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About statsmodels
statsmodels
Fits and diagnoses Python statistical models including OLS, GLM
statsmodels is an agent skill for fitting and diagnosing statistical models in Python with the statsmodels library. It covers regression, time series and econometric models, including OLS, GLM, discrete and mixed models, ARIMA and SARIMAX. It also covers coefficient inference, marginal effects and model diagnostics. The skill is clear about what a fit shows. A successful fit establishes that the numerical procedure ran, but causal identification, calibrated uncertainty and model adequacy depend on a defensible study design and assumptions. The skill was reviewed against statsmodels 0.15.0, released on 27 August 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, in a dedicated environment. It recommends the stable high-level imports from statsmodels.api and statsmodels.formula.api, with direct module imports where newer or specialised classes are needed. In version 0.15, the skill advises using result_object=True with named fields for the ADF and KPSS tests, and rng= where older versions accepted seed or random_state.
- Price
- Free
- Made by
- k-dense-ai
- Category
- AI Skills
- Website
- github.com/k-dense-ai/scientific-agent-skills/statsmodels