Title: Calculate Pi Ratings for Teams Competing in Sport Matches
Maintainer: Lars Van Cutsem <lars.vancutsem@hotmail.com>
Description: Calculate and optimize dynamic performance ratings of association football
teams competing in matches, in accordance with the method used in
the research paper "Determining the level of ability of football teams by
dynamic ratings based on the relative discrepancies in scores between adversaries",
This dynamic rating system has proven to provide superior
results for predicting association football outcomes.

Title: Create a Bayesian Posterior from a Phylogeny
person("Giovanni", "Laudanno", email = "glaudanno@gmail.com",   role = "aut"),
Theoretical biologists are interested in measuring the extent
at which we can measure the truth. This package allows to
create a Bayesian posterior from a phylogeny that depicts
the true evolutionary relationships. The given and true phylogeny
can than be compared to the posterior phylogenies.
Richèl J. C. Bilderbeek, Giovanni Laudanno, Rampal S. Etienne (2020)
"Quantifying the impact of an inference model in Bayesian phylogenetics"
Imports: ape, beautier (>= 2.6.2), beastier (>= 2.4.6), DDD, forcats,
magrittr, mauricer (>= 2.5), mcbette (>= 1.7), nodeSub,
phangorn, phytools, plyr, pryr, rappdirs, readr, stringr, TESS,
tibble, tidyr, tracerer (>= 2.0.2), xtable
Suggests: devtools, dplyr, ggplot2, knitr, lintr, markdown, nLTT (>=
1.4.3), rmarkdown, Rmpfr, testthat (>= 2.1.0)

phangorn, phytools, plyr, pryr, readr, stringr, TESS, tibble,
1.4.3), rappdirs, rmarkdown, Rmpfr, testthat (>= 2.1.0)

Title: Small Example Response and Response Time Data from PISA 2015
person("Esther", "Ulitzsch", email = "ulitzsch@ipn.uni-kiel.de", role = c("ctb")),
person("Christoph", "Koenig", email = "koenig@psych.uni-frankfurt.de", role = c("ctb")))
Description: Scored responses and responses times from the Canadian subsample of the PISA 2015 assessment, accessible as the "Cognitive Item Data File" by OECD (2016) <https://www.oecd.org/pisa/data/2015database/>.