pmdarima
2.0.0
  • API Reference
  • Examples
  • User Guide
    • 1. About the project
    • 2. Setup
    • 3. Quickstart
    • 4. Serializing your ARIMA models
    • 5. Refreshing your ARIMA models
    • 6. Tips to using auto_arima
    • 7. When no viable models can be found
    • 8. Encountering issues in seasonal differencing
    • 9. Toy time-series datasets
    • 10. Use cases
      • 10.1. Stock Market Prediction
      • 10.2. An end-to-end time series analysis
    • 11. Contributing to pmdarima
    • 12. Contributors
    • 13. Citing
  • What's New?
  • RFCs
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10. Use casesΒΆ

Here are some easy-to-follow, common use cases for why you might use pmdarima in your forecasting work.


  • 10.1. Stock Market Prediction
    • 10.1.1. Imports & data loading
    • 10.1.2. Data splitting
    • 10.1.3. Pre-modeling analysis
      • 10.1.3.1. Estimating the differencing term
    • 10.1.4. Fitting our model
    • 10.1.5. Updating the model
    • 10.1.6. Viewing forecasts
    • 10.1.7. Conclusion
  • 10.2. An end-to-end time series analysis
    • 10.2.1. Imports, data loading & splitting
    • 10.2.2. Examining the data
    • 10.2.3. Fitting a baseline
    • 10.2.4. Transforming our data
    • 10.2.5. Fitting the transformed data
    • 10.2.6. Examining forecasts
    • 10.2.7. Final thoughts

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