Individual skill
statsmodels
Fits and diagnoses Python statistical models including OLS, GLM, discrete and mixed models, ARIMA and SARIMAX. Supports coefficient inference, marginal effects, model comparison and time series forecasting with explicit design and uncertainty checks. Used for econometrics and statistical modeling; for guided test selection with APA reporting, see statistical-analysis.
skills/statsmodels/SKILL.md
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SKILL.mdcore · 12,681 bytesSKILL.mdcore · 12,681 bytesSKILL.mdcore · 12,681 bytesSKILL.mdcore · 12,681 bytesreferences/discrete_choice.mddoc · 18,733 bytesreferences/glm.mddoc · 18,448 bytesreferences/linear_models.mddoc · 14,048 bytesreferences/model_selection.mddoc · 3,500 bytesreferences/modeling_capabilities.mddoc · 6,244 bytesreferences/quick_start_guide.mddoc · 4,850 bytesreferences/review.mddoc · 7,035 bytesreferences/stats_diagnostics.mddoc · 24,066 bytesreferences/time_series.mddoc · 21,839 bytes
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# Statsmodels: Statistical Modeling and Econometrics
## Overview
Statsmodels provides estimation, inference and diagnostics for regression, time series and econometric models. A successful fit establishes numerical execution; causal identification, calibrated uncertainty and model adequacy require a defensible study design and assumptions.
## Current Compatibility
Reviewed against statsmodels 0.15.0 (released August 27, 2026). Native checks used Python 3.13, NumPy 2.5.3, SciPy 1.18.1, pandas 3.0.6, matplotlib 3.11.2 and scikit-learn 1.9.1. Install in a dedicated environment:
```bash
uv pip install statsmodels==0.15.0 numpy==2.5.3 scipy==1.18.1 pandas==3.0.6 matplotlib==3.11.2 scikit-learn==1.9.1
```
