statistical-method-design

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Design statistical methods, baselines, diagnostics, variants, and ablations that directly address a formal problem formulation.

aiming-lab By aiming-lab schedule Updated 5/20/2026

name: statistical-method-design description: > Design statistical methods, baselines, diagnostics, variants, and ablations that directly address a formal problem formulation. metadata: category: domain trigger-keywords: "method proposal,estimator,algorithm,baseline,ablation,diagnostic,statistical method" applicable-stages: "3,4,5,6,7,8" priority: "1"

Statistical Method Design

Overview

Use this skill after formal problem formulation. The method should be a response to the formal target and assumptions, not a generic collection of techniques.

Required Method Proposal

For each method:

  • Name
  • Problem it solves
  • Formula or algorithm
  • Inputs and outputs
  • Tuning parameters
  • Required assumptions
  • Diagnostics
  • Expected failure modes
  • Computational cost
  • Relation to baselines

Baselines and Ablations

Always define meaningful baselines:

  • Classical or standard method
  • Naive or unadjusted method
  • Oracle or idealized reference when available
  • Robust variant
  • Ablation removing the key design feature

Method-to-Claim Map

Every method must connect to at least one claim:

method_to_claim_map:
  proposed_method:
    claims: [C1, C2]
    expected_evidence: "lower risk under stress condition"
    theory_target: "consistency under assumptions A1-A3"
Install via CLI
npx skills add https://github.com/aiming-lab/AutoResearchClaw --skill statistical-method-design
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