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Research Article | Open Access

Weighted expectile average estimation based on CBPS with responses missing at random

Qiang Zhao1, Zhaodi Wang1, Jingjing Wu2, Xiuli Wang1( )
School of Mathematics and Statistics, Shandong Normal University, Jinan 250014, China
Department of Mathematics and Statistics, University of Calgary, Calgary, AB, Canada
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Abstract

An improved weighted expectile average estimator for the regression coefficient has been obtained based on the covariate balancing propensity score (CBPS), when the responses of linear models are missing at random. The asymptotic normality of the proposed method has been proved, and the estimation effect of the method is further illustrated by numerical simulation.

Keywords

expectile regressionweighted expectile average estimatorcovariate balancing propensity scoreresponses missinggeneralized method of moments
CLC number: 62F10, 62F12

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AIMS Mathematics
Volume 9 Issue 8,
August 2024
Pages 23088-23099
DOI: 10.3934/math.20241122

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Cite this article:
Zhao Q, Wang Z, Wu J, et al. Weighted expectile average estimation based on CBPS with responses missing at random. AIMS Mathematics, 2024, 9(8): 23088-23099. https://doi.org/10.3934/math.20241122

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Received: 22 February 2024
Revised: 08 July 2024
Accepted: 22 July 2024
Published: 15 August 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)