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Probabilistic Forecast Reconciliation #31
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Hi @Manjubn777, We have been doing research/working on probabilistic hierarchical forecasting, but have not released. I can point you to my work in progress paper "Probabilistic Hierarchical Forecasting with Deep Poisson Mixtures" and Taieb's PERMBU. Regarding implementations of algorithms GluonTS team did an effort to improve the usability of PERMBU in this repository, it has a lot of dependency frictions. If you have any pointers please let me know, this is a really interesting topic for us. |
Hey @Manjubn777! The new version of |
Hey Team,
Thank you so much for notebooks and I do have a question. Let's say I have
2000 forecast samples for each day,which will be passed as y_hat_df and I
have actuals which is like one value for each day(daily data)., I will pass
actual data as fitted values. setting bootstrap = True helps me reconcile?
I would appreciate your answer to the above question.
Thanks and Regards,
Manjula
…On Wed, Sep 28, 2022 at 7:39 AM fede ***@***.***> wrote:
Hey @Manjubn777 <https://github.com/Manjubn777>! The new version of
HierarchicalForecast supports probabilistic forecast reconciliation.
- Example assuming normality
<https://nixtla.github.io/hierarchicalforecast/examples/australiandomestictourism-intervals.htmll>
- Example using bootstrapping
<https://nixtla.github.io/hierarchicalforecast/examples/australiandomestictourism-bootstraped-intervals.html>
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After going through the package and paper found that supports only point forecasts reconciliation. I would like to know if it supports probabilistic forecast reconciliation. I appreciate your quick response to my inquiry for information.
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