Efficient Utilization of Multiple Auxiliary Variables for Nonresponse Problem in Estimating the Population Mean Under Sub-sampling Technique

The main key objective of this paper is to address the nonresponse problems by adapting Hansen and Hurwitz’s technique (1964) and Saini et al.’s estimator (2022) to propose a novel estimator of population mean under sub-sampling technique using multiple auxiliary variables. A comparative analysis of the proposed novel estimator's efficacy has been performed through theoretical and numerical studies. The results of this paper confirm that our estimator is more effective than others under the same situation.

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Publication Details

Journal
Journal of Modern Applied Statistical Methods
Published
2024-10-18
DOI
https://doi.org/10.56801/jmasm.v24.i1.2
Primary Topic
Survey Sampling and Estimation Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Efficient Utilization of Multiple Auxiliary Variables for Nonresponse Problem in Estimating the Population Mean Under Sub-sampling Technique

Napattchan Dansawad
Journal of Modern Applied Statistical Methods
Survey Sampling and Estimation Techniques
article

Efficient Utilization of Multiple Auxiliary Variables for Nonresponse Problem in Estimating the Population Mean Under Sub-sampling Technique

Napattchan Dansawad
article en

Abstract

The main key objective of this paper is to address the nonresponse problems by adapting Hansen and Hurwitz’s technique (1964) and Saini et al.’s estimator (2022) to propose a novel estimator of population mean under sub-sampling technique using multiple auxiliary variables. A comparative analysis of the proposed novel estimator's efficacy has been performed through theoretical and numerical studies. The results of this paper confirm that our estimator is more effective than others under the same situation.

Journal of Modern Applied Statistical MethodsVol. 24(1)
King Mongkut's University of Technology Thonburi (TH)
King Mongkut's University of Technology Thonburi
Openalex Percentile: Top 76%
Survey Sampling and Estimation Techniques
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