Nonparametric relative error regression estimator under η-weak dependence with geometric rate

In this paper, we present a non-parametric regression approach to study the relationship between two variables. The relative error estimator serves as a more robust alternative to classical regression, particularly under the influence of outliers. First, we present the relative error regression estimator. Next, we then investigate both pointwise and uniform almost complete convergence, along with their rates, under the η-weak dependence condition. Finally, the numerical simulations demonstrate the effectiveness and accuracy of the proposed estimator.

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Publication Details

Journal
Gulf Journal of Mathematics
Published
2025-04-20
DOI
https://doi.org/10.56947/gjom.v19i2.2770
Citations
1
Primary Topic
Advanced Statistical Methods and Models
Type
article
Field-Weighted Citation Impact
2.63
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article

Nonparametric relative error regression estimator under η-weak dependence with geometric rate

Kenza Assia Mezhoud, Sarra Leulmi, Hadjer Djeniba
1 citations
Gulf Journal of Mathematics
Advanced Statistical Methods and Models
2.63
article

Nonparametric relative error regression estimator under η-weak dependence with geometric rate

Kenza Assia Mezhoud, Sarra Leulmi, Hadjer Djeniba
article en
1 citations

Abstract

In this paper, we present a non-parametric regression approach to study the relationship between two variables. The relative error estimator serves as a more robust alternative to classical regression, particularly under the influence of outliers. First, we present the relative error regression estimator. Next, we then investigate both pointwise and uniform almost complete convergence, along with their rates, under the η-weak dependence condition. Finally, the numerical simulations demonstrate the effectiveness and accuracy of the proposed estimator.

Gulf Journal of MathematicsVol. 19(2)
University Frères Mentouri Constantine 1 (DZ), Université Constantine 2 (DZ)
Openalex Percentile: Top 13%
Advanced Statistical Methods and Models
2.63
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