Structure learning in Bayesian networks using regular vines
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Publication:1659079
DOI10.1016/j.csda.2016.03.003zbMath1466.62097OpenAlexW2296746326MaRDI QIDQ1659079
Arnoldo Frigessi, Ingrid Hobæk Haff, Virginia Lacal, Kjersti Aas
Publication date: 15 August 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2016.03.003
Related Items (6)
Regular vines with strongly chordal pattern of (conditional) independence ⋮ A novel divergence for sensitivity analysis in Gaussian Bayesian networks ⋮ Dependence modelling in ultra high dimensions with vine copulas and the graphical Lasso ⋮ A Bayesian network to analyse basketball players' performances: a multivariate copula-based approach ⋮ Explaining predictive models using Shapley values and non-parametric vine copulas ⋮ Representing Sparse Gaussian DAGs as Sparse R-Vines Allowing for Non-Gaussian Dependence
Uses Software
Cites Work
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