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Statistical models library for Python. Use when you need specific model classes (OLS, GLM, mixed models, ARIMA) with detailed diagnostics, residuals, and…
Statsmodels: Statistical Modeling and Econometrics Overview Statsmodels is Python's premier library for statistical modeling, providing tools for estimation, inference, and diagnostics across a wide range of statistical methods. Apply this skill for rigorous statistical analysis, from simple linear regression to complex time series models and econometric analyses. When to Use This Skill This skill should be used when: Fitting regression models (OLS, WLS, GLS, quantile regression) Performing generalized linear modeling (logistic, Poisson, Gamma, etc.) Analyzing discrete outcomes (binary, multinomial, count, ordinal) Conducting time series analysis (ARIMA, SARIMAX, VAR, forecasting) Running statistical tests and diagnostics Testing model assumptions (heteroskedasticity, autocorrelation, normality) Detecting outliers and influential observations Comparing models (AIC/BIC, likelihood ratio tests) Estimating causal effects Producing publication-ready statistical tables and inference
don't have the plugin yet? install it then click "run inline in claude" again.