Package: aggutils 2.0.0

Molly Hickman

aggutils: Utilities for Aggregating Probabilistic Forecasts

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>).

Authors:Molly Hickman [aut, cre], Zach Jacobs [aut]

aggutils_2.0.0.tar.gz
aggutils_2.0.0.zip(r-4.5)aggutils_2.0.0.zip(r-4.4)aggutils_2.0.0.zip(r-4.3)
aggutils_2.0.0.tgz(r-4.5-any)aggutils_2.0.0.tgz(r-4.4-any)aggutils_2.0.0.tgz(r-4.3-any)
aggutils_2.0.0.tar.gz(r-4.5-noble)aggutils_2.0.0.tar.gz(r-4.4-noble)
aggutils_2.0.0.tgz(r-4.4-emscripten)aggutils_2.0.0.tgz(r-4.3-emscripten)
aggutils.pdf |aggutils.html
aggutils/json (API)

# Install 'aggutils' in R:
install.packages('aggutils', repos = c('https://forecastingresearch.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/forecastingresearch/aggutils/issues

On CRAN:

Conda:

2.48 score 3 stars 3 scripts 260 downloads 6 exports 30 dependencies

Last updated 1 years agofrom:ef4d5e488b. Checks:1 OK, 8 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 18 2025
R-4.5-winNOTEMar 18 2025
R-4.5-macNOTEMar 18 2025
R-4.5-linuxNOTEMar 18 2025
R-4.4-winNOTEMar 18 2025
R-4.4-macNOTEMar 18 2025
R-4.4-linuxNOTEMar 18 2025
R-4.3-winNOTEMar 18 2025
R-4.3-macNOTEMar 18 2025

Exports:geoMeanCalcgeoMeanOfOddsCalchd_trimneymanAggCalcsoften_meantrim

Dependencies:brewcallrclicommonmarkcpp11descdocstringevaluatefsgluehighrknitrlifecyclemagrittrpkgbuildpkgloadprocessxpspurrrR6rlangroxygen2rprojrootstringistringrvctrswithrxfunxml2yaml