L-Moments and Calibration-Based Estimators for Variance Parameter

Anas Malik Muhammad; Ali Muhammad; Shafqat AmbreenShahzad FaisalAbbass KashifAlilah David Anekeya

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L-Moments and Calibration-Based Estimators for Variance Parameter

机译：L-Moments and Calibration-Based Estimators for Variance Parameter

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The subject of variance estimation is one of the most important topics in statistics. It has been clarified by many different research studies due to its various applications in the human and natural sciences. Different variance estimators are built based on traditional moments that are especially influenced by the existence of extreme values. In this paper, with the presence of extreme values, we proposed some new calibration estimators for variance based on L-moments under double-stratified random sampling. A simulation study with COVID-19 data is performed to evaluate the efficiency of the proposed estimators. All results indicate that the proposed estimators are often superior and highly efficient compared to the existing traditional estimator.

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《Mathematical Problems in Engineering: Theory, Methods and Applications》 |2021年第37期|9847714.1-9847714.8|共8页
作者
Anas Malik Muhammad; Ali Muhammad; Shafqat AmbreenShahzad FaisalAbbass KashifAlilah David Anekeya;
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Nanjing Univ Sci & Technol, Sch Sci, Dept Stat & Financial Math, Nanjing 210094, Jiangsu, Peoples R China;

PMAS Arid Agr Univ Rawalpindi, Departemnt Math & Stat, Rawalpindi 46300, Pakistan;

Nanjing Univ Sci & Technol, Sch Econ & Management, Nanjing 210094, Jiangsu, Peoples R ChinaMasinde Muliro Univ Sci & Technol, Dept Math, Kakamega, Kenya;

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L-Moments and Calibration-Based Estimators for Variance Parameter

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