Estimating spatial quantile regression with functional coefficients: a robust semiparametric framework

DOI10.3150/12-BEJ480zbMath1400.62066arXiv1402.0958MaRDI QIDQ2444662

Longsheng Cheng, Qingguo Tang, Zu-di Lu

Publication date: 10 April 2014

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1402.0958

zbMATH Keywords

quantile regressionasymptotic distributionsspatial datafunctional (varying) coefficient spatial regressionlocal M-estimatorsrobust frameworksoil data analysis

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Random fields; image analysis (62M40) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05)

Related Items

High-Dimensional Spatial Quantile Function-on-Scalar Regression ⋮ Empirical likelihood for nonparametric regression models with spatial autoregressive errors ⋮ Asymptotic theory for varying coefficient regression models with dependent data ⋮ Robust estimation for spatial semiparametric varying coefficient partially linear regression ⋮ Discussion of ``Local quantile regression ⋮ Estimating spatial quantile regression with functional coefficients: a robust semiparametric framework ⋮ Linear quantile regression models for longitudinal experiments: an overview ⋮ Variable selection for spatial semivarying coefficient models ⋮ Nonparametric spatial regression with spatial autoregressive error structure ⋮ Nonparametric M-estimation for functional stationary ergodic data ⋮ The nonparametric estimation of long memory spatio-temporal random field models

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