Fit OLS, GLM, ARIMA, and VAR models with statsmodels.
npx skills add https://github.com/Sologa/codex-pipeline --skill statsmodels-sologa
Please help me install this Agent Skill. Skill: statsmodels Source: https://github.com/Sologa/codex-pipeline/tree/main/.codex/skills/statsmodels Command: npx skills add https://github.com/Sologa/codex-pipeline --skill statsmodels-sologa
This Skill provides a comprehensive suite of statistical models and diagnostic tools for rigorous data analysis, hypothesis testing, and inference.
Use the statsmodels skill to fit an OLS regression model with 'y' as the dependent variable and 'x1', 'x2' as independent variables.
High-intent search queries and answers about installing and using this skill.
You can fit OLS regression models and perform hypothesis testing in Python by using the statsmodels library, which generates detailed diagnostic tables and robust inference results for your data.
Yes, you can perform time series forecasting with ARIMA and VAR models in Python using statsmodels, which supports fitting, diagnosing, and validating temporal patterns in your time series data.
Statsmodels focuses on rigorous econometrics and inference, offering publication-ready tables, extensive diagnostic checks, and specialized models like discrete choice and generalized linear models for advanced data analysis.
To model discrete choice data, use statsmodels in Python to fit Logit or Poisson models, enabling you to analyze categorical outcomes and count data with robust statistical inference.
No external dependencies are required beyond the base environment to fit generalized linear models (GLM), as the statsmodels library operates independently to perform statistical modeling and inference.
You should use robust inference and diagnostic checks during regression analysis when testing model assumptions, detecting outliers, or validating treatment effects to ensure your econometric conclusions are statistically rigorous.
Ritabrata-ChakrabortyFit statistical models and analyze time series data in Python.
matheus-rechDetect publication bias in meta-analyses with funnel plots and Egger's test.
StarlitnightlyPerform statistical tests and corrections on datasets using SciPy, statsmodels, and NumPy.
hxhyyyPerform statistical tests on financial time-series data with statsmodels and arch.
