PC Translation Models for Random Vectors and Multivariate Extremes

DOI10.1137/18M118061XzbMath1411.60011OpenAlexW2941858295WikidataQ127985623 ScholiaQ127985623MaRDI QIDQ5376557

Mircea D. Grigoriu

Publication date: 13 May 2019

Published in: SIAM Journal on Scientific Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/18m118061x

zbMATH Keywords

Monte Carlospectral measuredependencepolynomial chaostail independence

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Measures of association (correlation, canonical correlation, etc.) (62H20) Convergence of probability measures (60B10) Limit theorems for vector-valued random variables (infinite-dimensional case) (60B12) Multivariate analysis and fuzziness (62H86)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Identification of high-dimension polynomial chaos expansions with random coefficients for non-Gaussian tensor-valued random fields using partial and limited experimental data
• Polynomial chaos representation of spatio-temporal random fields from experimental measurements
• Extremes and related properties of random sequences and processes
• Introduction to stochastic integration.
• Asymptotic Sampling Distribution for Polynomial Chaos Representation from Data: A Maximum Entropy and Fisher Information Approach
• Parametrization of Random Vectors in Polynomial Chaos Expansions via Optimal Transportation
• The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
• On the foundations of multivariate heavy-tail analysis
• Nonparametric estimation of copula functions for dependence modelling
• Heavy-Tail Phenomena
• Remarks on a Multivariate Transformation
• Optimal Transport