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A Class of Almost Unbiased Estimators for Finite Populations Mean Using Two Auxiliary Variables
Author(s) -
Tracy Derrick S.,
Singh Housila P.,
Singh Rajesh
Publication year - 1998
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(199810)40:6<753::aid-bimj753>3.0.co;2-o
Subject(s) - mathematics , estimator , minimum variance unbiased estimator , jackknife resampling , statistics , bias of an estimator , u statistic , efficient estimator , efficiency , best linear unbiased prediction , unbiased estimation , stein's unbiased risk estimate , population , econometrics , demography , computer science , sociology , selection (genetic algorithm) , artificial intelligence
For estimating finite population mean ‐ Y 0 of study character y 0 , a class of almost unbiased estimators applying jackknife technique envisaged by Quenouille (1956) is derived. Optimum unbiased estimator (OUE) is also investigated with its variance formula. An empirical study is carried out to demonstrate the performance of the constructed estimator over the usual unbiased estimator, Srivastava (1965), Singh (1967), Singh and Biradar (1992), Tracy , Singh , and Singh (1996) and other almost unbiased estimators.