Prophet
Facebook's Prophet is both a Python/R library and the algorithm that comes with it. The algorithm was published in 2017 ("Forecasting at Scale" by Sean Taylor and Benjamin Letham). The authors write that the problems of forecasting and anomaly detection in practice involve the complexity of handling a variety of idiosyncratic forecasting problems at Facebook with piecewise trends, multiple seasonalities, and floating holidays, and building trust across the organization in these forecasts.
With these goals in mind, Prophet was designed to be scalable to many time-series, flexible enough for a wide range of business-relevant, possibly idiosyncratic time-series, and at the same time intuitive enough to be configurable by domain experts who might have little knowledge of time-series methods.
The Prophet algorithm is similar to the Generalized Additive Model (GAM) and formalizes the relationship between the forecast for the three model components, trend...
