Probabilistic Forecast Combination Using CRPS Learning R package profoc version 1.3.4 CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries) Combine probabilistic forecasts using CRPS learning algorithms proposed in Berrisch, Ziel (2021) <doi:10.48550/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) <doi:10.48550/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>. Software Depends: R (>= 4.3.0) Imports: Rcpp (>= 1.0.5), Matrix, abind, methods, lifecycle, generics, tibble, ggplot2 LinkingTo: Rcpp, RcppArmadillo (>= 0.10.7.5.0), RcppProgress, splines2 (>= 0.4.4), rcpptimer (>= 1.2.0) Suggests: testthat (>= 3.0.0), gamlss.dist, knitr, rmarkdown, dplyr, rcpptimer (>= 1.2.0), Jonathan Berrisch <Jonathan@Berrisch.biz> Comprehensive R Archive Network (CRAN) Jonathan Berrisch [aut, cre] (ORCID: <https://orcid.org/0000-0002-4944-9074>), Florian Ziel [aut] (ORCID: <https://orcid.org/0000-0002-2974-2660>) GPL (>= 3) 2026-01-23 application/tgz https://CRAN.R-project.org/package=profoc doi:10.32614/CRAN.package.profoc en-US