braggR: Calculate the Revealed Aggregator of Probability Predictions

Forecasters predicting the chances of a future event may disagree due to differing evidence or noise. To harness the collective evidence of the crowd, Ville Satopää (2021) "Regularized Aggregation of One-off Probability Predictions" <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3769945> proposes a Bayesian aggregator that is regularized by analyzing the forecasters' disagreement and ascribing over-dispersion to noise. This aggregator requires no user intervention and can be computed efficiently even for a large numbers of predictions. The author evaluates the aggregator on subjective probability predictions collected during a four-year forecasting tournament sponsored by the US intelligence community. The aggregator improves the accuracy of simple averaging by around 20% and other state-of-the-art aggregators by 10-25%. The advantage stems almost exclusively from improved calibration. This aggregator – know as "the revealed aggregator" – inputs a) forecasters' probability predictions (p) of a future binary event and b) the forecasters' common prior (p0) of the future event. In this R-package, the function sample_aggregator(p,p0,...) allows the user to calculate the revealed aggregator. Its use is illustrated with a simple example.

Version: 0.1.1
Imports: Rcpp
LinkingTo: Rcpp
Suggests: testthat (≥ 3.0.0)
Published: 2021-05-29
Author: Ville Satopää [aut, cre, cph]
Maintainer: Ville Satopää <ville.satopaa at gmail.com>
License: GPL-2
Copyright: (c) Ville Satopaa
NeedsCompilation: yes
Citation: braggR citation info
Materials: README
CRAN checks: braggR results

Documentation:

Reference manual: braggR.pdf

Downloads:

Package source: braggR_0.1.1.tar.gz
Windows binaries: r-devel: braggR_0.1.1.zip, r-release: braggR_0.1.1.zip, r-oldrel: braggR_0.1.1.zip
macOS binaries: r-release (arm64): braggR_0.1.1.tgz, r-oldrel (arm64): braggR_0.1.1.tgz, r-release (x86_64): braggR_0.1.1.tgz, r-oldrel (x86_64): braggR_0.1.1.tgz
Old sources: braggR archive

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