Nonparametric test for checking lack of fit of the quantite regression model under random censoring

DOI10.1002/CJS.5550360209zbMath1144.62032OpenAlexW2013324221MaRDI QIDQ3526433

Lan Wang

Publication date: 25 September 2008

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

Full work available at URL: https://doi.org/10.1002/cjs.5550360209

zbMATH Keywords

random censoringmodel checkingconditional moment

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Censored data models (62N01) Testing in survival analysis and censored data (62N03)

Related Items (9)

Assessing quantile prediction with censored quantile regression models ⋮ An updated review of goodness-of-fit tests for regression models ⋮ Posterior Inference in Bayesian Quantile Regression with Asymmetric Laplace Likelihood ⋮ Median regression model with left truncated and right censored data ⋮ Median regression model with doubly truncated data ⋮ Multiple Imputation forM-Regression With Censored Covariates ⋮ Inference of time-varying regression models ⋮ Nonparametric inference of quantile curves for nonstationary time series ⋮ Testing for jumps in the presence of smooth changes in trends of nonstationary time series

Cites Work

• Central limit theorem for integrated square error of multivariate nonparametric density estimators
• Least absolute deviations estimation for the censored regression model
• Empirical likelihood inference for median regression models for censored survival data
• Quantile regression under random censoring.
• A simple nonparametric test for diagnosing nonlinearity in Tobit median regression model
• Regression with censored data
• Asymptotic Statistics
• Non-Parametric Analysis of Covariance
• Censored Regression Quantiles
• A Lack-of-Fit Test for Quantile Regression
• Censored Median Regression Using Weighted Empirical Survival and Hazard Functions
• Median regression using nonparametric kernel estimation
• SEMIPARAMETRIC ESTIMATION OF A PARTIALLY LINEAR CENSORED REGRESSION MODEL
• Survival Analysis with Median Regression Models
• Non‐parametric Quantile Regression with Censored Data

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