hikaru122700/cim-cac-maxcut-g22/statistical-method-design

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

Install

npx vskill@latest install hikaru122700/cim-cac-maxcut-g22/statistical-method-design

SKILL.md

The same SKILL.md was published earlier as aiming-lab/autoresearchclaw/statistical-method-design.

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:

yaml
method_to_claim_map:
  proposed_method:
    claims: [C1, C2]
    expected_evidence: "lower risk under stress condition"
    theory_target: "consistency under assumptions A1-A3"

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Works with

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