Var

使用 VAR 分析多个时间序列的动态关系(forecast 向量自回归)

Zafer-Liu 53dd6da 1.0 KB Updated

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VAR 分析

确认多个同步时间序列、频率和滞后范围,检查平稳性与样本长度。报告滞后选择、预测表现和动态响应;将格兰杰关系表述为预测信息而非因果证明。

Tool routing

  1. Use get_schema to identify multiple time-aligned target series, the time column, and source table.
  2. Use query_data only to verify frequency alignment, missing periods, stationarity preparation needs, and sample length.
  3. Use run_analysis with analysis_name="Time_Series_VAR" for the actual VAR computation.
  4. Use generate_chart on forecast, lag, or response 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_VAR/analyze.py
  • Chart implementation: Function/Charts_generation/chart_generate.py

Zafer-Liu/Data-Analysis-Agent commit 53dd6da166

Frequently asked questions

npx skillmds add zafer-liu/var