Influence measures and stability for graphical models

DOI10.1016/j.jmva.2016.01.006zbMath1384.62208OpenAlexW2291828424MaRDI QIDQ272066

Avner Bar-Hen, Jean-Michel Poggi

Publication date: 20 April 2016

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2016.01.006

zbMATH Keywords

robustnessgraphical modelinfluence measure

Mathematics Subject Classification ID

Multivariate analysis (62H99) Nonparametric robustness (62G35) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

Uses Software

• igraph
• glasso
• huge
• GGMselect
• Bolasso

Cites Work

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• Graph Selection with GGMselect
• Sparse inverse covariance estimation with the graphical lasso
• Lasso-type recovery of sparse representations for high-dimensional data
• Limit behavior of the empirical influence function of the median
• Stable graphical model estimation with random forests for discrete, continuous, and mixed variables
• Inferring sparse Gaussian graphical models with latent structure
• High-dimensional graphs and variable selection with the Lasso
• Empirical φ∗-Divergence Minimizers for Hadamard Differentiable Functionals
• Robust estimators for nondecomposable elliptical graphical models
• Asymptotic Statistics
• Stability Selection
• On the estimation of the influence curve
• The huge Package for High-dimensional Undirected Graph Estimation in R

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