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voiage.methods.calibration.sophisticated_calibration_modeler

sophisticated_calibration_modeler([positional or keyword] psa_samples: PSASample = None, [positional or keyword] study_design: dict[str, object] = None, [positional or keyword] process_spec: dict[str, object] = None) -> NetBenefitArray

Run the built-in calibration study modeler.

psa_samples : ParameterSet Prior parameter samples. study_design : dict[str, object] Calibration study design specification. process_spec : dict[str, object] Calibration process specification.

ValueArray Net-benefit samples for the strategies under the calibrated model.

The built-in modeler is a testing-oriented approximation that simulates the effect of calibration by shrinking uncertainty toward target values.

Parameters:

  • psa_samples PSASample
  • study_design dict[str, object]
  • process_spec dict[str, object]

Returns: NetBenefitArray