Package: footBayes 2.0.0

footBayes: Fitting Bayesian and MLE Football Models
This is the first package allowing for the estimation, visualization and prediction of the most well-known football models: double Poisson, bivariate Poisson, Skellam, student_t, diagonal-inflated bivariate Poisson, and zero-inflated Skellam. It supports both maximum likelihood estimation (MLE, for 'static' models only) and Bayesian inference. For Bayesian methods, it incorporates several techniques: MCMC sampling with Hamiltonian Monte Carlo, variational inference using either the Pathfinder algorithm or Automatic Differentiation Variational Inference (ADVI), and the Laplace approximation. The package compiles all the 'CmdStan' models once during installation using the 'instantiate' package. The model construction relies on the most well-known football references, such as Dixon and Coles (1997) <doi:10.1111/1467-9876.00065>, Karlis and Ntzoufras (2003) <doi:10.1111/1467-9884.00366> and Egidi, Pauli and Torelli (2018) <doi:10.1177/1471082X18798414>.
Authors:
footBayes_2.0.0.tar.gz
footBayes_2.0.0.zip(r-4.5)footBayes_2.0.0.zip(r-4.4)footBayes_2.0.0.zip(r-4.3)
footBayes_2.0.0.tgz(r-4.5-x86_64)footBayes_2.0.0.tgz(r-4.5-arm64)footBayes_2.0.0.tgz(r-4.4-x86_64)footBayes_2.0.0.tgz(r-4.4-arm64)footBayes_2.0.0.tgz(r-4.3-x86_64)footBayes_2.0.0.tgz(r-4.3-arm64)
footBayes_2.0.0.tar.gz(r-4.5-noble)footBayes_2.0.0.tar.gz(r-4.4-noble)
footBayes_2.0.0.tgz(r-4.4-emscripten)footBayes_2.0.0.tgz(r-4.3-emscripten)
footBayes.pdf |footBayes.html✨
footBayes/json (API)
NEWS
# Install 'footBayes' in R: |
install.packages('footBayes', repos = c('https://leoegidi.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/leoegidi/footbayes/issues
Last updated 7 days agofrom:73fb6d6948. Checks:12 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 16 2025 |
R-4.5-win-x86_64 | OK | Mar 16 2025 |
R-4.5-mac-x86_64 | OK | Mar 16 2025 |
R-4.5-mac-aarch64 | OK | Mar 16 2025 |
R-4.5-linux-x86_64 | OK | Mar 16 2025 |
R-4.4-win-x86_64 | OK | Mar 16 2025 |
R-4.4-mac-x86_64 | OK | Mar 16 2025 |
R-4.4-mac-aarch64 | OK | Mar 16 2025 |
R-4.4-linux-x86_64 | OK | Mar 16 2025 |
R-4.3-win-x86_64 | OK | Mar 16 2025 |
R-4.3-mac-x86_64 | OK | Mar 16 2025 |
R-4.3-mac-aarch64 | OK | Mar 16 2025 |
Exports:btd_footcauchycompare_footfoot_abilitiesfoot_probfoot_rankfoot_round_robinlaplacemle_footnormalplot_btdPosteriorplot_logStrengthpp_footstan_footstudent_t
Dependencies:abindbackportsBHcallrcheckmateclicolorspacecpp11DEoptimRdescdistributionaldplyrextraDistrfansifarverfsgenericsggplot2ggridgesgluegridExtragtableinlineinstantiateisobandlabelinglatticelifecycleloomagrittrMASSMatrixmatrixStatsmetRologymgcvmunsellnlmenumDerivpillarpkgbuildpkgconfigplyrposteriorprocessxpspurrrQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreshape2rlangrobustbaserstanscalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Bayesian Bradley-Terry-Davidson Model | btd_foot |
Compare Football Models using Various Metrics | compare_foot |
English league results 1888-2022 | england |
Plot football abilities from Stan and MLE models | foot_abilities |
Plot football matches probabilities for out-of-sample football matches. | foot_prob |
Rank and points predictions | foot_rank |
Round-robin for football leagues | foot_round_robin |
Italy league results 1934-2022 | italy |
Fit football models with Maximum Likelihood | mle_foot |
Plot Posterior Distributions for 'btdFoot' Objects | plot_btdPosterior |
Plot Rankings for btdFoot Objects | plot_logStrength |
Posterior predictive checks for football models | pp_foot |
Print Method for btdFoot Objects | print.btdFoot |
Print method for compareFoot objects | print.compareFoot |
Print Method for stanFoot Objects | print.stanFoot |
Football priors distributions and options | cauchy laplace normal priors student_t |
Fit football models with Stan | stan_foot |