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Estimation of Population Mean Under Successive Sampling Scheme when Various Weights and Regression Coefficients are Unknown
Author(s) -
Tikkiwal G. C.,
Gupta A. K.
Publication year - 1991
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/bimj.4710330504
Subject(s) - mathematics , statistics , estimator , population mean , population , sampling scheme , sampling (signal processing) , bias of an estimator , regression , regression analysis , minimum variance unbiased estimator , variance (accounting) , mean squared error , linear regression , estimation , population variance , computer science , demography , accounting , filter (signal processing) , sociology , business , computer vision , management , economics
In this paper properties of an estimator of the population mean on current occasion under successive sampling scheme, when various weights (φ h 'S) and regression coefficients (β h , h ‐1) are estimated for h ≥ 2, have been studied. Some empirical results on the estimation of the variance of an unbiased estimator of population mean for h = 2 are also given.