SAS Viya Forecasting Cookbook


You may be familiar with the online text Forecasting: Principles and Practice, by two of the very top contributors in the field, Rob Hyndman and George Athanasopoulos. (Both are at Monash University in Australia. Rob was longtime Editor-in-Chief of the International Journal of Forecasting, and George is currently President of the International Institute of Forecasters.) From the Preface:

This textbook is intended to provide a comprehensive introduction to forecasting methods and to present enough information about each method for readers to be able to use them sensibly. We don’t attempt to give a thorough discussion of the theoretical details behind each method, although the references at the end of each chapter will fill in many of those details.

The online text is frequently updated (most recently on June 11, 2020 as of this writing). And while the online version is free to access, downloadable and hard copy versions can be purchased.

SAS Viya Forecasting Cookbook on GitHub

Throughout Forecasting: Principles and Practice, the authors use R to illustrate examples. But what if you want to try the examples in SAS?

My colleagues in R&D thought it would be helpful to illustrate some of the book's examples in SAS, and have produced the SAS Viya Forecasting Cookbook on GitHub. Examples include time series regression models, time series decomposition, exponential smoothing, ARIMA, hierarchical forecasting, and neural nets.

So what if you happen to like coding in R, Python, or other open source as well as in SAS?

SAS: Designed to Be Open

SAS delivers an open analytics platform that's accessible from the interface or coding language of your choice. The SAS open platform is compatible with the following:

  • SAS - SAS Viya uses PROC CAS to run CAS actions in SAS Cloud Analytic Services.
  • REST - Use REST APIs for any client language to access SAS analytics, data and services.
  • Python - Use Python APIs to apply SAS Viya CAS actions.
  • R - Use R APIs to apply SAS Viya CAS actions.
  • Java - Use Java APIs to apply SAS Viya CAS actions.
  • Lua - Use Lua APIs to apply SAS Viya CAS actions.
  • iOS and Android - Use iOS and Android SDKs to create mobile apps that access content in SAS Viya.

So with SAS, you can build analytics your way using your preferred programming language (SAS, Python, Java, R), or an intuitive interface, or open REST APIs -- from one platform.

Find more online about SAS and the Open Ecosystem.

Full citation of the book: Hyndman, R.J., & Athanasopoulos, G. (2018) Forecasting: principles and practice, 2nd edition, OTexts: Melbourne, Australia. Accessed on June 25, 2020.


About Author

Mike Gilliland

Product Marketing Manager

Michael Gilliland is author of The Business Forecasting Deal (the book), editor of Business Forecasting: Practical Problems and Solutions, and Associate Editor of Foresight: The International Journal of Applied Forecasting. He is a longtime business forecasting practitioner, and currently Product Marketing Manager for SAS Forecasting software. Mike serves on the Board of Directors of the International Institute of Forecasters, and received the 2017 Lifetime Achievement award from the Institute of Business Forecasting. He initiated The Business Forecasting Deal (the blog) to help expose the seamy underbelly of forecasting practice, and to provide practical solutions to its most vexing problems.

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