Agent skill

statsmodels

Statsmodels is Python's premier library for statistical modeling, providing tools for estimation, inference, and diagnostics across a wide range of statistical methods.

majiayu000534★ · 1 repos on radarProfile →
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill statsmodels-francostino-opencode-skills-anti --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 19 KB
Bundled scripts: none
Path: skills/analysis/statsmodels-francostino-opencode-skills-anti/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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 ## Quick Start Guide ### Linear Regression (OLS) ```python import statsmodels.api as sm import numpy as np import pandas as pd # Prepare data - ALWAYS add constant for intercept X

What's inside
Steps it walks through
  1. Overview
  2. When to Use This Skill
  3. Quick Start Guide
  4. Linear Regression (OLS)
  5. Logistic Regression (Binary Outcomes)
  6. Time Series (ARIMA)
  7. Generalized Linear Models (GLM)
  8. Core Statistical Modeling Capabilities
  9. 1. Linear Regression Models
  10. 2. Generalized Linear Models (GLM)
  11. 3. Discrete Choice Models
  12. 4. Time Series Analysis
  13. 5. Statistical Tests and Diagnostics
  14. Formula API (R-style)
Ships with 1 file
  • metadata.json
Commands it runs
Find information about specific models
grep -r "Quantile Regression" references/
Find diagnostic tests
grep -r "Breusch-Pagan" references/stats_diagnostics.md
Find time series guidance
grep -r "SARIMAX" references/time_series.md
More from claude-skill-registry
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About this skill
What does the statsmodels skill do?

Statsmodels is Python's premier library for statistical modeling, providing tools for estimation, inference, and diagnostics across a wide range of statistical methods.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill statsmodels-francostino-opencode-skills-anti --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going