Probabilistic Forecast Combination Using CRPS Learning

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 < https://github.com/kthohr/optim>.


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Reference manual

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install.packages("profoc")

0.8.4 by Jonathan Berrisch, 9 days ago


https://profoc.berrisch.biz/, https://github.com/BerriJ/profoc


Report a bug at https://github.com/BerriJ/profoc/issues


Browse source code at https://github.com/cran/profoc


Authors: Jonathan Berrisch [cre] , Florian Ziel [aut]


Documentation:   PDF Manual  


Task views: Time Series Analysis


GPL (>= 3) license


Imports Rcpp, Matrix

Suggests testthat, gamlss.dist, ggplot2

Linking to Rcpp, RcppArmadillo, RcppProgress, splines2


See at CRAN