What is the Statsmodels Claude Code skill?

It is a specialized capability that allows Claude to implement, interpret, and troubleshoot complex statistical models using the Python statsmodels library.

Is it suitable for publication-quality research?

Absolutely. It focuses on producing comprehensive summary tables and rigorous diagnostic metrics (AIC/BIC, P-values) required for academic and professional reporting.

Can this skill handle time series forecasting?

Yes, it includes support for univariate and multivariate time series models like ARIMA, SARIMAX, and VAR, including stationarity testing and residual diagnostics.

How does it help with model validation?

It includes specific routines for testing statistical assumptions like normality, heteroskedasticity, and autocorrelation to ensure valid inference and robust results.

Does it support R-style formulas?

Yes, the skill provides guidance on using the statsmodels formula API for intuitive model specification using the 'y ~ x1 + x2' syntax.

Statsmodels Statistical Analysis

Name: Statsmodels Statistical Analysis
Author: Microck

byMicrock

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111

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Data Science & ML

Performs rigorous statistical modeling, econometric analysis, and hypothesis testing using Python's statsmodels library.

This skill empowers Claude to conduct deep statistical investigations, providing a robust framework for regression analysis, time series forecasting, and generalized linear modeling. It includes comprehensive tools for model diagnostics, such as testing for heteroskedasticity and autocorrelation, ensuring that every analysis meets the standards of academic and professional econometric research. Whether you're fitting OLS models, analyzing discrete choice data, or performing complex ARIMA forecasting, this skill provides the domain-specific logic and best practices required for accurate statistical inference.

Key Features

01R-style formula API support for intuitive model specification

02Advanced regression modeling including OLS, WLS, and Mixed Effects

03Generalized Linear Models (GLM) for Poisson, Binomial, and Gamma distributions

04Comprehensive time series analysis with ARIMA, SARIMAX, and VAR models

05Rigorous diagnostic testing for model assumptions and influence detection

06111 GitHub stars

Use Cases

01Analyzing discrete outcomes in social science or marketing data

02Econometric research and financial time series forecasting

03Validating scientific hypotheses through rigorous statistical testing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add microck/ordinary-claude-skills statsmodels

For use in Claude.ai and ChatGPT

Download Skill