mrf_forecast: Multiresolution Forecast

In mrf: Multiresolution Forecasting

Multiresolution Forecast

Description

Creates a multiresolution forecast for a given multiresolution model based on [Stier et al., 2021] which is currently in press. (mrf_train).

Usage

mrf_forecast(Model, Horizon=1)

Arguments

Model	List containing model specifications from mrf_train().
Horizon	Number indicating horizon for forecast from 1 to horizon.

Value

List of

Forecast	[1:Horizon] Numerical vector with forecast of horizon according to its index.
Model	List containing model specifications from mrf_train().

Author(s)

Quirin Stier

References

[Stier et al., 2021] Stier, Q.,Gehlert, T. and Thrun, M. C.: Multiresolution Forecasting for Industrial Applications, Processess, 2021.

Examples

data(AirPassengers)
Data = as.vector(AirPassengers)
len_data = length(Data)
Train = Data[1:(len_data-2)]
Test = Data[(len_data-1):len_data]
# One-step forecast (Multiresolution Forecast)
model = mrf_train(Train)
one_step = mrf_forecast(model, Horizon=1)
Error = one_step$Forecast - Test[1]
# Multi-step forecast (Multiresolution Forecast)
# Horizon = 2 => Forecast with Horizon 1 and 2 as vector
model = mrf_train(Train, Horizon=2)
multi_step = mrf_forecast(model, Horizon=2)
Error = multi_step$Forecast - Test

mrf documentation built on March 18, 2022, 5:11 p.m.