Roadmap

TODO: New models being analyzed:
- Add new models for modeling time effects (newer contests have higher impact on the ability than older contests)
- Add model for the Bayesian ELO-type rating system
- Add Glicko and Glicko2 models
- Add models for cumulative comparisons

TODO: Get posterior distribution of the parameters without accessing the stanfit object
TODO: integration with bayesplot to get some of the nice plots that we see there

bpcs 1.2.2

fixing problems with solve_ties when the ties where provided directly (and not as two separate score issue #8

Ability to add credibility mass and choose HDPI or credible intervals in print and in summary
New function check_convergence_diagnostics for HMC diagnostics. This is printed as default in print but not in summary

Moving to cmdstanr instead of rstan.
- This will allow us to fix some bugs and tweaks that were not optimal.
- Now we can have faster installations and let cmdstan compile the models.
- There will be some additional time to compile the models for the first time but that is only the first time we use it
- We can now remove the errors from ubsan-clang in CRAN which apparently is a lot of trial and error to solve and not supporting tools from CRAN for identifying that
The interface of the bpcs will remain (practically) the same
new function to retrieve the posterior distribution of the parameters get_parameters_posterior
alias to retrieve the summary data frame of the parameters get_parameters_df
Removed dependency on coda
Now we can specify the probability mass in the parameters and in summary
rstan and shinystan are now optional
Fix problems with multiple clusters in the posterior predictive function

Possibility to add up to 3 intercept random effects (hopefully you will never need more than that)
Model for subject predictors (see example on the paper)
Make predictions of submodels with the model_type option (see example on the paper)
Some small bug fixes

removed ties_pred from models that do not have ties and from the stan models.
fixed predict for models with ties, so we return a vector y_pred with 0, 1, 2 and not separate as now
removed posterior distributions from the get_rank_of_players and get_probabilities. Now we have new functions to obtain the data frame or the posterior distributions separately. The posterior is now returned as matrix
Probabilities table is now optional in the summary function
New functions to get the probabilities for specific data get_probabilities_newdata_df and get_probabilities_newdata_posterior
Publication ready functions for
- plots: get_parameters_plot function and a thin S3 plot wrapper for the same function. Plots are default to APA.
- tables: Functions for publication tables: get_parameter_table, get_probabilities_table and get_rank_of_players_table
get_hpdi_parameters became get_parameters and the user specify if credible intervals or hpdi
Added ties to expand_aggregated_data.
We can get now both credible and HPD intervals in get_parameters. n_eff and Rhat are also now possible to add and remove from this df
Added functions to save and load bpc models

Package is feature complete and reached version 1.0.0
Test coverage > 80%
Bayesian computation of different variations of the Bradley-Terry and the Davidson model to handle ties in the contest (including with home advantage, random effects and the generalized model).
Input accepts a column with the results of the contest or the scores for each player.
Customize a normal prior distribution for every parameter.
Compute HDP interval for every parameter with the get_hpdi_parameters function
Compute rank of the players with the get_rank_of_players function.
Compute all the probability combinations for one player beating the other with the get_probabilities function.
Convert aggregated tables of results into long format (one contest per row) with the expand_aggregated_data.
Obtain the posterior distribution for every parameter of the model with the get_sample_posterior function.
Easy predictions using the predict function.
We do not reinforce any table or plotting library! Results are returned as data frames for easier plotting and creating tables
We reinforce the need to manually specify the model to be used.
Full documentation available at the package site
Dependence on Stan >= 2.20 for faster compilation times
Removing vignettes from building with the package. Now they are available only in the package website