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. The package allows Hamiltonian
Monte Carlo (HMC) estimation through the underlying Stan
environment and Maximum Likelihood estimation (MLE, for
'static' models only). 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>.
| Version: |
0.2.0 |
| Depends: |
R (≥ 3.1.0) |
| Imports: |
rstan (≥ 2.18.1), arm, reshape2, ggplot2, bayesplot, matrixStats, extraDistr, parallel, metRology, dplyr, numDeriv, tidyverse, magrittr |
| Suggests: |
testthat, knitr (≥ 1.37), rmarkdown (≥ 2.10), loo |
| Published: |
2023-08-31 |
| DOI: |
10.32614/CRAN.package.footBayes |
| Author: |
Leonardo Egidi[aut, cre], Vasilis Palaskas[aut]. |
| Maintainer: |
Leonardo Egidi <legidi at units.it> |
| License: |
GPL-2 |
| URL: |
https://github.com/leoegidi/footbayes |
| NeedsCompilation: |
no |
| SystemRequirements: |
pandoc (>= 1.12.3), pandoc-citeproc |
| Materials: |
NEWS |
| In views: |
SportsAnalytics |
| CRAN checks: |
footBayes results |
Documentation:
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