Estimation of the distribution function of a finite population utilizing auxiliary information in the context of non-response within complex survey sampling.
This study focuses on estimating a finite population cumulative distribution function (CDF) using two-stage and three-stage cluster sampling under non-response. This work is then extended to estimate the finite population CDF under non-response using stratified two-stage and three-stage cluster samp...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0322660 |
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| author | Mohsin Abbas Muhammad Ahmed Shehzad Haris Khurram Mahwish Rabia |
| author_facet | Mohsin Abbas Muhammad Ahmed Shehzad Haris Khurram Mahwish Rabia |
| author_sort | Mohsin Abbas |
| collection | DOAJ |
| description | This study focuses on estimating a finite population cumulative distribution function (CDF) using two-stage and three-stage cluster sampling under non-response. This work is then extended to estimate the finite population CDF under non-response using stratified two-stage and three-stage cluster sampling. We propose two distinct families of CDF estimators, specifically designed for these complex surveys, namely classical ratio/product-type and exponential ratio/product-type. Furthermore, we introduce a difference estimator for the CDF under non-response, utilizing ancillary information about the variances and covariances of the estimators under these complex schemes. We provide mathematical expressions for the biases and mean squared errors of the proposed CDF estimators, based on first-order approximation. To evaluate the performance of the proposed estimators, we conduct extensive simulations and assess their efficiency. The simulation results demonstrate that the proposed families of estimators perform well under different sampling scenarios. Our findings indicate that difference CDF estimators are more explicit than the other estimators discussed. We support our theoretical claims by analyzing real datasets. |
| format | Article |
| id | doaj-art-ffce5eba38d34359b2e8fc0fed0d1658 |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-ffce5eba38d34359b2e8fc0fed0d16582025-08-20T01:57:15ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01205e032266010.1371/journal.pone.0322660Estimation of the distribution function of a finite population utilizing auxiliary information in the context of non-response within complex survey sampling.Mohsin AbbasMuhammad Ahmed ShehzadHaris KhurramMahwish RabiaThis study focuses on estimating a finite population cumulative distribution function (CDF) using two-stage and three-stage cluster sampling under non-response. This work is then extended to estimate the finite population CDF under non-response using stratified two-stage and three-stage cluster sampling. We propose two distinct families of CDF estimators, specifically designed for these complex surveys, namely classical ratio/product-type and exponential ratio/product-type. Furthermore, we introduce a difference estimator for the CDF under non-response, utilizing ancillary information about the variances and covariances of the estimators under these complex schemes. We provide mathematical expressions for the biases and mean squared errors of the proposed CDF estimators, based on first-order approximation. To evaluate the performance of the proposed estimators, we conduct extensive simulations and assess their efficiency. The simulation results demonstrate that the proposed families of estimators perform well under different sampling scenarios. Our findings indicate that difference CDF estimators are more explicit than the other estimators discussed. We support our theoretical claims by analyzing real datasets.https://doi.org/10.1371/journal.pone.0322660 |
| spellingShingle | Mohsin Abbas Muhammad Ahmed Shehzad Haris Khurram Mahwish Rabia Estimation of the distribution function of a finite population utilizing auxiliary information in the context of non-response within complex survey sampling. PLoS ONE |
| title | Estimation of the distribution function of a finite population utilizing auxiliary information in the context of non-response within complex survey sampling. |
| title_full | Estimation of the distribution function of a finite population utilizing auxiliary information in the context of non-response within complex survey sampling. |
| title_fullStr | Estimation of the distribution function of a finite population utilizing auxiliary information in the context of non-response within complex survey sampling. |
| title_full_unstemmed | Estimation of the distribution function of a finite population utilizing auxiliary information in the context of non-response within complex survey sampling. |
| title_short | Estimation of the distribution function of a finite population utilizing auxiliary information in the context of non-response within complex survey sampling. |
| title_sort | estimation of the distribution function of a finite population utilizing auxiliary information in the context of non response within complex survey sampling |
| url | https://doi.org/10.1371/journal.pone.0322660 |
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