screening-then-decomposition
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npx mdskill add yogsoth-ai/de-anthropocentric-research-engine/screening-then-decompositionPerforms efficient sensitivity analysis using two-phase approach
- Identifies and eliminates unimportant model parameters
- Uses Morris screening followed by Sobol decomposition
- Evaluates mu*, sigma, Si, and STi metrics for parameter importance
- Delivers prioritized list of influential parameters and interactions
SKILL.md
.github/skills/screening-then-decompositionView on GitHub ↗
--- name: screening-then-decomposition description: Two-phase sensitivity — Morris quick screening to eliminate unimportant factors, then Sobol precise decomposition on survivors. Efficient allocation of analytical effort. execution: tactic used-by: parameter-screening, variance-decomposition --- # Screening Then Decomposition Two-phase approach: quick screening followed by precise decomposition. ## Operations morris-screening → sobol-decomposition → interaction-detection ## Available SOPs **Subagent:** morris-screening, sobol-decomposition, interaction-detection **Import:** paper-search ## Execution Guidance Phase 1 (Morris): Screen all parameters, eliminate those with low mu* and low sigma. These are unimportant and can be safely fixed at nominal values. Phase 2 (Sobol): For surviving parameters, compute precise variance decomposition. First-order indices (Si) measure direct effects, total-order indices (STi) measure direct + all interactions. Phase 3: Detect significant interaction pairs (STi - Si > threshold). Characterize interaction types and implications. ## Minimum Yield ``` <HARD-GATE> - Parameters screened: >= 5 - Parameters eliminated (low mu*): >= 1 - Sobol indices computed: >= 3 parameters - Interaction pairs identified: >= 1 </HARD-GATE> ```