Produce estimates of the calibration error.

Estimate calibration error using a 5-fold cross-validation. A 5-fold cross-validation was chosen as each calibration window should have at least 6 data points (e.g., if only daily validation data are used for the calibration) and therefore this ensures that the cross-validation should always run. Model is fit using lm and the caret package, with root-mean-square error (RMSE), the R-squared value, and mean-absolute error (MAE) extracted from the cross-validation.

Usage

estimate_calibration_error(formula, data)

Arguments

formula

Formula to pass to caret::train to perform cross validation.

data

Data frame to perform cross-validation on.

Author

Rich Fiorella rfiorella@lanl.gov