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Strong convergence of the functional nonparametric relative error regression estimator under right censoring

  • Omar Fetitah , Ibrahim M. Almanjahie , Mohammed Kadi Attouch EMAIL logo and Ali Righi
Published/Copyright: December 10, 2020
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Abstract

In this paper, we investigate the asymptotic properties of a nonparametric estimator of the relative error regression given a functional explanatory variable, in the case of a scalar censored response, we use the mean squared relative error as a loss function to construct a nonparametric estimator of the regression operator of these functional censored data. We establish the strong almost complete convergence rate and asymptotic normality of these estimators. A simulation study is performed to illustrate and compare the higher predictive performances of our proposed method to those obtained with standard estimators.

MSC 2010: 62G05; 62G08; 62G20; 62G35; 62N01

The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through the Research Groups Program under grant number R.G.P. 2/67/41.


Acknowledgement

The authors would like to thank the anonymous reviewers for their valuable comments and suggestions which improved substantially the quality of this paper.

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Received: 2019-04-06
Accepted: 2020-05-06
Published Online: 2020-12-10
Published in Print: 2020-12-16

© 2020 Mathematical Institute Slovak Academy of Sciences

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