Estimation of joint directed acyclic graphs with lasso family for gene networks

DOI10.1080/03610918.2019.1618869zbMath1497.62282OpenAlexW2969027267WikidataQ127727197 ScholiaQ127727197MaRDI QIDQ5082742

SungHwan Kim, Sung-Hoon Park, Sehee Jung, Hua Zhong, Pei Wang, Jeewhan Yoon, Sung Won Han, Jayeon Lim, Eun-Seok Ryu

Publication date: 21 June 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2019.1618869

zbMATH Keywords

Bayesian networkprobabilistic graphical modelLasso estimationstructure equation modeldrug response networkunknown natural ordering

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05) Probabilistic graphical models (62H22)

Uses Software

• glasso
• TETRAD

Cites Work

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• High-dimensional graphs and variable selection with the Lasso
• Joint estimation of multiple high-dimensional precision matrices
• Joint estimation of multiple graphical models
• Model selection and estimation in the Gaussian graphical model
• 10.1162/153244303321897717
• Learning Sparse Causal Gaussian Networks With Experimental Intervention: Regularization and Coordinate Descent
• The Joint Graphical Lasso for Inverse Covariance Estimation Across Multiple Classes

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