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name: forecasting description: "Fit, search, diagnose, and forecast fixed-order or automatic seasonal ARIMA models with pmdarima." disable-model-invocation: true metadata: disco-role: operating license: MIT

Forecasting

Use this skill when the task is to fit a pmdarima ARIMA/AutoARIMA, choose orders with auto_arima, handle seasonal periods or exogenous regressors, and produce forecasts or intervals. Keep the series and forecast horizon explicit; validate X shape before fitting and again before forecasting.

Operating route

1. Inspect the input as a finite one-dimensional numeric series and decide whether the requested seasonal period m is supported by the available history.
2. Start with a constrained fixed-order ARIMA when the order is known. Otherwise use stepwise auto_arima with a bounded search, error_action='trace' while debugging, and a reproducible small StepwiseContext when runtime needs a cap.
3. Fit with y and, if used, an X matrix whose row count equals len(y). For a future forecast, provide exactly one row per period and the same number of columns as training X.
4. Call predict(n_periods=h, return_conf_int=True, alpha=...) for an out-of-sample forecast and interval matrix, or predict_in_sample(...) for fitted values/residual inspection. Examine model.order, model.seasonal_order, model.resid(), and model.summary() after fitting.
5. Treat update(y_new, X=...) as the observation-refresh handoff to the persistence-update sub-skill; do not use this skill for artifact serialization or update mechanics.

Read the linked references for signatures, bounded workflows, diagnostics, and recovery. Run scripts/simple_forecast.py --help before adapting the bundled smoke case; it is deterministic, local, and plotting-free.

Boundaries

This skill covers pmdarima.ARIMA, pmdarima.auto_arima, pmdarima.arima.AutoARIMA, StepwiseContext, seasonal order/seasonal_order/m, exogenous regressors, fitting, prediction, intervals, and residual diagnostics. Preprocessing/transformer internals, cross-validation/model-selection orchestration, and serialization/update artifact mechanics belong to sibling skills.

Provenance note

The inspected source was tagged v2.1.1 at commit 4c2dfccb28f64d2c00a5e10b59c1d1a3e16576a9, while the inspection environment reports package version 0.0.0. Do not infer a release/version guarantee from this skill; route environment/version discrepancies to root troubleshooting.

Local references

• API reference — signatures, contracts, order semantics, exogenous shapes, and diagnostics.
• Workflows — fixed, seasonal, automatic, exogenous, interval, and diagnostic procedures.
• Troubleshooting — symptoms, likely causes, and bounded recovery actions.
• Deterministic smoke script — runnable tiny fixed/seasonal/automatic forecast example.