Man pages for adoptr
Adaptive Optimal Two-Stage Designs
| adoptr | Adaptive Optimal Two-Stage Designs |
| ANOVA-class | Analysis of Variance |
| AverageN2-class | Regularization via L1 norm |
| BinomialDataDistribution-class | Binomial data distribution |
| boundary-designs | Boundary designs |
| bounds | Get support of a prior or data distribution |
| ChiSquaredDataDistribution-class | Chi-Squared data distribution |
| composite | Score Composition |
| condition | Condition a prior on an interval |
| ConditionalPower-class | (Conditional) Power of a Design |
| ConditionalSampleSize-class | (Conditional) Sample Size of a Design |
| Constraints | Formulating Constraints |
| ContinuousPrior-class | Continuous univariate prior distributions |
| critical-values | Query critical values of a design |
| cumulative_distribution_function | Cumulative distribution function |
| DataDistribution-class | Data distributions |
| expectation | Expected value of a function |
| get_initial_design | Initial design |
| GroupSequentialDesign-class | Group-sequential two-stage designs |
| GroupSequentialDesignSurvival-class | Group-sequential two-stage designs for... |
| make_tunable | Fix parameters during optimization |
| MaximumSampleSize-class | Maximum Sample Size of a Design |
| minimize | Find optimal two-stage design by constraint minimization |
| n | Query sample size of a design |
| N1-class | Regularize n1 |
| NestedModels-class | F-Distribution |
| NormalDataDistribution-class | Normal data distribution |
| OneStageDesign-class | One-stage designs |
| OneStageDesignSurvival-class | One-stage designs for time-to-event endpoints |
| Pearson2xK-class | Pearson's chi-squared test for contingency tables |
| plot-TwoStageDesign-method | Plot 'TwoStageDesign' with optional set of conditional scores |
| PointMassPrior-class | Univariate discrete point mass priors |
| posterior | Compute posterior distribution |
| predictive_cdf | Predictive CDF |
| predictive_pdf | Predictive PDF |
| print.adoptrOptimizationResult | Printing an optimization result |
| Prior-class | Univariate prior on model parameter |
| probability_density_function | Probability density function |
| Scores | Scores |
| simulate-TwoStageDesign-numeric-method | Draw samples from a two-stage design |
| StudentDataDistribution-class | Student's t data distribution |
| subject_to | Create a collection of constraints |
| SurvivalDataDistribution-class | Log-rank test |
| SurvivalDesign | SurvivalDesign |
| tunable_parameters | Switch between numeric and S4 class representation of a... |
| TwoStageDesign-class | Two-stage designs |
| TwoStageDesignSurvival-class | Two-stage design for time-to-event-endpoints |
| ZSquared-class | Distribution class of a squared normal distribution |
