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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- pareto-gd Public
Pareto Improving GD. Only update when when doing so improves or maintains performance on all previously seen data.
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pyppur: Python Projection Pursuit Unsupervised (Dimension) Reduction To Min. Reconstruction Loss or DIstance DIstortion
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