Enhanced Estimators of Population Variance with the Use of Supplementary Information in Survey Sampling | Zendy

Showkat Ahmad Lone | Zendy; Mir Subzar | Zendy; Ankita Sharma | Zendy

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Enhanced Estimators of Population Variance with the Use of Supplementary Information in Survey Sampling

Author(s) -

Showkat Ahmad Lone,

Mir Subzar,

Ankita Sharma

Publication year - 2021

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2021/9931217

Subject(s) - estimator , variance (accounting) , population variance , statistics , mathematics , extremum estimator , efficiency , population , class (philosophy) , variable (mathematics) , sampling (signal processing) , econometrics , computer science , m estimator , artificial intelligence , mathematical analysis , demography , accounting , filter (signal processing) , sociology , computer vision , business

In the present study, we propose the proficient class of estimators of the finite population mean, while incorporating the nonconventional location and nonconventional measures of dispersion with coefficient of variation of the auxiliary variable. Properties associated with the suggested class of improved estimators are derived, and an efficiency comparison with the usual unbiased ratio estimator and other existing estimators under consideration in the present study is established. An empirical study has also been provided to validate the theoretical results. Finally, it is established that the proposed class of estimators of the finite population variance proves to be more efficient than the existing estimators mentioned in this study.

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