| apply_acd | Function to apply Approximate Cumulative Distribution (ACD) | 
| apply_shift_scale | Shift and scale vector x | 
| art | Artificial dataset with continuous response | 
| assign_df | Helper to assign degrees of freedom | 
| backscale_matrix | Backscale Columns of a Matrix (Internal) | 
| calculate_df | Helper to calculates the final degrees of freedom for the selected model | 
| calculate_f_test | Function to compute F-statistic and p-value from deviances | 
| calculate_lr_test | Function to calculate p-values for likelihood-ratio test | 
| calculate_model_metrics | Function to compute model metrics to be used within 'mfp2' | 
| calculate_number_fp_powers | Calculates the total number of fractional polynomial powers in adjustment variables. | 
| calculate_standard_error | Helper function to compute standard error of a partial predictor | 
| center_matrix | Simple function to center data | 
| coef.mfp2 | Extract coefficients from object of class 'mfp2' | 
| convert_powers_list_to_matrix | Helper to convert a nested list with same or different length into a matrix | 
| create_dummy_variables | Simple function to create dummy variables for ordinal and nominal variables | 
| create_fp_terms | Helper to create overview table of fp terms | 
| deviance_gaussian | Deviance computations as used in mfp in stata | 
| ensure_length | Helper function to ensure vectors have a specified length | 
| find_best_fp1_for_acd | Function to fit univariable FP1 models for acd transformation | 
| find_best_fpm_step | Function to find the best FP functions of given degree for a single variable | 
| find_best_fp_cycle | Helper to run cycles of the mfp algorithm | 
| find_best_fp_step | Function to estimate the best FP functions for a single variable | 
| find_scale_factor | Function that calculates an integer used to scale predictor | 
| find_shift_factor | Function that calculates a value used to shift predictor | 
| fit_acd | Function to estimate approximate cumulative distribution (ACD) | 
| fit_cox | Function that fits Cox proportional hazards models | 
| fit_glm | Function that fits generalized linear models | 
| fit_linear_step | Function to fit linear model for variable of interest | 
| fit_mfp | Function for fitting a model using the MFP or MFPA algorithm | 
| fit_model | Function that fits models supported by 'mfp2' | 
| fit_null_step | Function to fit null model excluding variable of interest | 
| fp | Helper to assign attributes to a variable undergoing FP-transformation | 
| fp2 | Helper to assign attributes to a variable undergoing FP-transformation | 
| fracplot | Plot response functions from a fitted 'mfp2' object | 
| gbsg | Breast cancer dataset used in the Royston and Sauerbrei (2008) book. | 
| generate_combinations_with_replacement | Helper function to generate combinations with replacement | 
| generate_powers_acd | Function that generates a matrix of FP powers for any degree | 
| generate_powers_fp | Function that generates a matrix of FP powers for any degree | 
| generate_transformations_acd | Function to generate all requested FP transformations for a single variable | 
| generate_transformations_fp | Function to generate all requested FP transformations for a single variable | 
| get_selected_variable_names | Helper function to extract selected variables from fitted 'mfp2' object | 
| mfp2 | Multivariable Fractional Polynomial Models with Extensions | 
| mfp2.default | Multivariable Fractional Polynomial Models with Extensions | 
| mfp2.formula | Multivariable Fractional Polynomial Models with Extensions | 
| name_transformed_variables | Helper function to name transformed variables | 
| order_variables | Helper to order variables for mfp2 algorithm | 
| order_variables_by_significance | Helper to order variables for mfp2 algorithm | 
| pima | Pima Indians dataset used in the Royston and Sauerbrei (2008) book. | 
| plot_mfp | Plot response functions from a fitted 'mfp2' object | 
| predict.mfp2 | Predict Method for 'mfp2' | 
| prepare_newdata_for_predict | Helper function to prepare newdata for predict function | 
| print.mfp2 | Print method for objects of class 'mfp2' | 
| print_mfp_ic_step | Function for verbose printing of function selection procedure (FSP) | 
| print_mfp_pvalue_step | Function for verbose printing of function selection procedure (FSP) | 
| print_mfp_step | Function for verbose printing of function selection procedure (FSP) | 
| prostate | Prostate cancer dataset used in the Royston and Sauerbrei (2008) book. | 
| reset_acd | Helper to reset acd transformation for variables with few values | 
| select_ic | Function selection procedure based on information criteria | 
| select_ic_acd | Function selection procedure based on information criteria | 
| select_linear | Helper to select between null and linear term for a single variable | 
| select_ra2 | Function selection procedure based on closed testing procedure | 
| select_ra2_acd | Function selection procedure for ACD based on closed testing procedure | 
| summary.mfp2 | Summarizing 'mfp2' model fits | 
| transform_data_step | Function to extract and transform adjustment variables | 
| transform_matrix | Function to transform each column of matrix using final FP powers or acd | 
| transform_vector_acd | Functions to transform a variable using fractional polynomial powers or acd | 
| transform_vector_fp | Functions to transform a variable using fractional polynomial powers or acd | 
| transform_vector_power | Simple function to transform vector by a single power |