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8 points by seanjtaylor 541 days ago | link | parent

I'm one of the creators of Prophet. I'm happy to answer any questions people have here.


2 points by don 540 days ago | link

Many thanks for releasing this! the effort to do so in both R and Python, with all the supporting documentation, is very appreciated.

Perhaps a more general or 'motivational' question - what are some common use cases for accurate events/clicks predictions? If it is just a trend that someone is interested in then an analyst can 'eyeball' it pretty well from the time series plot. I guess the need for high accuracy is driven by more than just spotting a trend?

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1 point by seanjtaylor 538 days ago | link

We don't really use Prophet for event prediction. It's mostly for predicting aggregates that are measured on a slower timescale (daily or weekly data). Accuracy is harder to measure for time series forecast because out of sample is tough to evaluate.

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1 point by saml 529 days ago | link

Are you applying any theory from the Hierarchical Temporal Memory work by Jeff Hawkins? (https://github.com/numenta/nupic/wiki/Hierarchical-Temporal-...)

It seemed to be great at forecasting periodic trends too, so that's why I wonder ...

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1 point by tfturing 538 days ago | link

Can it be used for causal inference (similar to counterfactual inference like CausalImpact)?

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1 point by fhira 539 days ago | link

What is the differentiation between Prophet's R API and Rob Hyndman's forecast package? Thanks!

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2 points by seanjtaylor 538 days ago | link

Good question. We tried to make it conform to a more standard fit/predict model. The main difference is that predict takes a dataframe of future dates which we provide a helper function for creating. In most of Rob Hyndman's predict functions, they take a number of periods ahead to forecast instead of an explicit set of dates.

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1 point by izyda 539 days ago | link

Are there plans to support covariates to the additive model?

If not, is this a feature/pull request that might be accepted?

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1 point by seanjtaylor 538 days ago | link

We'd love help with this. It's one of the most requested features.

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