| 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 |
| Gittins | Gittins Indices |
| pgreater_beta | Calculate the Futility Stopping Probability for Binary Endpoint with Beta Distribution |
| pgreater_NIX | Calculate the Futility Stopping Probability for Continuous Endpoint with Unknown Variances Using a Normal-Inverse-Chi-Squared Distribution |
| pgreater_normal | Calculate the Futility Stopping Probability for Continuous Endpoint with Known Variances Using Normal Distribution |
| pmax_beta | Posterior Probability that a Particular Arm is the Best for Binary Endpoint |
| pmax_NIX | Posterior Probability that a Particular Arm is the Best for Continuous Endpoint with Unknown Variances |
| pmax_normal | Posterior Probability that a Particular Arm is the Best for Continuous Endpoint with Known 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_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_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 |
| 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 |
| update_par_nichisq | Update Parameters of a Normal-Inverse-Chi-Squared Distribution with Available Data |