Skip to content

Governed Predictive Model Comparison

Python-facing port of governed-pupil-model-comparison.Rmd from the frozen R gp3bayes 0.5.0 reference. The statistical and governance framing below follows the canonical vignette; executable Python workflows use the mapped APIs listed later.

The sensitivity suite is a pre-fit registry of alternatives. It does not fit or rank models.

Weights are returned only as explicit evidence. gp3bayes does not automatically average predictions or declare the highest-weight model substantively correct.

Leave-future-out is an explicit refit workflow

Python API mapping

  • gp3bayespy.compare_pupil_models
  • gp3bayespy.create_pupil_advanced_sensitivity_suite
  • gp3bayespy.create_pupil_lfo_plan
  • gp3bayespy.create_pupil_model_set
  • gp3bayespy.fit_advanced_pupil_model_backend
  • gp3bayespy.materialize_pupil_advanced_sensitivity_scenario
  • gp3bayespy.plot_pupil_lfo
  • gp3bayespy.plot_pupil_model_comparison
  • gp3bayespy.pupil_model_comparison_table
  • gp3bayespy.pupil_model_weights
  • gp3bayespy.simulate_advanced_pupil_timecourse
  • gp3bayespy.specify_advanced_pupil_timecourse_model
  • gp3bayespy.validate_pupil_leave_future_out

Python usage

import gp3bayespy as gp

# All functions listed above are available from the package root.
# Use help(gp.<function>) or the API reference for the exact Python signature.

An executable workflow for this family is included in ../../examples/pupil_workflow.py.