Nonparametric robust regression estimation for censored data

In this paper, we consider a robust regression estimator when the interest random variable is subject to random right-censoring. Based on the so-called synthetic data, we define a new kernel estimator. Under classical conditions and using a VC-classes theory, we establish its uniform consistency wit...

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Bibliographic Details
Published in:Statistical papers (Berlin, Germany) Germany), 2017-06, Vol.58 (2), p.505-525
Main Authors: Lemdani, Mohamed, Ould Saïd, Elias
Format: Article
Language:English
Subjects:
Asymptotic properties
Censored data (mathematics)
Economic models
Economic Theory/Quantitative Economics/Mathematical Methods
Economics
Finance
Insurance
Management
Mathematics and Statistics
Nonparametric statistics
Normality
Operations Research/Decision Theory
Probability Theory and Stochastic Processes
Random variables
Regression analysis
Regular Article
Robustness (mathematics)
Statistics
Statistics for Business
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Summary:In this paper, we consider a robust regression estimator when the interest random variable is subject to random right-censoring. Based on the so-called synthetic data, we define a new kernel estimator. Under classical conditions and using a VC-classes theory, we establish its uniform consistency with rate and asymptotic normality properties. Special cases are studied and simulations are drawn to illustrate the main results.
ISSN:0932-5026
1613-9798
DOI:10.1007/s00362-015-0709-8