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An Improved Class of Estimators for Finite Population Mean in Sample Surveys
Author(s) -
Tracy Derrick S.,
Singh Housila P.
Publication year - 1999
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/(sici)1521-4036(199911)41:7<891::aid-bimj891>3.0.co;2-4
Subject(s) - estimator , mathematics , statistics , random variate , mean squared error , class (philosophy) , population , sample size determination , sample (material) , simple random sample , random variable , demography , computer science , chemistry , chromatography , artificial intelligence , sociology
This paper proposes a class of estimators for estimating the finite population mean ‐ Y of a study variate y using information on two auxiliary variates, one of which is positively and the other negatively correlated with the study variate y . An “asymptotically optimum estimator” (AOE) in the class is identified with its bias and mean square error formulae. It is observed that the proposed AOE is more efficient than Srivastava (1965), Srivastava (1974), Prasad (1989) and Gandge , Varghese , and Prabhu‐Ajgaonkar (1993) estimators.