Estimation and variable selection for partially functional linear models

DOI10.1016/j.jkss.2018.05.002zbMath1406.62034OpenAlexW2805157711WikidataQ129750858 ScholiaQ129750858MaRDI QIDQ1622116

Jiang Du, Rui-Yuan Cao, Deng-Ke Xu

Publication date: 12 November 2018

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jkss.2018.05.002

zbMATH Keywords

variable selectionoracle propertycomposite quantile regressionpartially functional linear regression model

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05)

Related Items (7)

Robust estimation with a modified Huber's loss for partial functional linear models based on splines ⋮ Robust estimation for partial functional linear regression models based on FPCA and weighted composite quantile regression ⋮ Functional sufficient dimension reduction based on weighted method ⋮ Functional dimension reduction based on fuzzy partition and transformation ⋮ Partially functional linear quantile regression model and variable selection with censoring indicators MAR ⋮ Nonparametric quantile regression estimation for functional data with responses missing at random ⋮ Unnamed Item

Uses Software

• fda (R)
• pffr

Cites Work

• Unnamed Item
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