Logo del repository
  1. Home
 
Opzioni

footBayes: Fitting Bayesian and MLE Football Models

Leonardo Egidi
2022
  • other

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
Archivio
https://hdl.handle.net/11368/3026125
https://CRAN.R-project.org/package=footBayes
https://cran.r-project.org/web/packages/footBayes/footBayes.pdf
Diritti
closed access
license:digital rights management non definito
license uri:iris.pri00
FVG url
https://arts.units.it/request-item?handle=11368/3026125
Soggetti
  • statistical modeling

  • football

  • Bayesian inference

  • maximum likelihood es...

google-scholar
Get Involved!
  • Source Code
  • Documentation
  • Slack Channel
Make it your own

DSpace-CRIS can be extensively configured to meet your needs. Decide which information need to be collected and available with fine-grained security. Start updating the theme to match your nstitution's web identity.

Need professional help?

The original creators of DSpace-CRIS at 4Science can take your project to the next level, get in touch!

Realizzato con Software DSpace-CRIS - Estensione mantenuta e ottimizzata da 4Science

  • Impostazioni dei cookie
  • Informativa sulla privacy
  • Accordo con l'utente finale
  • Invia il tuo Feedback