Posterior predictive diagnostics can retain uncertainty in entire outcome distributions as well as in predictive scores.
atlas <- create_predictive_distribution_atlas(
fit,
ndraws = 500,
include_group_effects = TRUE,
seed = 2026
)
plot_predictive_atlas_statistics(atlas)
quantiles <- predictive_quantile_envelope(atlas)
plot_predictive_quantile_envelope(quantiles)
scores <- prediction_score_uncertainty(
fit,
ndraws = 1000
)
prediction_score_uncertainty_table(scores)
plot_prediction_score_uncertainty(scores)For binary models:
calibration <- binary_calibration_uncertainty(
fit,
bins = 10,
ndraws = 1000
)
binary_calibration_uncertainty_table(calibration)
plot_binary_calibration_uncertainty(calibration)These summaries do not automatically establish calibration, predictive adequacy, or model superiority.
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