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On stratified ranked set sampling for the quest of an optimal class of estimators.
- Source :
- Alexandria Engineering Journal; Jan2024, Vol. 86, p79-97, 19p
- Publication Year :
- 2024
-
Abstract
- In the sample survey theory, the crux of survey practitioners is to provide "accurate" estimators of the parameter of choice. The conventional theory depends on the regression/difference estimators as they correspond to the best linear unbiased (B L U) estimators. This paper suggests some optimal classes of estimators by modifying the conventional estimators under stratified ranked set sampling (S R S S). The characteristics of the suggested estimators are established to the first-order approximation. The performance of the suggested class of estimators under SRSS has been theoretically and experimentally shown to be superior to traditional estimators, particularly regression (B L U) estimators. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 11100168
- Volume :
- 86
- Database :
- Supplemental Index
- Journal :
- Alexandria Engineering Journal
- Publication Type :
- Academic Journal
- Accession number :
- 174951809
- Full Text :
- https://doi.org/10.1016/j.aej.2023.11.037