ON THE COMBINATION OF ESTIMATORS OF FINITE POPULATION MEAN USING INCOMPLETE MULTI- AUXILIARY INFORMATION
Keywords:
Bias; Mean Square Error; Incomplete Multi-Auxiliary Information.Abstract
The present study is concerned with the estimation of a finite population mean when we have information on several auxiliary variables only for some part of the population. The maximum utilization of incomplete multi-auxiliary information is carried out in such cases by stratifying the population on the basis of available multi-auxiliary information at hand. This paper deals with the situation where some of the auxiliary variables are positively and some of them are negatively correlated with the main variable. For this purpose, in this paper ratio-cum-product and regression-cum-product type estimators are considered for estimating the mean of the finite population utilizing available incomplete multi-auxiliary information. The approximate expressions for bias and mean square error of the suggested estimators have also been derived and theoretical results are numerically supported.
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References
Cochran, W. G. (1977). Sampling Technique, 3rd edition, New York, Wiley and
Sons.
Olkin, I. (1958). Multivariate ratio estimation for finite population, Biometrika, 45,
p.154-165.
Sukhatme P.V. and Sukhatme, B.V. (1997). Sampling Theory of Surveys with
Applications, Ames, Iowa, Iowa State University Press, USA.
Singh, R. (1977). A Note On The Use Of Incomplete Multi-Auxiliary Information
In Sample Surveys, Australian Journal of Statistics, 19 (2), p.105-107.
Srivastava, M. and Garg, N. (2009). A class of estimators of finite population mean
using incomplete multi-auxiliary information when frame is unknown, Aligarh
Journal of Statistics, 29, p.51-73.
Srivastava, M and Garg, N.(2013) - The class of estimators of finite population
mean using incomplete auxiliary information, Statistics In Transition - New Series
(2), p.201 – 216.
