Optimally combined estimation for tail quantile regression

DOI10.5705/ss.2014.051zbMath1372.62024OpenAlexW2592253457MaRDI QIDQ3465106

Huixia Judy Wang, Kehui Wang

Publication date: 28 January 2016

Published in: Statistica Sinica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5705/ss.2014.051

zbMATH Keywords

efficiencyasymptotic distributionsextreme value indexinformation aggregationoptimal weightsregularly varyingjoint-quantile regression

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Asymptotic distribution theory in statistics (62E20) Statistics of extreme values; tail inference (62G32)

Related Items (9)

Inference in functional linear quantile regression ⋮ Extreme value inference for quantile regression with varying coefficients ⋮ GMM quantile regression ⋮ Bayesian joint-quantile regression ⋮ Improving estimation efficiency in quantile regression with longitudinal data ⋮ Estimation of complier expected shortfall treatment effects with a binary instrumental variable ⋮ A two-stage procedure to pool information across quantile levels in linear quantile regression ⋮ Model averaging for multiple quantile regression with covariates missing at random ⋮ Composite versus model-averaged quantile regression

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