Bayesian inference for conditional copulas using Gaussian process single index models

DOI10.1016/J.CSDA.2018.01.013zbMath1469.62099OpenAlexW2788099024MaRDI QIDQ1662326

Evgeny Levi, Radu V. Craiu

Publication date: 17 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2018.01.013

zbMATH Keywords

Gaussian processconditional copulasingle index modelcross validated marginal likelihoodsimplifying assumption

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Bayesian inference (62F15) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (6)

A nonparametric Bayesian approach to copula estimation ⋮ A new parametric method of estimating the joint probability density: revisited ⋮ Bayesian Nonparametric Modeling of Conditional Multidimensional Dependence Structures ⋮ Single-index copulas ⋮ Implicit copulas from Bayesian regularized regression smoothers ⋮ Approximate Bayesian conditional copulas

Uses Software

• PRMLT

Cites Work

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