Asymptotic properties of wavelet estimators in a semiparametric regression model with censored data

DOI10.1007/s11859-012-0844-1zbMath1274.62287OpenAlexW2128344910MaRDI QIDQ4925969

Yuan Feng, Hong Chang Hu

Publication date: 20 June 2013

Published in: Wuhan University Journal of Natural Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11859-012-0844-1

zbMATH Keywords

asymptotic normalityconvergence rate in probability

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Censored data models (62N01) Numerical methods for wavelets (65T60)

Cites Work

• Functional laws of the iterated logarithm for the product-limit estimator of a distribution function under random censorship or truncation
• Wavelet estimation of partially linear models
• Convergence rates for partially splined models
• Convergence rates for parametric components in a partly linear model
• A class of estimators of the parameters in linear regression with censored data
• Regression analysis with randomly right-censored data
• Asymptotic properties for the semiparametric regression model with randomly censored data
• Robust estimators in semiparametric partly linear regression models.
• Ridge estimation of a semiparametric regression model
• Empirical likelihood semiparametric regression analysis under random censorship
• Asymptotic properties for estimation of partial linear models with censored data
• Smoothing spline based tests for nonlinearity in a partially linear model
• Strong Convergence Rates of Wavelet Estimators in Semiparametric Regression Models with Censored Data*
• Asymptotic normality in a Semiparametric partially linear model with right–censored data
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