High-dimensional rank-based graphical models for non-Gaussian functional data

DOI10.1080/02331888.2023.2201009OpenAlexW4366829352MaRDI QIDQ6044815

Eftychia Solea, Unnamed Author

Publication date: 22 May 2023

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888.2023.2201009

zbMATH Keywords

Kendall's taugraphical modelsGaussian copulaLassofunctional data

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Sparse inverse covariance estimation with the graphical lasso
• Innovated scalable efficient estimation in ultra-large Gaussian graphical models
• From sparse to dense functional data and beyond
• Regularized rank-based estimation of high-dimensional nonparanormal graphical models
• Sparsistency and rates of convergence in large covariance matrix estimation
• High-dimensional semiparametric Gaussian copula graphical models
• Sparse permutation invariant covariance estimation
• High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence
• Nonparametric and high-dimensional functional graphical models
• High-dimensional graphs and variable selection with the Lasso
• A Constrainedℓ₁Minimization Approach to Sparse Precision Matrix Estimation
• Emergence of Scaling in Random Networks
• A Nonparametric Graphical Model for Functional Data With Application to Brain Networks Based on fMRI
• Ordinal Measures of Association
• Model selection and estimation in the Gaussian graphical model
• Joint Measures and Cross-Covariance Operators
• On an Additive Semigraphoid Model for Statistical Networks With Application to Pathway Analysis
• Partial separability and functional graphical models for multivariate Gaussian processes
• Doubly functional graphical models in high dimensions
• Functional Graphical Models
• Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators
• Partial Correlation Estimation by Joint Sparse Regression Models
• Probability Inequalities for Sums of Bounded Random Variables
• On an additive partial correlation operator and nonparametric estimation of graphical models
• Graph estimation with joint additive models
• Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima
• Copula Gaussian Graphical Models for Functional Data
• A unified framework for high-dimensional analysis of \(M\)-estimators with decomposable regularizers
• Nonparametric Functional Graphical Modeling Through Functional Additive Regression Operator