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Robust statistics toolkit

Skill a5c-ai/babysitter/library/specializations/domains/science/mathematics/skills/robust-statistics-toolkit

Robust statistical methods resistant to outliersFrom its SKILL.md

Install
npx -y skills add a5c-ai/babysitter --skill robust-statistics-toolkit

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SKILL.md

1.2 KB, 151 tokens by cl100k_base, as published. Nobody here has run it

Robust Statistics Toolkit

Purpose

Provides robust statistical methods resistant to outliers and model violations for reliable inference.

Capabilities

  • M-estimators (Huber, Tukey)
  • Trimmed and winsorized estimators
  • Robust regression (MM-estimation)
  • Breakdown point analysis
  • Influence function computation
  • Robust covariance estimation

Usage Guidelines

  1. Outlier Detection: Identify potential outliers first
  2. Estimator Selection: Choose based on expected contamination
  3. Breakdown Point: Consider required breakdown point
  4. Efficiency: Balance robustness and efficiency

Tools/Libraries

  • robustbase (R)
  • scikit-learn
  • statsmodels

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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