Robust Gaussian Graphical Modeling Via l1 Penalization

DOI10.1111/j.1541-0420.2012.01785.xzbMath1259.62102OpenAlexW2117411900WikidataQ42522635 ScholiaQ42522635MaRDI QIDQ4911945

Hokeun Sun, Hongzhe Li

Publication date: 20 March 2013

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2012.01785.x

zbMATH Keywords

outliersgenetic networkscoordinate descent algorithmpenalized likelihooditerative proportional fitting

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of graph theory (05C90) Biochemistry, molecular biology (92C40) Genetics and epigenetics (92D10)

Related Items (9)

A general family of trimmed estimators for robust high-dimensional data analysis ⋮ Graphical models via joint quantile regression with component selection ⋮ De-noising analysis of noisy data under mixed graphical models ⋮ Robust sparse Gaussian graphical modeling ⋮ Analysis of noisy survival data with graphical proportional hazards measurement error models ⋮ Learning Gaussian graphical models with fractional marginal pseudo-likelihood ⋮ Estimation of high-dimensional graphical models using regularized score matching ⋮ Robust estimation of sparse precision matrix using adaptive weighted graphical lasso approach ⋮ Dynamic and robust Bayesian graphical models

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