Time Series Modeling Using Auto Arima With Python

Time Series Modeling Using Auto Arima With Python

Pmdarima (pyramid-arima) statistical library is designed for Python time series analysis. The auto_arima is an automated arima function of this library, which is created to find the optimal order and the optimal seasonal order, based on determined criterion such as AIC, BIC, etc.

Pmdarima (pyramid-arima) statistical library is designed for Python time series analysis. The auto_arima is an automated arima function of this library, which is created to find the optimal order and the optimal seasonal order, based on determined criterion such as AIC, BIC, etc., and within the designated parameter restrictions, that fits the best model to a single variable (univariable) time series.

Pmdarima requires specific Python packages.

!pip install pmdarima
from pmdarima.arima import auto_arima

The model results highly depend on the parameter setting, which can be inspected in the documentation in detail. In this tutorial, we inspect the mechanics of time series modeling using auto_arima because the parameter settings vary based according to the dataset and expectations of forecasting.

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