Gittins                 Gittins Indices
brar_select_au_binary   Select au in Bayesian Response-Adaptive
                        Randomization with a Control Group for Binary
                        Endpoint
brar_select_au_known_var
                        Select au in Bayesian Response-Adaptive
                        Randomization with a Control Group for
                        Continuous Endpoint with Known Variances
brar_select_au_unknown_var
                        Select au in Bayesian Response-Adaptive
                        Randomization with a Control Group for
                        Continuous Endpoint with Unknown Variances
convert_chisq_to_gamma
                        Convert parameters from a
                        Normal-Inverse-Chi-Squared Distribution to a
                        Normal-Inverse-Gamma Distribution
convert_gamma_to_chisq
                        Convert parameters from a Normal-Inverse-Gamma
                        Distribution to a Normal-Inverse-Chi-Squared
                        Distribution
dabcd_max_power         Allocation Probabilities Using Doubly Adaptive
                        Biased Coin Design with Maximal Power Strategy
                        for Binary Endpoint
dabcd_min_var           Allocation Probabilities Using Doubly Adaptive
                        Biased Coin Design with Minimal Variance
                        Strategy for Binary Endpoint
flgi_cut_off_binary     Cut-off Value of the Forward-looking Gittins
                        Index Rule in Binary Endpoint
flgi_cut_off_known_var
                        Cut-off Value of the Forward-looking Gittins
                        Index Rule in Continuous Endpoint with Known
                        Variances
flgi_cut_off_unknown_var
                        Cut-off Value of the Forward-looking Gittins
                        Index rule in Continuous Endpoint with Unknown
                        Variances
pgreater_NIX            Calculate the Futility Stopping Probability for
                        Continuous Endpoint with Unknown Variances
                        Using a Normal-Inverse-Chi-Squared Distribution
pgreater_beta           Calculate the Futility Stopping Probability for
                        Binary Endpoint with Beta Distribution
pgreater_normal         Calculate the Futility Stopping Probability for
                        Continuous Endpoint with Known Variances Using
                        Normal Distribution
pmax_NIX                Posterior Probability that a Particular Arm is
                        the Best for Continuous Endpoint with Unknown
                        Variances
pmax_beta               Posterior Probability that a Particular Arm is
                        the Best for Binary Endpoint
pmax_normal             Posterior Probability that a Particular Arm is
                        the Best for Continuous Endpoint with Known
                        Variances
sim_A_optimal_known_var
                        Simulate a Trial Using A-Optimal Allocation for
                        Continuous Endpoint with Known Variances
sim_A_optimal_unknown_var
                        Simulate a Trial Using A-Optimal Allocation for
                        Continuous Endpoint with Unknown Variances
sim_Aa_optimal_known_var
                        Simulate a Trial Using Aa-Optimal Allocation
                        for Continuous Endpoint with Known Variances
sim_Aa_optimal_unknown_var
                        Simulate a Trial Using Aa-Optimal Allocation
                        for Continuous Endpoint with Unknown Variances
sim_RPTW                Simulate a Trial Using Randomized
                        Play-the-Winner Rule for Binary Endpoint
sim_RSIHR_optimal_known_var
                        Simulate a Trial Using Generalized RSIHR
                        Allocation for Continuous Endpoint with Known
                        Variances
sim_RSIHR_optimal_unknown_var
                        Simulate a Trial Using Generalized RSIHR
                        Allocation for Continuous Endpoint with Unknown
                        Variances
sim_brar_binary         Simulate a Trial Using Bayesian
                        Response-Adaptive Randomization with a Control
                        Group for Binary Outcomes
sim_brar_known_var      Simulate a Trial Using Bayesian
                        Response-Adaptive Randomization with a Control
                        Group for Continuous Endpoint with Known
                        Variances
sim_brar_unknown_var    Simulate a Trial Using Bayesian
                        Response-Adaptive Randomization with a Control
                        Group for Continuous Endpoint with Unknown
                        Variances
sim_dabcd_max_power     Simulate a Trial Using Doubly Adaptive Biased
                        Coin Design with Maximal Power Strategy for
                        Binary Endpoint
sim_dabcd_min_var       Simulate a Trial Using Doubly Adaptive Biased
                        Coin Design with Minmial Variance Strategy for
                        Binary Endpoint
sim_flgi_binary         Simulate a Trial Using Forward-Looking Gittins
                        Index for Binary Endpoint
sim_flgi_known_var      Simulate a Trial Using Forward-Looking Gittins
                        Index for Continuous Endpoint with Known
                        Variances
sim_flgi_unknown_var    Simulate a Trial Using Forward-Looking Gittins
                        Index for Continuous Endpoint with Unknown
                        Variances
update_par_nichisq      Update Parameters of a
                        Normal-Inverse-Chi-Squared Distribution with
                        Available Data
