Quantile regression and its empirical likelihood with missing response at random
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Publication:725686
DOI10.1007/s00362-016-0784-5zbMath1407.62142OpenAlexW2464519878MaRDI QIDQ725686
Publication date: 2 August 2018
Published in: Statistical Papers (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00362-016-0784-5
asymptotic normalityquantile regressionmissing at randomempirical likelihoodmaximum empirical likelihood estimation
Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Linear regression; mixed models (62J05) Nonparametric estimation (62G05)
Related Items (10)
Statistical inferences for varying coefficient partially non linear model with missing covariates ⋮ Quantile regression of ultra-high dimensional partially linear varying-coefficient model with missing observations ⋮ Change point estimation in regression model with response missing at random ⋮ Empirical likelihood in single-index partially functional linear model with missing observations ⋮ Weighted quantile regression for censored data with application to export duration data ⋮ Robust estimation of single index models with responses missing at random ⋮ Feature screening for ultrahigh-dimensional survival data when failure indicators are missing at random ⋮ Goodness-of-fit tests for quantile regression with missing responses ⋮ Quantile regression of partially linear single-index model with missing observations ⋮ Nonparametric estimation of expectile regression in functional dependent data
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