Atlas · GenAI 2026
ARIMA
Building autoregressive integrated moving-average models for univariate time series, including differencing, order selection and residual diagnostics.
Also searchable as: Autoregressive Integrated Moving Average, ARIMA Models
conceptForecastingAI consensus: 0/3
Prerequisites
- mediumStatistical Inference
Parameter estimation, residual testing and uncertainty intervals rely on statistical inference.
Recommended reference
statsmodels: ARIMA — https://www.statsmodels.org/stable/generated/statsmodels.tsa.arima.model.ARIMA.html
Reviewed sources
Primary and first-party material reviewed for this editorial summary. These citations are separate from the AI consensus score above.
- statsmodels: ARIMA
Autoregressive, differencing and moving-average orders and model specification.
- statsmodels: SARIMAX Introduction
Autoregressive and moving-average specifications, diagnostics and seasonal extensions.
- Hyndman and Athanasopoulos: ARIMA models
ARIMA foundations and the forecasting workflow.
Notes from AI deep research
Related skills
- ← is subcategory of: SARIMA
- → is subcategory of: Time Series Forecasting