Understand it before memorizing it.
Explain today from past values and past forecast errors after stabilizing the series.
Where this model earns its place
Classical forecasting
Start with a simpler baseline then compare this model using the same evaluation split and operational constraints.
Stationary-ish signals
Start with a simpler baseline then compare this model using the same evaluation split and operational constraints.
Transparent baselines
Start with a simpler baseline then compare this model using the same evaluation split and operational constraints.
Trade-offs matter more than popularity.
Strengths
✓ Interpretable
✓ Good baseline
Limitations
△ Weak with complex nonlinear seasonality
Metrics to watch
Before it reaches real users
- 01
Check stationarity
Document the assumption and instrument the condition so regressions can be detected.
- 02
Backtest chronologically
Document the assumption and instrument the condition so regressions can be detected.
- 03
Monitor residuals
Document the assumption and instrument the condition so regressions can be detected.