How is this different from fbprophet?

[bholland]

Hello all,

I couldn't find this out easily online but how is this different from fbprophet? It seems that fbrpophet + all of those dependencies is a requirement plus it provides plots that are nearly identical to prophet along with trend lines and error bounds. I was hoping to get a bit more into the algorithm and how it differs from other algorithms that detects trends, trend breaks, seasonality adjustments, and more. Basically, I would be looking for the research paper behind greykite and arguments about why those changes make it better than others.

I am very interesting is how the forecasts improved with this algorithm and a theoretical underpinning for this conclusion. I have no doubt that an algorithm built and designed by linkedin would work quite well on linked in data. I would love to read about additional examples and why greykite out performs these models.

Thanks!

[sayanpatra]

Hi,

We allow users to use Prophet through our interface, hence the dependencies. However, we have removed the dependency in the latest version greykite==0.2.0.

The algorithms for Prophet and greykite are quite different. E.g. Prophet is a Bayesian method while the main algorithm of greykite (called Silverkite) is a frequentist method. You can find a high-level comparison between the two here.

You can find more details about the algorithm in our blog post and research paper where we compare the performance of the models on external datasets.