CVFolds                 CVFolds (from SuperLearner package)
FW                      Frank-Wolfe algorithm
HX                      Compute the Inverse Propensity Score Weight
                        (IPW)
Lagrangian_p            Objective function taking the form of a
                        Lagrangian
Optimization_Estimation
                        Iterative optimization procedure
R_p                     Risk function for Conditional Average Treatment
                        Effect (CATE)
SGD                     Stochastic Gradient Descent (SGD) algorithm
SL.grf                  SL.grf
S_p                     Constraint function
SuperLearner.CV.control
                        SuperLearner.CV.control (from SuperLearner
                        package)
V_Pn                    Estimation of policy value
V_p                     Oracular approximation of value function
binary_S_p              Constraint function for binary policy
check_data              Check input data for validity
delta_mu_constant       Constant Conditional Average Treatment Effect
                        estimator for Y
delta_mu_linear         Linear-shaped Conditional Average Treatment
                        Effect estimator for Y
delta_mu_mix            Mixed-shape Conditional Average Treatment
                        Effect estimator for Y
delta_mu_null           Null Conditional Average Treatment Effect
                        estimator for Y
delta_mu_realistic      Realistic Conditional Average Treatment Effect
                        estimator for Y
delta_mu_threshold      Thresholded-shaped Conditional Average
                        Treatment Effect estimator for Y
delta_nu_linear         Linear-shaped Conditional Average Treatment
                        Effect estimator for Xi
delta_nu_mix            Mixed-shaped Conditional Average Treatment
                        Effect estimator for Xi
delta_nu_realistic      Realistic Conditional Average Treatment Effect
                        estimator for Xi
delta_nu_satisfied      Computes the difference in expected outcomes
                        under treatment and control.
delta_nu_threshold      Thresholded Conditional Average Treatment
                        Effect estimator for Xi
estimate_mu             Estimate mu
estimate_nu             Estimate nu
estimate_ps             Estimate propensity score
estimate_real_valued_mu
                        Estimate real-valued mu
generate_data           Synthetic data generator and functions
                        generator
generate_realistic_data
                        Realistic synthetic data generator and
                        functions generator
get_opt_beta_lambda     Select Optimal Beta and Lambda Combination
grad_Lagrangian_p       Gradient of the objective function
learn_threshold         Learn Optimal Decision Threshold
lwr_upper_bound_estimators
                        Lower and upper bound estimators for policy
                        value and constraint
main_algorithm          Main algorithm
make_psi                Generate psi function
model_Xi_linear         Linear treatment effect on Xi Component
                        Function
model_Xi_mix            Mixed treatment effect on Xi component function
model_Xi_realistic      Realistic treatment effect on Xi Component
                        Function
model_Xi_satisfied      Low treatment effect on Xi
model_Xi_threshold      Thresholded treatment effect on Xi component
                        function
model_Y_constant        Constant treatment effect on Y component
                        function
model_Y_linear          Linear treatment effect on Y component function
model_Y_mix             Mixed treatment effect on Y component function
model_Y_null            No treatment effect on Y component function
model_Y_realistic       Realistic treatment effect on Y component
                        function
model_Y_threshold       Thresholded treatment effect on Y component
                        function
naive_approach_algorithm
                        Naive approach main algorithm
oracular_approach_algorithm
                        Oracular approach main algorithm
oracular_process_results
                        Oracular evaluation of a policy
phi                     Normalize a Matrix by Column Min-Max Scaling
phi_inv                 Inverse Min-Max Normalization
plot_metric_comparison
                        Plot metric values for comparison
plot_realistic          Plot realistic data setting
predict.SL.grf          predict.SL.grf
process_results         Evaluate a policy
sigma_beta              Link function
sigma_beta_prime        Derivative of link function
synthetic_data_plot     Plot synthetic data setting
update_mu               Update mu via augmented covariate adjustment
update_mu_XA            Update mu via augmented covariate adjustment
                        for fixed X
update_nu               Update nu via augmented covariate adjustment
update_nu_XA            Update nu via augmented covariate adjustment
                        for fixed X
visual_treatment_plot   Visualize treatment assignment probability
