Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/2274
Title: Nonlinear wavelet regression function estimator for censored dependent data
Authors: Fateh Benatia
Djabrane Yahia
Keywords: Censored data; Mean integrated squared error; Nonlinear wavelet-based esti-mator; Nonparametric regression; Strong mixing condition.
Issue Date: 11-Apr-2014
Abstract: 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 α- mixing sequence. Link http://www.ajol.info/index.php/afst/article/view/83627
URI: http://dspace.univ-biskra.dz:8080/jspui/handle/123456789/2274
Appears in Collections:Publications Internationales

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