On Enhanced Ratio-Type Estimators Using Quantile Regression for Finite Population Mean under Robustness and Empirical Validation
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| Publicado en: | Iranian Journal of Science vol. 49, no. 1 (Feb 2025), p. 169 |
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| Autor principal: | |
| Otros Autores: | , |
| Publicado: |
Springer Nature B.V.
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| 045 | 2 | |b d20250101 |b d20250331 | |
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| 100 | 1 | |a Zohaib, Muhammad |u Government College University, Department of Statistics, Faisalabad, Pakistan (GRID:grid.411786.d) (ISNI:0000 0004 0637 891X) | |
| 245 | 1 | |a On Enhanced Ratio-Type Estimators Using Quantile Regression for Finite Population Mean under Robustness and Empirical Validation | |
| 260 | |b Springer Nature B.V. |c Feb 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a When the conditions of traditional regression analysis aren't met, an alternative method called quantile regression is utilized to estimate the value of the study variable across different quantiles of the distribution. This study proposes leveraging quantile regression information to develop ratio-type estimators for the finite population mean, particularly under robust measures of auxiliary variables in simple random sampling (SRS) without replacement. The performance of these proposed families of estimators is compared with existing studies using metrics such as mean squared error (MSE) equations and percentage relative efficiency (PRE). Additionally, this article incorporates simulation studies. Moreover, various real-world datasets are considered for empirical investigation to validate the theoretical findings. | |
| 653 | |a Mean square errors | ||
| 653 | |a Kurtosis | ||
| 653 | |a Datasets | ||
| 653 | |a Estimates | ||
| 653 | |a Random variables | ||
| 653 | |a Statistical sampling | ||
| 653 | |a Adultery | ||
| 653 | |a Quantiles | ||
| 653 | |a Variables | ||
| 653 | |a Regression analysis | ||
| 653 | |a Estimators | ||
| 653 | |a Random sampling | ||
| 653 | |a Economic | ||
| 700 | 1 | |a Latif, Waqas |u Government College University, Department of Statistics, Faisalabad, Pakistan (GRID:grid.411786.d) (ISNI:0000 0004 0637 891X) | |
| 700 | 1 | |a Alam, Mubeen |u The University of Faisalabad, Department of Mathematics, Faisalabad, Pakistan (GRID:grid.444767.2) (ISNI:0000 0004 0607 1811) | |
| 773 | 0 | |t Iranian Journal of Science |g vol. 49, no. 1 (Feb 2025), p. 169 | |
| 786 | 0 | |d ProQuest |t ABI/INFORM Trade & Industry | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3255183986/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3255183986/fulltext/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3255183986/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |