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skillboardM-estimation, influence functions, and semiparametric efficiency theory for causal inference
Asymptotic Theory Rigorous framework for statistical inference and efficiency in modern methodology Use this skill when working on: asymptotic properties of estimators, influence functions, semiparametric efficiency, double robustness, variance estimation, confidence intervals, hypothesis testing, M estimation, or deriving limiting distributions. Efficiency Bounds Semiparametric Efficiency Theory Cramér Rao Lower Bound : For any unbiased estimator, $$\text{Var}(\hat{\theta}) \geq…
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/asymptotic-theory · 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/26-Data-Wise-scholar/skills/mathematical/asymptotic-theory" ".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/26-Data-Wise-scholar/skills/mathematical/asymptotic-theory" ".claude/skills/"
rm -rf .skillboard-tmpDestination: .claude/skills/asymptotic-theory
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.