Auto-ARIMA

Auto-ARIMA performs a stepwise search over ARIMA parameter combinations and selects the best model using AIC or BIC. This removes the need for manual ACF/PACF analysis and order selection.

When to use:

• When ARIMA order selection is unclear or time-consuming
• Automated pipelines where manual tuning is not feasible
• Multiple series forecasting where each series may have different optimal orders

Input:

• Trained model checkpoint — exported auto-selected ARIMA model
• Preprocessing config — scaling settings
• Training tail — last N observations
• Steps — forecast horizon

Output: Forecasted values using the auto-selected model

Model Settings (set during training, used at inference)

Auto-ARIMA searches within bounds set during training:

• Max P / Max Q — upper bounds for AR and MA order search
• Max D — maximum differencing order
• Seasonal — whether to include seasonal components
• Information Criterion — aic or bic for model selection

The selected (p, d, q) and seasonal orders are fixed at training time.

Inference Settings

No dedicated inference-time settings. The selected order is baked into the trained model.