model_score(varest, criterion, logtransformed)
varest
model.'AIC'
or 'BIC'
.TRUE
or FALSE
, indicating whether the input data for the model has been logtransformed.This function returns the model fit for the given model as either an AIC or BIC score. We compensating for logtransformation so that the model scores of logtransformed and non-logtransformed models can be compared with each other directly. This compensation is implemented by subtracting the logtransformed data from the log-likelihood score and using the result as log-likelihood score for the AIC/BIC calculations.
data_matrix <- matrix(nrow = 40, ncol = 3) data_matrix[, ] <- runif(ncol(data_matrix) * nrow(data_matrix), 1, nrow(data_matrix)) colnames(data_matrix) <- c('rumination', 'happiness', 'activity') varest <- autovarCore:::run_var(data_matrix, NULL, 1) autovarCore:::model_score(varest, 'AIC', FALSE)[1] 918.9129