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feat: Add Scaled CRPS as an accuracy metric #51
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sjmccorm1993
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Nov 18, 2025
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looks good, could you just
- ensure the unit tests still run and add tests for CRPS specifically
- update
metrics.mdandtests.mdto document the new metric you've added?
sjmccorm1993
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Nov 25, 2025
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Continuous Ranked Probability Score (CRPS) is a proper scoring rule to evaluate the prediction of a probability distribution.
It rewards distributions that:
This implements a scaled version of CRPS in the mmm-eval alongside the existing accuracy metrics (MAPE, R2, etc.).
The scaling factor makes this a generalisation of MAPE, so the output value can be consistently compared against a threshold regardless of what kinds of values the data has.
Note
Introduces scaled CRPS accuracy metric and plumbs posterior predictive distributions from adapters into validation to compute it, with docs, thresholds, tests, and version updated.
CRPScomputation (crps_one_date,calculate_crps) and include inAccuracyMetricNames/ResultsandCrossValidationMetricNames/Results(mean_crps).CRPS/MEAN_CRPS.BaseAdapterpredict/fit_and_predict/fit_and_predict_in_sampleto return(posterior_mean, posterior_distribution).predict_posterior(combined=True); return mean and distribution (transposed) tuples.CRPS.distribution_to_dataframeutility to reshape distributions for metric calc.0.13.0; updateCHANGELOG.md.Written by Cursor Bugbot for commit 9058b5a. This will update automatically on new commits. Configure here.