Package: footBayes
Type: Package
Title: Fitting Bayesian and MLE Football Models
Version: 1.0.0
Date: 2025-01-09
Authors@R: c(person(given = "Leonardo",
                      family = "Egidi",
                      role = c("aut", "cre"),
                      email = "legidi@units.it"),
               person(given = c("Roberto", "Macrì"),
                      family = "Demartino",
                      role = "aut"),
               person(given = "Vasilis",
                      family = "Palaskas.",
                      role = "aut"))
Maintainer: Leonardo Egidi <legidi@units.it>
License: GPL-2
Description: 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>.
URL: https://github.com/leoegidi/footbayes
Encoding: UTF-8
SystemRequirements: pandoc (>= 1.12.3), pandoc-citeproc
Depends: R (>= 3.1.0)
Imports: rstan (>= 2.18.1), arm, reshape2, ggplot2, ggridges,
        bayesplot, matrixStats, extraDistr, parallel, metRology, dplyr,
        tidyr, numDeriv, magrittr, rlang
Suggests: testthat, knitr (>= 1.37), rmarkdown (>= 2.10), loo
RoxygenNote: 7.3.2
LazyData: true
BuildManual: yes
NeedsCompilation: no
Packaged: 2025-01-09 15:07:52 UTC; 17245
Author: Leonardo Egidi [aut, cre],
  Roberto Macrì Demartino [aut],
  Vasilis Palaskas. [aut]
Repository: CRAN
Date/Publication: 2025-01-09 15:20:02 UTC
