Central limit theorem for the kernel estimator of the regression function for censored time series

DOI10.1080/10485252.2011.640678zbMath1244.62056OpenAlexW2135075540MaRDI QIDQ2892932

Elias Ould Saïd, Zohra Guessoum

Publication date: 25 June 2012

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

Full work available at URL: https://doi.org/10.1080/10485252.2011.640678

zbMATH Keywords

predictionstrong mixingnonparametric regressioncensored datalimit distribution

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic distribution theory in statistics (62E20) Asymptotic properties of nonparametric inference (62G20) Censored data models (62N01) Asymptotic properties of parametric tests (62F05)

Related Items (7)

Reweighted Nadaraya-Watson estimation of conditional density function in the right-censored model ⋮ Non parametric estimation of the conditional density function with right-censored and dependent data ⋮ Relative error prediction: Strong uniform consistency for censoring time series model ⋮ Nonparametric \(M\)-estimation for right censored regression model with stationary ergodic data ⋮ A note on estimating the conditional expectation under censoring and association: strong uniform consistency ⋮ Asymptotic normality of the relative error regression function estimator for censored and time series data ⋮ Weighted local polynomial estimations of a non-parametric function with censoring indicators missing at random and their applications

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