Atlas · GenAI 2026
SARIMA
Specifying, fitting and diagnosing seasonal ARIMA models with separate seasonal and non-seasonal autoregressive, differencing and moving-average orders.
Also searchable as: Seasonal ARIMA, Seasonal Autoregressive Integrated Moving Average
conceptForecastingAI consensus: 0/3
Prerequisites
- mediumTime Series Forecasting
Temporal dependence, seasonality and time-respecting evaluation are the task foundation.
Recommended reference
statsmodels: SARIMAX Introduction — https://www.statsmodels.org/stable/examples/notebooks/generated/statespace_sarimax_stata.html
Reviewed sources
Primary and first-party material reviewed for this editorial summary. These citations are separate from the AI consensus score above.
- statsmodels: SARIMAX Introduction
Separate seasonal and non-seasonal orders; seasonal ARIMA specification.
- statsmodels: ARIMA
Seasonal and non-seasonal model order specification.
- Hyndman and Athanasopoulos: Seasonal ARIMA models
Seasonal differencing, multiplicative seasonal models and model diagnostics.
Notes from AI deep research
Related skills
- → is subcategory of: ARIMA