Adaptively weighted group Lasso for semiparametric quantile regression models
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Publication:2325373
DOI10.3150/18-BEJ1091zbMath1429.62140MaRDI QIDQ2325373
Toshio Honda, Wei-Ying Wu, Ching-Kang Ing
Publication date: 25 September 2019
Published in: Bernoulli (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.bj/1569398767
varying coefficient modelsadditive modelsquantile regressionB-splineLassostructure identificationhigh-dimensional information criteria
Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Asymptotic properties of nonparametric inference (62G20)
Related Items (7)
The information detection for the generalized additive model ⋮ Forward variable selection for sparse ultra-high-dimensional generalized varying coefficient models ⋮ QuantRegGLasso ⋮ Forward variable selection for ultra-high dimensional quantile regression models ⋮ Forward selection for feature screening and structure identification in varying coefficient models ⋮ Penalized kernel quantile regression for varying coefficient models ⋮ Adaptively weighted group Lasso for semiparametric quantile regression models
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