ica.elm_forecast: Forecasting from ICA based ELM model

In ICompELM: Independent Component Analysis Based Extreme Learning Machine

Forecasting from ICA based ELM model

Description

Forecasts are generated recursively from a trained Extreme Learning Machine built using Independent Component Analysis.

Usage

ica.elm_forecast(ica.elm_model, h = 1)

Arguments

ica.elm_model	A trained ICA based ELM model.
h	Number of periods for forecasting. Defaults to one-step ahead forecast.

Value

Vector of point forecasts.

See Also

ica.elm_train() for training an ICA based ELM model.

Examples

train_set <- head(price, 12*12)
test_set <- tail(price, 12)
ica.model <- ica.elm_train(train_data = train_set, lags = 12)
y_hat <- ica.elm_forecast(ica.elm_model = ica.model, h = length(test_set))
# Evaluation of the forecasts
if(require("forecast")) forecast::accuracy(y_hat, test_set)

ICompELM documentation built on June 22, 2024, 11:57 a.m.