Bivariate copula additive models for location, scale and shape

DOI10.1016/j.csda.2017.03.004zbMath1464.62127arXiv1605.07521OpenAlexW2595554554MaRDI QIDQ1654263

Rosalba Radice, Giampiero Marra

Publication date: 7 August 2018

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

Full work available at URL: https://arxiv.org/abs/1605.07521

zbMATH Keywords

copulamarginal distributionadditive predictorsimultaneous parameter estimation

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonparametric estimation (62G05) Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Generalized linear models (logistic models) (62J12)

Related Items (10)

Boosting Distributional Copula Regression ⋮ Introducing Lasso-type penalisation to generalised joint regression modelling for count data ⋮ A joint regression modeling framework for analyzing bivariate binary data in \(\mathsf{R}\) ⋮ Generalised joint regression for count data: a penalty extension for competitive settings ⋮ Copula Link-Based Additive Models for Right-Censored Event Time Data ⋮ Modular regression -- a Lego system for building structured additive distributional regression models with tensor product interactions ⋮ SemiParBIVProbit ⋮ Generalized Additive Models for Pair-Copula Constructions ⋮ A trivariate additive regression model with arbitrary link functions and varying correlation matrix ⋮ Correcting for sample selection bias in Bayesian distributional regression models

Uses Software

• R
• VGAM
• gss
• SemiPar
• mgcv
• copula
• GAMLSS
• CDVine
• gamair
• numDeriv
• trust
• copula
• CopulaRegression
• MSwM
• gamCopula

Cites Work

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