Approximate likelihood with proxy variables for parameter estimation in high-dimensional factor copula models

DOI10.1007/s00362-021-01252-1OpenAlexW3194623631MaRDI QIDQ2122830

Pavel Krupskii, Joe, Harry

Publication date: 7 April 2022

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-021-01252-1

zbMATH Keywords

maximum likelihood estimationconditional independencetail dependencetail asymmetry

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

High-dimensional factor copula models with estimation of latent variables ⋮ Copula modeling from Abe Sklar to the present day

Uses Software

• R

Cites Work

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• Factor copula models for multivariate data
• Strength of tail dependence based on conditional tail expectation
• Tail order and intermediate tail dependence of multivariate copulas
• Parsimonious parameterization of correlation matrices using truncated vines and factor analysis
• Copula-based measures of reflection and permutation asymmetry and statistical tests
• Generalized autoregressive conditional heteroscedasticity
• Structured factor copula models: theory, inference and computation
• Linear factor copula models and their properties
• Parsimonious graphical dependence models constructed from vines
• Tail-weighted measures of dependence
• Simulated Method of Moments Estimation for Copula-Based Multivariate Models

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