Comments (3)
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.
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Hey @Manjubn777! The new version of HierarchicalForecast
supports probabilistic forecast reconciliation.
from hierarchicalforecast.
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Related Issues (20)
- Update evaluation example in `README`
- hierarchicalforecast.core - 'list' object has no attribute 'insample' - HOT 2
- Sparse Methods Missing from 0.3.0 HOT 3
- StatsForecast models producing NotImplementedError: tiny datasets in 0.4.0 HOT 5
- MinTraceSparse(nonnegative=True) HOT 1
- [Core][Enhancement]: Add dummies to Aggregate
- Add temporal hierarchies HOT 2
- [Core] not balancing when doing aggregate() HOT 3
- [Core] KaTex parse error: Can't use function '$' in math mode
- Wrong argument name in evaluation section of README
- [utils] HierarchicalPlot is not plotting HOT 1
- TopDown method (proportion_averages, average_proportions) broken in 0.3.0, 0.4.0 and 0.4.1 HOT 6
- TopDown returns NaN HOT 10
- dependency on `quadprog` HOT 6
- [Core] Possible issue with core.py HOT 4
- [Methods] Undesired conversion to a dense matrix HOT 4
- KeyError when trying to get prediction intervals with MiddleOut HOT 1
- Package does not work with 3.12 HOT 3
- Support newer numpy versions HOT 4
- [<Library component: Models|Core|etc...>] Enhancement request: Include Elasso Algorithm HOT 2
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