The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
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 |
| Reference manual: | braggR.pdf |
| 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 |
Please use the canonical form https://CRAN.R-project.org/package=braggR to link to this page.
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.
Health stats visible at Monitor.