Selection of sparse vine copulas in high dimensions with the Lasso

DOI10.1007/s11222-018-9807-5zbMath1430.62102arXiv1705.05877OpenAlexW2616758160WikidataQ130069089 ScholiaQ130069089MaRDI QIDQ2329765

Dominik Müller, Claudia Czado

Publication date: 18 October 2019

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1705.05877

zbMATH Keywords

sparsityLassodependence modelingvine copula

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items

Regular vines with strongly chordal pattern of (conditional) independence, Dependence modelling in ultra high dimensions with vine copulas and the graphical Lasso, Pair-copula models for analyzing family data, Model selection in sparse high-dimensional vine copula models with an application to portfolio risk, Dependence structure estimation using copula recursive trees, Copula shrinkage and portfolio allocation in ultra-high dimensions

Uses Software

• glasso
• glmnet
• VineCopula
• CDVine
• GitHub
• CopulaModel

Cites Work

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