Efficient estimation in the partially linear quantile regression model for longitudinal data

DOI10.1214/18-EJS1409zbMath1401.62061OpenAlexW2790004130MaRDI QIDQ1746542

Hyunkeun Ryan Cho, Seon Jin Kim

Publication date: 25 April 2018

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

Full work available at URL: https://projecteuclid.org/euclid.ejs/1520046230

zbMATH Keywords

kernel smoothingsemiparametric regressionquantile regressionempirical likelihoodquadratic inference function

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

Related Items (5)

A difference-based approach in the partially linear model with dependent errors ⋮ Improved multiple quantile regression estimation with nonignorable dropouts ⋮ Bayesian empirical likelihood of quantile regression with missing observations ⋮ Weighted quantile regression in varying-coefficient model with longitudinal data ⋮ Semiparametric inference for the scale-mixture of normal partial linear regression model with censored data

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