Estimation of sparse directed acyclic graphs for multivariate counts data

DOI10.1111/biom.12467zbMath1390.62263OpenAlexW2409064471WikidataQ31043278 ScholiaQ31043278MaRDI QIDQ2827189

Hua Zhong, Sung Won Han

Publication date: 12 October 2016

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc4975686

zbMATH Keywords

count datadirected acyclic graphBayesian networkpenalized likelihood estimationLasso estimationunknown variable ordering

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Uses Software

• LBFGS-B
• DEseq
• Reactome

Cites Work

• Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs
• Sparse inverse covariance estimation with the graphical lasso
• Sparse permutation invariant covariance estimation
• High-dimensional graphs and variable selection with the Lasso
• PC algorithm for Gaussian copula graphical models
• Model selection and estimation in the Gaussian graphical model
• The multivariate Poisson-log normal distribution
• 10.1162/153244302760200696
• A Limited Memory Algorithm for Bound Constrained Optimization
• Learning Sparse Causal Gaussian Networks With Experimental Intervention: Regularization and Coordinate Descent

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