Bayesian Network Structure Learning with Permutation Tests

DOI10.1080/03610926.2011.593284zbMath1296.62044arXiv1101.5184OpenAlexW2169030506MaRDI QIDQ3167859

Adriana Brogini, Marco Scutari

Publication date: 29 October 2012

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1101.5184

zbMATH Keywords

Bayesian networkspermutation testsconditional independence testsshrinkage tests

Mathematics Subject Classification ID

Parametric hypothesis testing (62F03) Bayesian inference (62F15) Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence (68T35)

Related Items (3)

Squared error-based shrinkage estimators of discrete probabilities and their application to variable selection ⋮ Efficient feature selection using shrinkage estimators ⋮ Improving the efficiency of genomic selection

Uses Software

• R
• bnlearn

Cites Work

• The max-min hill-climbing Bayesian network structure learning algorithm
• Estimating the dimension of a model
• Introduction to Graphical Modelling
• Testing Statistical Hypotheses
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