Package: profoc 1.3.3
profoc: Probabilistic Forecast Combination Using CRPS Learning
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>.
Authors:
profoc_1.3.3.tar.gz
profoc_1.3.3.tar.gz(r-4.5-noble)profoc_1.3.3.tar.gz(r-4.4-noble)
profoc_1.3.3.tgz(r-4.4-emscripten)profoc_1.3.3.tgz(r-4.3-emscripten)
profoc.pdf |profoc.html✨
profoc/json (API)
NEWS
# Install 'profoc' in R: |
install.packages('profoc', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/berrij/profoc/issues
Pkgdown:https://profoc.berrisch.biz
Last updated 3 months agofrom:7c8fdf57f2. Checks:OK: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 21 2024 |
R-4.5-linux-x86_64 | OK | Nov 21 2024 |
Exports:autoplotbatchconlineinit_experts_listmake_basis_matsmake_hat_matsmake_knotsonlineoraclepenaltypost_process_modelsplines2_basistidy
Dependencies:abindclicolorspacefansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadilloRcppProgressrcpptimerrlangscalessplines2tibbleutf8vctrsviridisLitewithr
Introduction
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usingknitr::rmarkdown
on Nov 21 2024.Last update: 2024-01-10
Started: 2023-08-25
Production
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on Nov 21 2024.Last update: 2024-01-10
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Using the C++ Interface
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on Nov 21 2024.Last update: 2024-01-10
Started: 2024-01-10