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profoc  

Probabilistic Forecast Combination Using CRPS Learning
View on CRAN: Click here


Download and install profoc package within the R console
Install from CRAN:
install.packages("profoc")

Install from Github:
library("remotes")
install_github("cran/profoc")

Install by package version:
library("remotes")
install_version("profoc", "1.3.4")



Attach the package and use:
library("profoc")
Maintained by
Jonathan Berrisch
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-07-28
Latest Update: 2024-09-21
Description:
Combine probabilistic forecasts using CRPS learning algorithms proposed in Berrisch, Ziel (2021) . The package implements multiple online learning algorithms like Bernstein online aggregation; see Wintenberger (2014) . 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 .
How to cite:
Jonathan Berrisch (2021). profoc: Probabilistic Forecast Combination Using CRPS Learning. R package version 1.3.4, https://cran.r-project.org/web/packages/profoc. Accessed 28 Oct. 2026.
Previous versions and publish date:
(2026-07-09 06:43), 0.8.0 (2021-07-28 13:00), 0.8.3 (2021-08-15 14:20), 0.8.4 (2021-09-15 16:30), 0.8.5 (2021-10-22 16:20), 0.9.0 (2022-02-07 12:00), 0.9.1 (2022-02-25 11:20), 0.9.2 (2022-03-17 13:40), 0.9.3 (2022-04-21 18:30), 0.9.4 (2022-11-30 20:00), 0.9.5 (2022-12-16 11:50), 1.0.0 (2022-12-23 12:30), 1.1.0 (2023-01-13 17:00), 1.1.1 (2023-03-02 08:10), 1.2.0 (2023-06-13 09:30), 1.2.1 (2023-08-25 23:10), 1.3.0 (2024-01-09 21:50), 1.3.1 (2024-01-13 23:10), 1.3.2 (2024-03-25 12:30), 1.3.3 (2024-09-22 00:10)
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