Regression-type Estimators Based on Two Auxiliary Variables of a Finite Population Mean in Two-phase Sampling

P. A. Patel¹ , F. H. Shah²

Section:Research Paper, Product Type: Isroset-Journal
Vol.5 , Issue.5 , pp.144-152, Oct-2018

CrossRef-DOI:   https://doi.org/10.26438/ijsrmss/v5i5.144152

Online published on Oct 31, 2018

Copyright © P. A. Patel , F. H. Shah . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
This paper suggests a class of regression-type estimators of a finite population mean incorporating auxiliary information on two variables at estimation stage in two-phase sampling. This class of estimators includes many known estimators. Up to the first order of approximation the mean square error (MSE) and optimal MSE are obtained and compared with the MSEs of the estimators included in this paper. Also, an empirical comparison is carried out using a Monte Carlo simulation over three natural populations.

Key-Words / Index Term :
Auxiliary variables, mean square error, optimum estimation, regression-type estimator, simulation, two-phase sampling

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