Man pages for MatheMax/OptReSample
Computing Optimal Adaptive Designs
| b | A simplified version of the function b that is defined in the... |
| c2 | Computing optimal c_2-values |
| c_early | Optimal Stopping Boundaries |
| cond_power | Computing conditional power |
| cond_power_design | Defines design based on conditional power |
| d_ce | d Score / d c_e |
| d_cf | d Score / d c_f |
| design | Creating design objects |
| direct_design | Find the optimal design via direct optimization |
| direct_design_smooth | Compute smooth designs via the direct method |
| dr_design | Compute designs for delayed response situation |
| err | Evaluate the deviation of the desired error constraints |
| exp_n | Computing the expected sample size for an effect size |
| find_lambda | Find the correct values of lambda |
| find_lambda_direct | Find lambda values faster |
| fixed | Compute the fixed design |
| hello | Hello, World! |
| inverse_normal_design | Compute optimal sample size based on inverse normal method |
| jt_design | Compute the design by Jennison and Turnbull (2015) |
| lagrange_design | Find the optimal Lagrangian design |
| lagrange_dr_design | Optimal design in delayed response situation |
| lambda_start | Starting values for lambda |
| n1 | Find the optimal stage one sample size |
| n2 | Compute n_2 function |
| nodes | Define equi distance nodes |
| omega | Define weights for Milne integration |
| opt_alpha | Compute the type I error rate of a design |
| optimal_design | Compute an optimal adaptive design |
| optimal_gsd | Compute the optimal group sequential design |
| optimal_inverse_normal_design | Compute the optimal design based on the inverse normal... |
| opt_power | Compute the power of a design |
| parameters | Creating parameters object |
| plot_c2 | Plot the c2-function |
| plot_cond_power | Plotting conditional power |
| plot_exp_n | Plotting expected sample size |
| plot_n | Plotting total sample size |
| plot_n2 | Plot the n2 function |
| plot_power | Plot power dependent on true effect |
| real_power | Computing the conditional power for differnt true effect... |
| response | Compute concrete n_2-value |
| score | Score in the Lagrangian framework |
| score_direct | Compute the score |
| score_direct_smooth | Score version for smooth direct designs |
| score_smooth | Smooth score version |
| stage_two | Compute optimal stage two values for given first stage |
| t_design | Find the optimal design when using a t-approximation |
| t_score | Version of the score when using t-approximation |
| t_type_one | Type one error when using t-approximation |
| t_type_two | Type two error when using t-approximation |
| type_one | Compute the type I error |
| type_one_smooth | Type I version for smooth direct designs |
| type_two | Compute the type II error |
| type_two_smooth | Type II version for smooth direct designs |
