For combination operators see: Kourentzes N., Barrow B.K., Crone S.F. (2014) Neural network ensemble operators for time series forecasting. Expert Systems with Applications, 41(9), 4235-4244.

See Also

mlp, elm.thief.

Examples

## Not run: 
  library(thief)
  frc <- thief(AirPassengers,forecastfunction=mlp.thief)
  plot(frc)

## End(Not run)

nnfor documentation built on Nov. 15, 2023, 1:09 a.m.