profoc: Probabilistic Forecast Combination Using CRPS Learning

Combine probabilistic forecasts using CRPS learning algorithms proposed in Berrisch, Ziel (2021) <arXiv:2102.00968>. The package implements multiple online learning algorithms like Bernstein online aggregation; see Wintenberger (2014) <arXiv:1404.1356>. Quantile regression is also implemented for comparison purposes. Model parameters can be tuned automatically with respect to the loss of the forecast combination. Methods like predict(), update(), plot() and print() are available for convenience. This package utilizes the optim C++ library for numeric optimization <https://github.com/kthohr/optim>.

Package details

AuthorJonathan Berrisch [cre] (<https://orcid.org/0000-0002-4944-9074>), Florian Ziel [aut] (<https://orcid.org/0000-0002-2974-2660>)
MaintainerJonathan Berrisch <Jonathan@Berrisch.biz>
LicenseGPL (>= 3)
Version0.8.5
URL https://profoc.berrisch.biz/ https://github.com/BerriJ/profoc
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("profoc")

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profoc documentation built on Oct. 22, 2021, 5:08 p.m.