comb_GLMNET: GLMNET Regression Forecast Combination

In Techtonique/ahead: Time Series Forecasting with uncertainty quantification

GLMNET Regression Forecast Combination

Description

Computes forecast combination weights using GLMNET Regression (OLS) regression.

Usage

comb_GLMNET(x, custom_error = NULL)

Arguments

x	An object of class 'foreccomb'. Contains training set (actual values + matrix of model forecasts) and optionally a test set.

Details

The function integrates the GLMNET Regression forecast combination implementation of the ForecastCombinations package into ForecastComb.

The results are stored in an object of class 'ForecastComb::foreccomb_res', for which separate plot and summary functions are provided.

Value

Returns an object of class ForecastComb::foreccomb_res with the following components:

Method	Returns the best-fit forecast combination method.
Models	Returns the individual input models that were used for the forecast combinations.
Weights	Returns the combination weights obtained by applying the combination method to the training set.
Intercept	Returns the intercept of the linear regression.
Fitted	Returns the fitted values of the combination method for the training set.
Accuracy_Train	Returns range of summary measures of the forecast accuracy for the training set.
Forecasts_Test	Returns forecasts produced by the combination method for the test set. Only returned if input included a forecast matrix for the test set.
Accuracy_Test	Returns range of summary measures of the forecast accuracy for the test set. Only returned if input included a forecast matrix and a vector of actual values for the test set.
Input_Data	Returns the data forwarded to the method.

See Also

Forecast_comb, foreccomb, plot.ForecastComb::foreccomb_res, summary.ForecastComb::foreccomb_res, accuracy

Examples

library(ForecastComb)

data(electricity)

print(head(electricity))

forecasting_methods <- colnames(electricity)[1:5]

train_obs <- electricity[1:84, "Actual"]
train_pred <- electricity[1:84, forecasting_methods]
test_obs <- electricity[85:123, "Actual"]
test_pred <- electricity[85:123, forecasting_methods]
data <- ForecastComb::foreccomb(train_obs, train_pred, test_obs, test_pred)

# obj <- ahead::comb_GLMNET(data))

Techtonique/ahead documentation built on Nov. 24, 2024, 10:33 a.m.