Robust estimator for estimation of population mean under PPS sampling: Application to radiation data

When the population features are same, choosing the units with the help of simple random sampling (SRS). However, in situations while there is a significant variation in unit dimensions, the probability proportional to size (PPS) sampling approach might be implemented. The aim of this work was to bring a new estimator for mean estimation using PPS sampling. The efficiency of the estimators was demonstrated using radiation data, also apply simulation analysis. When comparing the proposed estimator to existing counterparts, the numerical result shows that recommended estimators performs better for estimating population means. Visual representations of the data further prove the validity of the proposed estimator. As a result, we are in favor of utilizing the proposed estimator and believe it can improve outcomes when estimating the populations mean using a PPS sampling method.

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Publication Details

Journal
Journal of Radiation Research and Applied Sciences
Published
2025-03-05
DOI
https://doi.org/10.1016/j.jrras.2025.101384
Citations
18
Primary Topic
Survey Sampling and Estimation Techniques
Type
article
Field-Weighted Citation Impact
47.34

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article

Robust estimator for estimation of population mean under PPS sampling: Application to radiation data

Sohaib Ahmad, Badr Aloraini, Ahmed R. El‐Saeed
18 citations
Journal of Radiation Research and Applied Sciences
Survey Sampling and Estimation Techniques
47.34
article

Robust estimator for estimation of population mean under PPS sampling: Application to radiation data

Sohaib Ahmad, Badr Aloraini, Ahmed R. El‐Saeed
article en
18 citations

Abstract

When the population features are same, choosing the units with the help of simple random sampling (SRS). However, in situations while there is a significant variation in unit dimensions, the probability proportional to size (PPS) sampling approach might be implemented. The aim of this work was to bring a new estimator for mean estimation using PPS sampling. The efficiency of the estimators was demonstrated using radiation data, also apply simulation analysis. When comparing the proposed estimator to existing counterparts, the numerical result shows that recommended estimators performs better for estimating population means. Visual representations of the data further prove the validity of the proposed estimator. As a result, we are in favor of utilizing the proposed estimator and believe it can improve outcomes when estimating the populations mean using a PPS sampling method.

Journal of Radiation Research and Applied SciencesVol. 18(2)
Quaid-i-Azam University (PK), Shaqra University (SA), Imam Mohammad ibn Saud Islamic University (SA)
Al-Imam Muhammad Ibn Saud Islamic University
Openalex Percentile: Top 0%
Survey Sampling and Estimation Techniques
47.34
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