cv_error: Test and training error from model cross-validation
Description
cv_error computes the root mean squared error from a model fitted
to kfold cross-validated test-training-data. cv_compare
does the same, for multiple formulas at once (by calling cv_error
for each formula).
Usage
cv_error(data, formula, k = 5)
cv_compare(data, formulas, k = 5)
Arguments
data
A data frame.
formula
The formula to fit the linear model for the test and training data.
k
The number of folds for the kfold-crossvalidation.
formulas
A list of formulas, to fit linear models for the test and training data.
Value
A tibble with the root mean squared errors for the training and test data.
Details
cv_error first generates cross-validated test-training pairs, using
crossv_kfold and then fits a linear model, which
is described in formula, to the training data. Then, predictions
for the test data are computed, based on the trained models.
The training error is the mean value of the rmse for
all trained models; the test error is the rmse based on all
residuals from the test data.