GLMNET Regression Forecast Combination

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

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.
custom_error: Custom error function

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.

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.