PenPC : A two-step approach to estimate the skeletons of high-dimensional directed acyclic graphs

DOI10.1111/biom.12415zbMath1393.62065arXiv1405.1603OpenAlexW2127491240WikidataQ27314773 ScholiaQ27314773MaRDI QIDQ2805190

Jichun Xie, Min Jin Ha, Wei Sun

Publication date: 10 May 2016

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1405.1603

zbMATH Keywords

penalized regressionskeletonPC-algorithmDAGlog penaltyhigh-dimensional directed acyclic graphs

Mathematics Subject Classification ID

Multivariate analysis (62H99) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items

Unnamed Item ⋮ Risk spillover network structure learning for correlated financial assets: a directed acyclic graph approach ⋮ Nonlinear directed acyclic graph estimation based on the kernel partial correlation coefficient ⋮ Sparse directed acyclic graphs incorporating the covariates ⋮ Model free estimation of graphical model using gene expression data ⋮ Learning Moral Graphs in Construction of High-Dimensional Bayesian Networks for Mixed Data ⋮ High-dimensional consistency in score-based and hybrid structure learning ⋮ Bayesian Structure Learning in Multilayered Genomic Networks

Uses Software

• pcalg
• PenPC

Cites Work

• Penalized likelihood methods for estimation of sparse high-dimensional directed acyclic graphs
• Designing penalty functions in high dimensional problems: the role of tuning parameters
• \(\ell_{0}\)-penalized maximum likelihood for sparse directed acyclic graphs
• The max-min hill-climbing Bayesian network structure learning algorithm
• Estimating high-dimensional intervention effects from observational data
• Learning Bayesian networks: The combination of knowledge and statistical data
• High-dimensional graphs and variable selection with the Lasso
• High-dimensional learning of linear causal networks via inverse covariance estimation
• Emergence of Scaling in Random Networks
• SparseNet: Coordinate Descent With Nonconvex Penalties
• Extended Bayesian information criteria for model selection with large model spaces
• The Maximum Degree of the Barabási–Albert Random Tree
• 10.1162/153244303321897717
• Nonconcave Penalized Likelihood With NP-Dimensionality
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item