EloSteepness: Bayesian Dominance Hierarchy Steepness via Elo Rating and David's Scores

Obtain Bayesian posterior distributions of dominance hierarchy steepness (Neumann and Fischer (2022) <doi:10.1101/2022.01.28.478016>). Steepness estimation is based on Bayesian implementations of either Elo-rating or David's scores.

Version: 0.4.6
Depends: R (≥ 3.5.0), EloRating
Imports: methods, Rcpp (≥ 0.12.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), rstantools (≥ 2.1.1), aniDom
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥, RcppParallel (≥ 5.0.1), rstan (≥ 2.18.1), StanHeaders (≥ 2.18.0)
Suggests: rmarkdown, bookdown, xtable, knitr, testthat (≥ 3.0.0)
Published: 2022-10-11
Author: Christof Neumann ORCID iD [aut, cre]
Maintainer: Christof Neumann <christofneumann1 at gmail.com>
BugReports: https://github.com/gobbios/EloSteepness/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/gobbios/EloSteepness
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README
CRAN checks: EloSteepness results


Reference manual: EloSteepness.pdf
Vignettes: tutorial


Package source: EloSteepness_0.4.6.tar.gz
Windows binaries: r-devel: EloSteepness_0.4.6.zip, r-release: EloSteepness_0.4.6.zip, r-oldrel: EloSteepness_0.4.6.zip
macOS binaries: r-release (arm64): EloSteepness_0.4.6.tgz, r-oldrel (arm64): EloSteepness_0.4.6.tgz, r-release (x86_64): EloSteepness_0.4.6.tgz, r-oldrel (x86_64): EloSteepness_0.4.6.tgz
Old sources: EloSteepness archive


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