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EFFICIENT CLASSES OF ROBUST RATIO TYPE ESTIMATORS OF MEAN AND VARIANCE IN ADAPTIVE CLUSTER SAMPLING.

Authors :
Raghav, Yashpal Singh
Singh, Rajesh
Mishra, Rohan
Adichawal, Nitesh Kumar
Ali, Irfan
Source :
International Journal of Agricultural & Statistical Sciences; 2024, Vol. 20 Issue 1, p173-186, 14p
Publication Year :
2024

Abstract

This paper proposes two classes of robust ratio type estimators of finite population mean and two classes of robust ratio type estimators of finite population variance using a single auxiliary variable under the adaptive cluster sampling design. Seven robust ratio type estimators have been developed from each class. The generalized expressions of bias and mean square error for each class have been derived up to the first order of approximation. The exact expressions of bias and MSE for all the developed estimators have been presented. Using simulation studies conducted in R programming, the high efficiency of all the developed estimators over similar existing estimators in adaptive cluster sampling has been demonstrated. [ABSTRACT FROM AUTHOR]

Subjects

Subjects :
CLUSTER sampling
DESIGN

Details

Language :
English
ISSN :
09731903
Volume :
20
Issue :
1
Database :
Complementary Index
Journal :
International Journal of Agricultural & Statistical Sciences
Publication Type :
Academic Journal
Accession number :
178710382
Full Text :
https://doi.org/10.59467/IJASS.2024.20.173