truelies: Bayesian Methods to Estimate the Proportion of Liars in Coin Flip Experiments

Implements Bayesian methods, described in Hugh-Jones (2019) <doi:10.1007/s40881-019-00069-x>, for estimating the proportion of liars in coin flip-style experiments, where subjects report a random outcome and are paid for reporting a "good" outcome.

Version: 0.2.0
Imports: hdrcde
Suggests: dplyr, ggplot2, MASS, purrr, tidyr
Published: 2019-08-26
Author: David Hugh-Jones
Maintainer: David Hugh-Jones <davidhughjones at gmail.com>
BugReports: https://github.com/hughjonesd/truelies/issues
License: MIT + file LICENSE
URL: https://github.com/hughjonesd/truelies
NeedsCompilation: no
Citation: truelies citation info
Materials: README NEWS
CRAN checks: truelies results

Documentation:

Reference manual: truelies.pdf

Downloads:

Package source: truelies_0.2.0.tar.gz
Windows binaries: r-devel: truelies_0.2.0.zip, r-release: truelies_0.2.0.zip, r-oldrel: truelies_0.2.0.zip
macOS binaries: r-release (arm64): truelies_0.2.0.tgz, r-oldrel (arm64): truelies_0.2.0.tgz, r-release (x86_64): truelies_0.2.0.tgz
Old sources: truelies archive

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