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voiage.methods.adaptive.bayesian_adaptive_trial_simulator

bayesian_adaptive_trial_simulator

Section titled “bayesian_adaptive_trial_simulator”
bayesian_adaptive_trial_simulator([positional or keyword] psa_samples: PSASample = None, [positional or keyword] base_design: TrialDesign = None, [positional or keyword] adaptive_rules: dict[str, object] = None, [positional or keyword] true_parameters: dict[str, float] | None = None) -> NetBenefitArray

Simulate a Bayesian adaptive trial with belief updating.

Parameters

Section titled “Parameters”

psa_samples : ParameterSet PSA samples representing parameter uncertainty. base_design : TrialDesign Trial design before adaptive modifications. adaptive_rules : dict[str, object] Rules describing interim analyses and early stopping behavior. true_parameters : dict[str, float], optional Optional true parameter values used to generate the simulated trial.

Returns

Section titled “Returns”

ValueArray Net-benefit samples after Bayesian updating.

Notes

Section titled “Notes”

The implementation is a testing-oriented approximation of a Bayesian adaptive design rather than a fully general trial simulator.

Parameters:

  • psa_samples PSASample
  • base_design TrialDesign
  • adaptive_rules dict[str, object]
  • true_parameters dict[str, float] | None (default: None)

Returns: NetBenefitArray