Semiparametric copula quantile regression for complete or censored data

DOI10.1214/17-EJS1273zbMath1422.62148arXiv1603.07493OpenAlexW2305888676MaRDI QIDQ527093

Mickaël De Backer, Anouar El Ghouch, Ingrid Van Keilegom

Publication date: 16 May 2017

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1603.07493

zbMATH Keywords

kernel smoothingsemiparametric regressioncensored quantile regressionmultidimensional copula modellingpolynomial local-likelihoodprobit transformationsemiparametric vine copulas

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

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High-Dimensional Spatial Quantile Function-on-Scalar Regression ⋮ Robust optimization of mixed CVaR STARR ratio using copulas ⋮ Model-based recursive partitioning algorithm to penalized non-crossing multiple quantile regression for the right-censored data ⋮ On multivariate asymmetric dependence using multivariate skew-normal copula-based regression ⋮ Copula-based regression models with data missing at random ⋮ Expansion for moments of regression quantiles with applications to nonparametric testing ⋮ Semiparametric quantile regression with random censoring ⋮ An Adapted Loss Function for Censored Quantile Regression

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