Total positivity in multivariate extremes
From MaRDI portal
Publication:6136578
DOI10.1214/23-aos2272arXiv2112.14727MaRDI QIDQ6136578
Sebastian Engelke, Frank Röttger, Piotr Zwiernik
Publication date: 31 August 2023
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2112.14727
Extreme value theory; extremal stochastic processes (60G70) Positive matrices and their generalizations; cones of matrices (15B48) Probabilistic graphical models (62H22)
Related Items (1)
Cites Work
- OSQP: An Operator Splitting Solver for Quadratic Programs
- Extremes on river networks
- A folded Laplace distribution
- Regular conditional distributions of continuous max-infinitely divisible random fields
- Inverse \(M\)-matrices and ultrametric matrices
- Phylogenetic trees and Euclidean embeddings
- Interpolation of scattered data: distance matrices and conditionally positive definite functions
- Conditional association and unidimensionality in monotone latent variable models
- A general central limit theorem for FKG systems
- Total positivity in exponential families with application to binary variables
- Causal discovery in heavy-tailed models
- Maximum empirical likelihood estimation of the spectral measure of an extreme-value distribu\-tion
- Multivariate generalized Pareto distributions
- Conditional independence among max-stable laws
- Exact tail asymptotics in bivariate scale mixture models
- Extremal dependence measure and extremogram: the regularly varying case
- Properties of Euclidean and non-Euclidean distance matrices
- Classes of orderings of measures and related correlation inequalities. I. Multivariate totally positive distributions
- Positively correlated normal variables are associated
- Correlation inequalities on some partially ordered sets
- Some characterizations of symmetric inverse \(M\)-matrices
- Differentiating the pseudo determinant
- Unifying Markov properties for graphical models
- Maxima of normal random vectors: Between independence and complete dependence
- Domains of attraction of multivariate extreme value distributions
- High-dimensional covariance estimation by minimizing \(\ell _{1}\)-penalized log-determinant divergence
- Total positivity in Markov structures
- Principal component analysis for multivariate extremes
- Effective resistance is more than distance: Laplacians, simplices and the Schur complement
- Locally associated graphical models and mixed convex exponential families
- Inference on extremal dependence in the domain of attraction of a structured Hüsler-Reiss distribution motivated by a Markov tree with latent variables
- Dependence in elliptical partial correlation graphs
- Positive loadings and factor correlations from positive covariance matrices
- Extremal dependence of random scale constructions
- Maximum likelihood estimation in Gaussian models under total positivity
- Estimation of positive definite \(M\)-matrices and structure learning for attractive Gaussian Markov random fields
- Dependence modelling for spatial extremes
- Recent Developments in Discrete Convex Analysis
- Modelling multivariate extreme value distributions
- Variograms for spatial max-stable random fields
- Graphical Models, Exponential Families, and Variational Inference
- Simplicial matrix-tree theorems
- Limit theory for multivariate sample extremes
- Markov chain models for threshold exceedances
- A dependence measure for multivariate and spatial extreme values: Properties and inference
- Factor Copula Models for Replicated Spatial Data
- A Conditional Approach for Multivariate Extreme Values (with Discussion)
- One- versus multi-component regular variation and extremes of Markov trees
- Graphical Models for Extremes
- Maximum likelihood estimation for totally positive log‐concave densities
- Latent tree models
- Optimization Algorithms for Graph Laplacian Estimation via ADMM and MM
- Estimation of Hüsler–Reiss Distributions and Brown–Resnick Processes
- Exact simulation of max-stable processes
- Association of Random Variables, with Applications
- An M-Estimator of Spatial Tail Dependence
- Brownian motion tree models are toric
- Decompositions of dependence for high-dimensional extremes
- Spherical clustering in detection of groups of concomitant extremes
- Geometry of cuts and metrics
- Dependence measures for extreme value analyses
- Structure Learning for Extremal Tree Models
- Total positivity in multivariate extremes
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: Total positivity in multivariate extremes
