Practical, well‑documented tooling for applied statistics and econometrics: deployable probability calibration, exact thresholding for stepwise metrics, stable trees, projection‑pursuit dimension reduction, nonparametric smoothing, and time‑series trend estimation. Several libraries are scikit‑learn compatible; others target R directly or expose R’s capabilities to AI assistants via MCP.
finite-sample
econometrics adjacent
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- stagecoachml Public
finite-sample/stagecoachml’s past year of commit activity - fewlab Public
Pick the fewest items to label for most efficient unbiased OLS regression on per‑row trait shares
finite-sample/fewlab’s past year of commit activity - pyppur Public
pyppur: Python Projection Pursuit Unsupervised (Dimension) Reduction To Min. Reconstruction Loss or DIstance DIstortion
finite-sample/pyppur’s past year of commit activity - optimal-classification-cutoffs Public
Script for calculating the optimal cut-off for max. F1-score, etc.
finite-sample/optimal-classification-cutoffs’s past year of commit activity
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