Afrika Statistika

Nonlinear wavelet regression function estimator for censored dependent data

Fateh Benatia and Djabrane Yahia

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Abstract

Let $(Y,C,X)$ be a vector of random variables where $Y,$ $C$ and $X$ are, respectively, the interest variable, a right censoring and a covariable (predictor). In this paper, we introduce a new nonlinear wavelet-based estimator of the regression function in the right censorship model. An asymptotic expression for the mean integrated squared error of the estimator is obtained to both continuous and discontinuous curves. It is assumed that the lifetime observations form a stationary $\alpha-$mixing sequence.

Article information

Source
Afr. Stat., Volume 7, Number 1 (2012), 391-411.

Dates
First available in Project Euclid: 1 February 2013

Permanent link to this document
https://projecteuclid.org/euclid.as/1359744265

Mathematical Reviews number (MathSciNet)
MR3034386

Zentralblatt MATH identifier
1258.62046

Subjects
Primary: 62G07: Density estimation 62G20: Asymptotic properties

Keywords
Censored data Mean integrated squared error Nonlinear wavelet-based estimator Nonparametric regression Strong mixing

Citation

Yahia, Djabrane; Benatia, Fateh. Nonlinear wavelet regression function estimator for censored dependent data. Afr. Stat. 7 (2012), no. 1, 391--411. https://projecteuclid.org/euclid.as/1359744265


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