Strong consistency result of a non parametric conditional mode estimator under random censorship for functional regressors

DOI10.1080/03610926.2013.867997zbMath1338.62094OpenAlexW2301207336MaRDI QIDQ2811395

Khardani Salah, Thiam Baba

Publication date: 10 June 2016

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2013.867997

zbMATH Keywords

Kaplan-Meier estimatorcensored datafunctional dataalmost complete convergencestrong mixing conditionkernel mode estimator

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Censored data models (62N01) Estimation in survival analysis and censored data (62N02)

Related Items (5)

Asymptotic normality of the regression mode in the nonparametric random design model for censored data ⋮ Non parametric estimations of the conditional density and mode when the regressor and the response are curves ⋮ Strong consistency of local linear estimation of a conditional density function under random censorship ⋮ Unnamed Item ⋮ Strong convergence of the functional nonparametric relative error regression estimator under right censoring

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• Strong uniform consistency of nonparametric estimation of the censored conditional mode function
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• Estimating a distribution function for censored time series data

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