python-regression-statistics
CommunityRegression analysis and diagnostics in Python.
Authorjkitchin
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill covers regression analysis, diagnostics, and outlier detection in Python using statsmodels, scikit-learn, scipy, and PyOD, with ready-made workflows for inference and validation.
Core Features & Use Cases
- Statistical regression: OLS, GLM, time-series models with inference.
- ML regression: Ridge, Lasso, ElasticNet, cross-validation.
- Outlier detection: Multiple detectors (isolation forest, LOF, COPOD, ECOD) and ensembles.
Quick Start
Request an end-to-end regression workflow: fit an OLS model with confidence intervals, validate assumptions, and produce a diagnostic plot.
Dependency Matrix
Required Modules
statsmodelsscikit-learnscipypandasnumpypyodmatplotlib
Components
references
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: python-regression-statistics Download link: https://github.com/jkitchin/skillz/archive/main.zip#python-regression-statistics Please download this .zip file, extract it, and install it in the .claude/skills/ directory.