beta_corrected_density
                        Density Plot of Beta Corrections for a Variable
beta_corrected_scatter
                        Scatter Plot of Beta Corrections for a Variable
beta_corrections_derive
                        Compute Beta Corrections based on SHAP values
bias_density            Density Plot of Bias Corrections from SHAP
                        values
check_iblm_model        Check Object of Class 'iblm'
correction_corridor     Plot GLM vs IBLM Predictions with Different
                        Corridors
create_beta_corrected_density
                        Create Pre-Configured Beta Corrected Density
                        Plot Function
create_beta_corrected_scatter
                        Create Pre-Configured Beta Corrected Scatter
                        Plot Function
create_bias_density     Create Pre-Configured Bias Density Plot
                        Function
create_overall_correction
                        Create Pre-Configured Overall Correction Plot
                        Function
data_beta_coeff_booster
                        Obtain Booster Model Beta Corrections for
                        tabular data
data_beta_coeff_glm     Obtain GLM Beta Coefficients for tabular data
data_to_onehot          Convert Data Frame to Wide One-Hot Encoded
                        Format
explain_iblm            Explain GLM Model Predictions Using SHAP Values
extract_booster_shap    Extract SHAP values from an xgboost Booster
                        model
freMTPLmini             French Motor Insurance Claims Dataset
get_pinball_scores      Calculate Pinball Scores for IBLM and
                        Additional Models
load_freMTPL2freq       Load French Motor Third-Party Liability
                        Frequency Dataset
overall_correction      Plot Overall Corrections from Booster Component
predict.iblm            Predict Method for IBLM
shap_to_onehot          Convert Shap values to Wide One-Hot Encoded
                        Format
split_into_train_validate_test
                        Split Dataframe into: 'train', 'validate',
                        'test'
theme_iblm              Custom ggplot2 Theme for IBLM
train_iblm_xgb          Train IBLM Model on XGBoost
train_xgb_as_per_iblm   Train XGBoost Model Using the IBLM Model
                        Parameters
