L-Moments and calibration-based variance estimators under double stratified random sampling scheme: Application of Covid-19 pandemic
Scientia Iranica
; 30(2):814-821, 2023.
Article
in English
| Web of Science | ID: covidwho-2328251
ABSTRACT
Extreme events gives rise to outrageous results in terms of population-related parameters and their estimates are usually done using traditional moments. Traditional moments are usually affected by extreme observations. This study aims to propose some new calibration estimators considering the L-Moments scheme for variance, which is one of the most important population parameters. a number of suitable calibration constraints under double stratified random sampling were defined for these estimators. The proposed estimators, which were based on L-Moments, were relatively more robust despite extreme values. The empirical efficiency of the proposed estimators was also assessed through simulation. Covid-19 pandemic data from January 22, 2020 to August 23, 2020 was taken into account in the simulation study. (c) 2023 Sharif University of Technology. All rights reserved.
Full text:
Available
Collection:
Databases of international organizations
Database:
Web of Science
Type of study:
Observational study
/
Prognostic study
/
Randomized controlled trials
Language:
English
Journal:
Scientia Iranica
Year:
2023
Document Type:
Article
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