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htsDegenerateR

htsDegenerateR adapts the original hts library implementation of the trace minimization algorithm originally proposed by Wickramasuriya et al..

This library can be installed using:

devtools::install_github("lsteinmeister/htsDegenerateR“)

For more details, see Steinmeister et al..

Citation

Please cite this library as follows:

Steinmeister, L., & Pauly, M. (2024). Degenerate Hierarchical Time Series Reconciliation With The Minimum Trace Algorithm in R. In D. Herberger & M. Hübner (Eds.), Proceedings of the Conference on Production Systems and Logistics: CPSL. publish-Ing. https://doi.org/https://doi.org/10.15488/17729

References

Steinmeister, L., & Pauly, M. (2024). Degenerate Hierarchical Time Series Reconciliation With The Minimum Trace Algorithm in R. In D. Herberger & M. Hübner (Eds.), Proceedings of the Conference on Production Systems and Logistics: CPSL. publish-Ing. https://doi.org/https://doi.org/10.15488/17729

Wickramasuriya, S. L., Athanasopoulos, G., & Hyndman, R. J. (2019). Optimal Forecast Reconciliation for Hierarchical and Grouped Time Series Through Trace Minimization. Journal of the American Statistical Association, 114(526), 804–819. https://doi.org/10.1080/01621459.2018.1448825

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Version

Install

install.packages('htsDegenerateR')

Monthly Downloads

278

Version

0.1.0

License

GPL (>= 2)

Maintainer

Louis Steinmeister

Last Published

December 10th, 2024

Functions in htsDegenerateR (0.1.0)

BU

Bottom-up reconciliation
MinT

Using the method of Wickramasuriya et al. (2019), this function (based on Hyndman et al.'s hts library) combines the forecasts at all levels of a hierarchical time series and works for degenerate hierarchies.
accuracy.gts

accuracy.gts
strucScaling

Structural Scaling reconciliation