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statsmodels

Fit OLS, ARIMA, and discrete choice models with Python statistical diagnostics.

1|1|Updated Mar 13, 2026
Search Tags:#time series#data analysis#hypothesis testing#statistics#regression#econometrics
One-click install
npx skills add https://github.com/youyinnn/skills-collection --skill statsmodels-youyinnn
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: statsmodels
Source: https://github.com/youyinnn/skills-collection/tree/main/plugins/results-analysis-and-visualization/skills/statsmodels
Command: npx skills add https://github.com/youyinnn/skills-collection --skill statsmodels-youyinnn

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a comprehensive suite of tools for statistical modeling, estimation, inference, and diagnostics, enabling rigorous data analysis and hypothesis testing.

Core Features & Use Cases

  • Model Fitting: Supports OLS, GLM, discrete choice, time series, and more.
  • Inference & Diagnostics: Offers robust standard errors, hypothesis tests, and diagnostic checks.
  • Use Case: Analyze complex datasets by fitting appropriate statistical models, testing hypotheses, and generating publication-ready results with detailed diagnostics.

Quick Start

Use the statsmodels skill to fit an OLS regression model with y as the dependent variable and x1, x2 as independent variables.

Frequently Asked Questions about statsmodels

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I perform time series forecasting with ARIMA or SARIMAX models?▼

Time series forecasting with ARIMA or SARIMAX is achieved by fitting these statistical models to your sequential data. This Skill supports fitting both models to generate forecasts and conduct rigorous inference on time-dependent datasets.

Can I use a formula API for OLS regression analysis in Python?▼

Yes, OLS regression analysis supports a formula API for defining dependent and independent variables. This allows you to fit linear models using a standard formula syntax and generate detailed diagnostic results.

What's the best way to run discrete choice modeling like Logit or Probit?▼

Running discrete choice modeling like Logit or Probit is handled directly through this Skill's statistical modeling capabilities. It supports fitting Logit, Probit, Poisson, and Negative Binomial models with extensive diagnostic tools.

Does this support hypothesis testing and robust standard errors for econometrics?▼

Hypothesis testing and robust standard errors are fully supported for econometric analysis. The Skill provides comprehensive inference and diagnostic checks, enabling rigorous data analysis and model validation for your statistical models.

When do I need GLS or WLS instead of OLS for statistical modeling?▼

You need GLS or WLS for statistical modeling when your data violates OLS assumptions like homoscedasticity. This Skill supports Generalized Least Squares and Weighted Least Squares alongside OLS to handle complex datasets with varying error structures.

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