Reference

Basic usage functions Basic functions that are used in the R console for model fitting and simple investigations.
bpc()	Bayesian Paired comparison regression models in Stan
summary(<bpc>)	Summary of the model bpc model.
print(<bpc>)	Print method for the bpc object.
predict(<bpc>)	Predict results for new data.
plot(<bpc>)	S3 plot function for the parameter plot of a bpc model This is just a wrapper for the get_parameters_plot function and can be used interchangebly
get_probabilities_df()	Get the empirical win/draw probabilities based on the ability/strength parameters.
get_rank_of_players_df()	Generate a ranking of the ability based on sampling the posterior distribution of the ranks.
Model checking functions These are a thin wrapper over other packages functions to facilitate the investigation of the convergence of the MCMC.
check_convergence_diagnostics()	Run cmdstan diagnostics for convergence and print the results in the screen Thin wrapper over cmdstanr cmdstan_diagnose() function
launch_shinystan()	Tiny wrapper to launch a shinystan app to investigate the MCMC. It launches a shinystan app automatically in the web browser This function requires having rstan and shinystan installed
get_waic()	Tiny wrapper for the WAIC method from the loo package.
get_loo()	Tiny wrapper for the PSIS-LOO-CV method from the loo package.
Publication-ready functions Functions used to generate publication-ready plots and tables.
get_rank_of_players_table()	Publication-ready table for the rank table
get_parameters_table()	Publication-ready table for the parameter estimates
get_probabilities_table()	Publication-ready table for the probabilities
get_parameters_plot()	Return a plot for the parameters estimates based on the HPD interval The returned plot is a caterpillar type of plot
Posterior distribution functions Functions used to investigate the posterior distribution.
get_sample_posterior()	Get the posterior samples for a parameter of the model.
get_rank_of_players_posterior()	Generate a ranking of the ability based on sampling the posterior distribution of the ranks.
get_probabilities_posterior()	Get the posterior of the probabilities
Data Transformation Functions that provide that transformations.
expand_aggregated_data()	Expand aggregated data Several datasets for the Bradley-Terry Model aggregate the number of wins for each player in a different column. The models we provide are intended to be used in a long format. A single result for each contest. This function expands datasets that have aggregated data into this long format.
Datasets Description of the built-in datasets.
tennis_agresti	This is the expansion of the tennis data from Agresti (2003) p.449 This data refers to matches for several women tennis players during 1989 and 1990
brasil_soccer_league	This is a dataset with the results matches fromo the first league of the Brazilian soccer championship from 2017-2019. It was reduced and translatedfrom the adaduque/Brasileirao_Dataset repository
optimization_algorithms	Dataset containing an example of the performance of different optimization algorithms against different benchmark functions. This is a reduced version of the dataset presented at the paper: "Statistical Models for the Analysis of Optimization Algorithms with Benchmark Functions.". For details on how the data was collected we refer to the paper.