An overview of heavy-tail extensions of multivariate Gaussian distribution and their relations

DOI10.1080/02664763.2022.2044018OpenAlexW4214888347MaRDI QIDQ5044660

Johan Lim, Seongoh Park

Publication date: 2 November 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2022.2044018

zbMATH Keywords

elliptical distributionsscatter matrixgeneralized elliptical distributionsmutual relationsnon-paranormal distributionstranseliptical distributions

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Marčenko-Pastur law for Tyler's M-estimator
• Nonparametric estimation of multivariate elliptic densities via finite mixture sieves
• A characterization of elliptical distributions and some optimality properties of principal components for functional data
• The meta-elliptical distributions with given marginals
• Angular Gaussian and Cauchy estimation
• A normal scale mixture representation of the logistic distribution
• Estimation methods for the multivariate \(t\) distribution
• A generalization of Tyler's M-estimators to the case of incomplete data
• Covariance regularization by thresholding
• A distribution-free M-estimator of multivariate scatter
• Consistency property of elliptical probability density functions
• High-dimensional semiparametric Gaussian copula graphical models
• Optimal tests for elliptical symmetry: specified and unspecified location
• Estimating the effect of joint interventions from observational data in sparse high-dimensional settings
• Estimating high-dimensional covariance and precision matrices under general missing dependence
• Robust sparse covariance estimation by thresholding Tyler's M-estimator
• User-friendly covariance estimation for heavy-tailed distributions
• Robust estimator of the correlation matrix with sparse Kronecker structure for a high-dimensional matrix-variate
• Mean estimation and regression under heavy-tailed distributions: A survey
• Robust and Accurate Inference via a Mixture of Gaussian and Student’s t Errors
• Image denoising using scale mixtures of gaussians in the wavelet domain
• A multivariate version of kendall's τ
• Model-Based Gaussian and Non-Gaussian Clustering
• The Generalization of Student's Ratio
• Robust Shrinkage Estimation of High-Dimensional Covariance Matrices
• Rectified Gaussian Scale Mixtures and the Sparse Non-Negative Least Squares Problem
• ECA: High-Dimensional Elliptical Component Analysis in Non-Gaussian Distributions
• Scale-Invariant Sparse PCA on High-Dimensional Meta-Elliptical Data
• Allometric analysis using the multivariate shifted exponential normal distribution
• Sparse nonparametric graphical models

This page was built for publication: An overview of heavy-tail extensions of multivariate Gaussian distribution and their relations