L-Moments and Calibration-Based Estimators for Variance Parameter
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 i...
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Series: | Mathematical Problems in Engineering |
Online Access: | http://dx.doi.org/10.1155/2021/9847714 |
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doaj-95061be357784c609b1b3332bb61c2ab2021-09-13T01:24:06ZengHindawi LimitedMathematical Problems in Engineering1563-51472021-01-01202110.1155/2021/9847714L-Moments and Calibration-Based Estimators for Variance ParameterMalik Muhammad Anas0Muhammad Ali1Ambreen Shafqat2Faisal Shahzad3Kashif Abbass4David Anekeya Alilah5Department of Statistics and Financial MathematicsDepartemnt of Mathematics and StatisticsDepartment of Statistics and Financial MathematicsDepartment of Statistics and Financial MathematicsSchool of Economics and ManagementDepartment of MathematicsThe 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.http://dx.doi.org/10.1155/2021/9847714 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Malik Muhammad Anas Muhammad Ali Ambreen Shafqat Faisal Shahzad Kashif Abbass David Anekeya Alilah |
spellingShingle |
Malik Muhammad Anas Muhammad Ali Ambreen Shafqat Faisal Shahzad Kashif Abbass David Anekeya Alilah L-Moments and Calibration-Based Estimators for Variance Parameter Mathematical Problems in Engineering |
author_facet |
Malik Muhammad Anas Muhammad Ali Ambreen Shafqat Faisal Shahzad Kashif Abbass David Anekeya Alilah |
author_sort |
Malik Muhammad Anas |
title |
L-Moments and Calibration-Based Estimators for Variance Parameter |
title_short |
L-Moments and Calibration-Based Estimators for Variance Parameter |
title_full |
L-Moments and Calibration-Based Estimators for Variance Parameter |
title_fullStr |
L-Moments and Calibration-Based Estimators for Variance Parameter |
title_full_unstemmed |
L-Moments and Calibration-Based Estimators for Variance Parameter |
title_sort |
l-moments and calibration-based estimators for variance parameter |
publisher |
Hindawi Limited |
series |
Mathematical Problems in Engineering |
issn |
1563-5147 |
publishDate |
2021-01-01 |
description |
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. |
url |
http://dx.doi.org/10.1155/2021/9847714 |
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