skillboardUpdated every 6 hours
skillboardStatistical modeling: OLS/WLS/GLS, GLM (logit, probit, Poisson), time series (ARIMA, VAR), mixed effects, diagnostics. Formula API. Use for regressions without fixed effects, GLMs, or time series. For FE/DiD use pyfixest; panel/IV use linearmodels.
statsmodels Skill statsmodels general purpose statistical modeling library for Python. Covers OLS/WLS/GLS, GLM (logit, probit, Poisson, negative binomial), discrete choice models, time series (ARIMA, SARIMAX, VAR), mixed effects (MixedLM), robust regression, hypothesis tests, and comprehensive diagnostics. Supports R style formula API. Use when fitting regressions without fixed effects, running GLMs or logit/probit, analyzing time series, or using formula syntax. For fixed effects or DiD, use…
Full body not shown for this license – view the source on GitHub →Copy a source-pinned command for your client. You run it yourself.
Destination: .claude/skills/statsmodels · pinned to the source commit
# Run from your project root
git clone https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 692e9fa3fea40bbdf614584d461851f8fb968ac2
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels" ".claude/skills/"
rm -rf .skillboard-tmpReview the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.
sudo apt update && sudo apt install -y gitnpm install -g @anthropic-ai/claude-code# Run from your project root
git clone https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git .skillboard-tmp
git -C .skillboard-tmp checkout 692e9fa3fea40bbdf614584d461851f8fb968ac2
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/statsmodels" ".claude/skills/"
rm -rf .skillboard-tmpDestination: .claude/skills/statsmodels
Scanner static-checks@0.1.0 · commit 692e9fa3fea4. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.
No static rules matched. This is not a safety guarantee.