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Description

Probabilistic Forecast Combination Using CRPS Learning.

Combine probabilistic forecasts using CRPS learning algorithms proposed in Berrisch, Ziel (2021) <arXiv:2102.00968> <doi:10.1016/j.jeconom.2021.11.008>. 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>.

The profoc Package

An R package for probabilistic forecast combination

R-CMD-check GitHub Workflow Status (branch) Lifecycle: stable

The primary function online can be used to combine probabilistic forecasts using the CRPS learning algorithm introduced in Berrisch, Ziel (2021): Pre-Print, Publication. The function batch can be used in a similar way for batch optimization. Common methods like summary, print, plot, update, and predict are available.

Installation

Install from CRAN

You can install the latest stable release from CRAN using:

install.packages("profoc")

Install from GitHub

You can install the latest stable release from GitHub using:

# install.packages("remotes")
remotes::install_github("BerriJ/profoc")

You can install the latest development version from GitHub using:

# install.packages("remotes")
remotes::install_github("BerriJ/profoc@develop")

Documentation

You can find the documentation at profoc.berrisch.biz.

Contributions and Issues

Feel free to raise an issue if you find something not working properly.

You are very welcome to contribute to profoc. Please base your pull requests on the develop branch.

License

GNU General Public License (≥ 3)

Metadata

Version

1.3.2

License

Unknown

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