# Analyze Results

> 分析数模求解结果，计算统计量，生成对比表和洞察。当用户说'分析结果'、'结果对比'、'analyze results'、或需要解读计算结果时使用。

- Skill: `best6668/analyze-results` (Agent Skill, multi-file: 3 files)
- Install (CLI): `npx skillmds@latest add best6668/analyze-results`
- Raw SKILL.md: https://api.skillmd.com/api/skills/best6668/analyze-results/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: best6668 (https://skillmd.com/u/best6668)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/best6668/analyze-results

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# 分析求解结果

Analyze: $ARGUMENTS

## Workflow

### Step 1: 定位结果文件
Find all relevant result files:
- Check `results/`, `output/`, `figures/`, or project-specific output directories
- Parse JSON/CSV/Excel results into structured data
- Read solver logs for convergence information

### Step 2: 构建对比表
Organize results by:
- **子问题**: which sub-problem each result belongs to
- **方法**: which mathematical method was used
- **关键指标**: R², RMSE, 目标函数值, 残差, 误差率 etc.
- **与预期对比**: compare against expected values, theoretical bounds, or baseline methods

### Step 3: 统计分析
- If multiple runs: report mean +/- std, check robustness
- If sweeping a parameter: identify sensitivity trends (monotonic, U-shaped, plateau)
- Perform error analysis: residual distribution, prediction vs actual
- Check model fit: R², adjusted R², F-statistic, p-values
- Flag outliers or suspicious results (unreasonable values, non-convergence)

### Step 4: 生成洞察
For each finding, structure as:
1. **观察**: what the data shows (with numbers)
2. **解读**: why this result makes sense (or doesn't)
3. **意义**: what this means for the competition problem
4. **下一步**: what analysis or improvement would strengthen the result

### Step 5: 生成图表建议
Based on the analysis, suggest figures for the paper:
- 拟合曲线 (predicted vs actual)
- 残差分布图
- 灵敏度分析图 (parameter sensitivity)
- 误差随参数变化图
- 结果对比柱状图/表格

### Step 6: 更新文档
If findings are significant:
- Propose updates to MODEL_REPORT.md or SOLVE_PLAN.md
- Draft a concise finding statement (1-2 sentences)
- Save analysis to `RESULTS_ANALYSIS.md`

## Output Format
Always include:
1. Raw data table (数值结果)
2. Key findings (numbered, concise)
3. Statistical validation (误差分析、模型检验)
4. Suggested figures for paper
5. Suggested next steps (if any)