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2014 Estimation of Finite Population Mean in Multivariate Stratified Sampling under Cost Function Using Goal Programming
Atta Ullah, Javid Shabbir, Zawar Hussain, Bander Al-Zahrani
J. Appl. Math. 2014: 1-7 (2014). DOI: 10.1155/2014/686579

Abstract

In practical utilization of stratified random sampling scheme, the investigator meets a problem to select a sample that maximizes the precision of a finite population mean under cost constraint. An allocation of sample size becomes complicated when more than one characteristic is observed from each selected unit in a sample. In many real life situations, a linear cost function of a sample size nh is not a good approximation to actual cost of sample survey when traveling cost between selected units in a stratum is significant. In this paper, sample allocation problem in multivariate stratified random sampling with proposed cost function is formulated in integer nonlinear multiobjective mathematical programming. A solution procedure is proposed using extended lexicographic goal programming approach. A numerical example is presented to illustrate the computational details and to compare the efficiency of proposed compromise allocation.

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Atta Ullah. Javid Shabbir. Zawar Hussain. Bander Al-Zahrani. "Estimation of Finite Population Mean in Multivariate Stratified Sampling under Cost Function Using Goal Programming." J. Appl. Math. 2014 1 - 7, 2014. https://doi.org/10.1155/2014/686579

Information

Published: 2014
First available in Project Euclid: 2 March 2015

zbMATH: 07131789
Digital Object Identifier: 10.1155/2014/686579

Rights: Copyright © 2014 Hindawi

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