A Bayesian network to analyse basketball players' performances: a multivariate copula-based approach

DOI10.1007/s10479-022-04871-5MaRDI QIDQ6115873

Vincenzina Vitale, Pierpalo D'Urso, Livia De Giovanni

Publication date: 13 July 2023

Published in: Annals of Operations Research (Search for Journal in Brave)

zbMATH Keywords

Bayesian networksGaussian copulamultivariate dependencefour factorsbasketball data

Mathematics Subject Classification ID

Statistics (62-XX) Artificial intelligence (68Txx) Multivariate analysis (62Hxx)

Cites Work

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• Measuring the efficiency of NBA teams: additive efficiency decomposition in two-stage DEA
• Copula directed acyclic graphs
• The max-min hill-climbing Bayesian network structure learning algorithm
• Mining and visualising ordinal data with non-parametric continuous BBNs
• Graphical models for associations between variables, some of which are qualitative and some quantitative
• Causation, prediction, and search
• A Bayesian method for the induction of probabilistic networks from data
• Structure learning in Bayesian networks using regular vines
• High-dimensional semiparametric Gaussian copula graphical models
• Modelling an energy market with Bayesian networks for non-normal data
• A continuous-time stochastic block model for basketball networks
• PC algorithm for Gaussian copula graphical models
• Pair-copula constructions for non-Gaussian DAG models
• Uncertainty Analysis with High Dimensional Dependence Modelling
• A Tutorial on Learning with Bayesian Networks
• Probabilistic Networks and Expert Systems
• Independence properties of directed markov fields
• Modeling Offensive Player Movement in Professional Basketball

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