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Provides several methods for aggregating probabilistic forecasts. You have a group of people who have made probabilistic forecasts for the same event. You want to take advantage of the "wisdom of the crowd" and combine these forecasts in some sensible way. This package provides implementations of several strategies, including geometric mean of odds, an extremized aggregate (Neyman, Roughgarden (2021) <doi:10.1145/3490486.3538243>), and "high-density trimmed mean" (Powell et al. (2022) <doi:10.1037/dec0000191>).
Version: | 1.0.2 |
Imports: | stats, docstring |
Suggests: | testthat |
Published: | 2023-08-22 |
DOI: | 10.32614/CRAN.package.aggutils |
Author: | Molly Hickman |
Maintainer: | Molly Hickman <molly at forecastingresearch.org> |
BugReports: | https://github.com/forecastingresearch/aggutils/issues |
License: | MIT + file LICENSE |
URL: | https://github.com/forecastingresearch/aggutils |
NeedsCompilation: | no |
CRAN checks: | aggutils results |
Reference manual: | aggutils.pdf |
Package source: | aggutils_1.0.2.tar.gz |
Windows binaries: | r-devel: aggutils_1.0.2.zip, r-release: aggutils_1.0.2.zip, r-oldrel: aggutils_1.0.2.zip |
macOS binaries: | r-release (arm64): aggutils_1.0.2.tgz, r-oldrel (arm64): aggutils_1.0.2.tgz, r-release (x86_64): aggutils_1.0.2.tgz, r-oldrel (x86_64): aggutils_1.0.2.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.