Looking at the prophet example (see here ), I notice that at the end when he makes an out-of-sample prediction, he does it by manually drawing his own samples and using the inferred quantities from the model to model the trend in the future. My question is this: Is there a way to do OOS time-series …

Does this help? If your observed variable is a pandas series or data frame column with missing values, pymc3 will automatically ‘interpolate’, which in this case is actually ‘predicting’: https://gist.github.com/DanielWeitzenfeld/bbfe8246dc20df77eee8e48ac12d65de extrapolating random walk.i…

Out-of-sample random-walk time series prediction

Questions

DanWeitzenfeld September 23, 2019, 2:02pm 5

The trick, AFAICT, is to pass either a pandas series or a pandas data frame column as observed.

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Bad Initial Energy when observed var contains nan

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Out-of-sample random-walk time series prediction

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