sarima
使用 SARIMA 建模季节性时间序列预测（forecast）
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- Zafer-Liu/Data-Analysis-Agent
- Last source activity
- July 17, 2026 at 13:24
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Source instructions · Read-only preview- name
- sarima
- description
- 使用 SARIMA 建模季节性时间序列预测（forecast）
- icon
- 🌊
- allowedTools
- ["get_schema","query_data","run_analysis","generate_chart"]
# SARIMA 预测
确认时间频率和季节周期，检查数据长度能否覆盖足够周期。执行季节模型与时间验证，报告参数、误差、预测区间和季节模式；数据不足时不要强行拟合。
## Tool routing
1. Use `get_schema` to identify the time column, target column, seasonal frequency, and source table.
2. Use `query_data` only to verify sorted frequency, missing periods, and enough seasonal cycles.
3. Use `run_analysis` with `analysis_name="Time_Series_SARIMA"` for the actual forecast computation.
4. Use `generate_chart` on forecast or seasonal diagnostic result tables after `run_analysis` succeeds.
## Implementation reference
- Tool entry: `agent/tools/business/data.py::_tool_run_analysis`
- Analysis registry: `Function/Analyze/registry.py`
- Analysis implementation: `Function/Analyze/Time_Series_SARIMA/analyze.py`
- Chart implementation: `Function/Charts_generation/chart_generate.py`
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