How to Save an ARIMA Time Series Forecasting Model in Python

Last Updated on August 28, 2019

The Autoregressive Integrated Moving Average Model, or ARIMA, is a popular linear model for time series analysis and forecasting.

The statsmodels library provides an implementation of ARIMA for use in Python. ARIMA models can be saved to file for later use in making predictions on new data. There is a bug in the current version of the statsmodels library that prevents saved models from being loaded.

In this tutorial, you will discover how to diagnose and work around this issue.

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• Updated Apr/2019: Updated the link to dataset.
• Updated Aug/2019: Updated data loading to use new API.

Daily Female Births Dataset

First, let’s look at a standard time series dataset we can use to
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