Seasonality in Time Series Forecasting with Facebook Prophet

Author(s): David Andres

Originally published on Towards AI.

Photo by Nattu Adnan on Unsplash

In the previous part of our Facebook Prophet series, we covered how to model the trend component and adjust the changepoints and regularization to improve forecasting accuracy. In this article, we’ll focus on the seasonal component and explore how to effectively model it using Facebook Prophet.

The way Facebook Prophet uses to model seasonality is through partial Fourier sums. Partial Fourier sums are truncated version of the Fourier series that uses a finite number of terms to represent a periodic function. The choice of how many terms to include in the partial Fourier sum depends on… Read the full blog for free on Medium.

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Published via Towards AI