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Exogenous Variables in Time Series Forecasting with Facebook Prophet
Latest   Machine Learning

Exogenous Variables in Time Series Forecasting with Facebook Prophet

Last Updated on July 25, 2023 by Editorial Team

Author(s): David Andres

Originally published on Towards AI.

Photo by John Fowler on Unsplash

In the previous part of our Facebook Prophet series, we covered how to model the seasonality component. You should also recall the first part, in which we dealt with trend modeling.

In this article, we’ll focus on how we can add exogenous variables to our model. They are also known as independent variables or predictor variables. They are variables that are not directly influenced by other variables within a system or model. In other words, variables that are assumed to have a causal effect on other variables in the system, but are not affected by them…. Read the full blog for free on Medium.

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Published via Towards AI

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