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2022 / March Volume 17 No.1
Consistency result of recursive conditional distribution estimate for dependent data under left truncation, with applications to the conditional quantile
Published Date
2022 / March
Title
Consistency result of recursive conditional distribution estimate for dependent data under left truncation, with applications to the conditional quantile
Author
Fatima Benziadi, Imane Bouazza
Keyword
Nonparametric recursive estimate, Conditional distribution, Left truncation, Conditional quantile, Functional data, α-mixing, Uniform almost sure convergence.
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Pagination
53-81
Abstract
In this paper, we discuss a question that is often asked repeatedly in the context of statistical studies, namely the presence of incomplete data in the dataset. Therefore, our goal is to study the recursive nonparametric estimation of the conditional distribution function of a vectorial response valued variable Y explained by a Hilbertian random variable X=x, based on the double-kernel approach. And because we are always looking for more credible methods that are in line with the research methodology, then, it is well known that the recursive methods are more efficient than its nonrecursive rival. Whereas, the variable of interest Y is left truncated by another variable T, that is, the random variables Y and T are observed if and only if $Y \geqslant T$; otherwise nothing is observed if Y
DOI
10.21915/BIMAS.2022102
https://doi.org/10.21915/BIMAS.2022102
AMS Subject
Classification
62G20, 62G08, 62G35, 62E20.
Received
2022-01-15
Accepted
2022-03-20
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