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. 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) , Karlis and Ntzoufras (2003) and Egidi, Pauli and Torelli (2018) . Copyright: GPL-2

footBayes: Fitting Bayesian and MLE Football Models

Leonardo Egidi
2022-01-01

Abstract

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. 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) , Karlis and Ntzoufras (2003) and Egidi, Pauli and Torelli (2018) . Copyright: GPL-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/3026125
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