Prediction Contrasts, Rankings, and Groups

Python-facing port of prediction-contrasts-ranking-and-groups.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.

Prediction grids can be summarised by observed design variables without expanding the approved model-family scope.

The ranking function is deliberately descriptive. A probability of rank one is not converted into an automatic selection.

When the prediction data contain multiple rows per substantive group:

This makes aggregation explicit and reproducible rather than hiding it inside plotting code.

Python API mapping

• gp3bayespy.create_prediction_grid
• gp3bayespy.group_prediction_summary
• gp3bayespy.plot_group_predictions
• gp3bayespy.predict_model
• gp3bayespy.prediction_interval_width
• gp3bayespy.prediction_pairwise_contrasts
• gp3bayespy.prediction_rank_probabilities

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/predictive_diagnostics.py.