A new class of median estimators using auxiliary information under PPS sampling: theoretical properties and empirical evaluation
The use of auxiliary or supplementary information plays a crucial role in enhancing the efficiency of estimators in survey sampling. Among various measures of central tendency, the median has attracted considerable attention due to its robustness against outliers and skewed distributions. This study...
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| Formato: | Artículo |
| Lenguaje: | inglés |
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2026
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| _version_ | 1881508903749943296 |
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| author | Shah, Salman Mahmoudi, Eisa Qureshi, Moiz Iftikhar, Hasnain Rodrigues, Paulo Canas Gonzales Medina, Ronny Ivan López Gonzales, Javier Linkolk |
| author_browse | Gonzales Medina, Ronny Ivan Iftikhar, Hasnain López Gonzales, Javier Linkolk Mahmoudi, Eisa Qureshi, Moiz Rodrigues, Paulo Canas Shah, Salman |
| author_facet | Shah, Salman Mahmoudi, Eisa Qureshi, Moiz Iftikhar, Hasnain Rodrigues, Paulo Canas Gonzales Medina, Ronny Ivan López Gonzales, Javier Linkolk |
| author_sort | Shah, Salman |
| collection | Producción científica |
| description | The use of auxiliary or supplementary information plays a crucial role in enhancing the efficiency of estimators in survey sampling. Among various measures of central tendency, the median has attracted considerable attention due to its robustness against outliers and skewed distributions. This study introduces a novel estimator for the finite population median that incorporates supplementary information under a probability proportional to size (PPS) sampling design. Analytical expressions for the bias and mean squared error (MSE) of the proposed estimator are derived up to the first order of approximation. The efficiency of the proposed estimator is evaluated through theoretical comparisons and empirical analyses against existing median estimators, using MSE and percent relative efficiency (PRE) as performance criteria. Furthermore, graphical representations are employed to illustrate the comparative performance. The proposed estimator is examined using three real-world datasets, and its precision is further validated through a comprehensive simulation study. The findings consistently demonstrate that the proposed estimator outperforms its existing counterparts in terms of efficiency and robustness. |
| format | Article |
| id | oai:cris.upeu.edu.pe:20.500.15037/393 |
| institution | UPeU |
| language | English |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
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| spelling | oai:cris.upeu.edu.pe:20.500.15037/3932026-10-30T16:14:36ZA new class of median estimators using auxiliary information under PPS sampling: theoretical properties and empirical evaluationShah, SalmanMahmoudi, EisaQureshi, MoizIftikhar, HasnainRodrigues, Paulo CanasGonzales Medina, Ronny IvanLópez Gonzales, Javier LinkolkStatistics, generalProbability and Statistics in Computer ScienceProbability Theory and Stochastic ProcessesEconomic Theory/Quantitative Economics/Mathematical MethodsThe use of auxiliary or supplementary information plays a crucial role in enhancing the efficiency of estimators in survey sampling. Among various measures of central tendency, the median has attracted considerable attention due to its robustness against outliers and skewed distributions. This study introduces a novel estimator for the finite population median that incorporates supplementary information under a probability proportional to size (PPS) sampling design. Analytical expressions for the bias and mean squared error (MSE) of the proposed estimator are derived up to the first order of approximation. The efficiency of the proposed estimator is evaluated through theoretical comparisons and empirical analyses against existing median estimators, using MSE and percent relative efficiency (PRE) as performance criteria. Furthermore, graphical representations are employed to illustrate the comparative performance. The proposed estimator is examined using three real-world datasets, and its precision is further validated through a comprehensive simulation study. The findings consistently demonstrate that the proposed estimator outperforms its existing counterparts in terms of efficiency and robustness.Article10.1007/s00180-026-01724-8https://hdl.handle.net/20.500.15037/393W7138910594enComputational Statistics0943-40621613-96582026-03-192026-06-13T08:12:34Z2026-06-13T08:12:34Z |
| spellingShingle | Statistics, general Probability and Statistics in Computer Science Probability Theory and Stochastic Processes Economic Theory/Quantitative Economics/Mathematical Methods Shah, Salman Mahmoudi, Eisa Qureshi, Moiz Iftikhar, Hasnain Rodrigues, Paulo Canas Gonzales Medina, Ronny Ivan López Gonzales, Javier Linkolk A new class of median estimators using auxiliary information under PPS sampling: theoretical properties and empirical evaluation |
| title | A new class of median estimators using auxiliary information under PPS sampling: theoretical properties and empirical evaluation |
| title_full | A new class of median estimators using auxiliary information under PPS sampling: theoretical properties and empirical evaluation |
| title_fullStr | A new class of median estimators using auxiliary information under PPS sampling: theoretical properties and empirical evaluation |
| title_full_unstemmed | A new class of median estimators using auxiliary information under PPS sampling: theoretical properties and empirical evaluation |
| title_short | A new class of median estimators using auxiliary information under PPS sampling: theoretical properties and empirical evaluation |
| title_sort | new class of median estimators using auxiliary information under pps sampling theoretical properties and empirical evaluation |
| topic | Statistics, general Probability and Statistics in Computer Science Probability Theory and Stochastic Processes Economic Theory/Quantitative Economics/Mathematical Methods |
| topic_facet | Statistics, general Probability and Statistics in Computer Science Probability Theory and Stochastic Processes Economic Theory/Quantitative Economics/Mathematical Methods |
| url | https://hdl.handle.net/20.500.15037/393 |
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