aiming-lab/autoresearchclaw/statistical-theory-analysis

Claude Code and agent skill by aiming-lab/autoresearchclaw

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Analyze theoretical properties of statistical methods under the formal formulation: identifiability, bias, variance, consistency, asymptotics, coverage, error bounds, robustness, and limitations.

Install

npx vskill@latest install aiming-lab/autoresearchclaw/statistical-theory-analysis

SKILL.md

Statistical Theory Analysis

Overview

Use this skill after method proposal and before final experimental comparison. Theory is required as a stage even if the final output is a simulation paper.

Theory Outputs

Depending on the topic, provide:

  • Identifiability argument
  • Bias or variance calculation
  • Consistency statement
  • Asymptotic distribution
  • Coverage or calibration argument
  • Risk or error bound
  • Robustness analysis
  • Sensitivity or impossibility result
  • Counterexample showing failure outside assumptions

Theorem Template

markdown
## Proposition
Under assumptions A1-Ak, method M satisfies ...
 
## Proof Sketch
1....
2....
3....
 
## Interpretation
This predicts that ...
 
## Limitations
The result does not cover ...

Experimental Predictions

Every theoretical claim should produce an empirical prediction when possible:

  • Direction of metric change
  • Condition under which the method should improve
  • Stress condition under which it should fail
  • Baseline it should outperform

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

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Source

Popularity

Repository stars
13,869
Repository forks
1,628
7-day trend score
48

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