On calibrated weights in stratified sampling

Rao, Dinesh K. and Khan, Mohammad G.M. and Singh, G.K. (2018) On calibrated weights in stratified sampling. Australian and New Zealand Industrial and Applied Mathematics Journal, NA . C190-C204. ISSN 1446-8735

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Abstract

In this paper, we propose a calibration estimator of population mean in stratified sampling using the known mean and variance information from multi-auxiliary variables. The problem of determining the optimum
calibrated weights is formulated as an optimisation problem and is solved using the Lagrange multiplier technique. A numerical example with real data is presented to illustrate the computational details of the
proposed estimator. A comparison study is also carried out using real and simulated data to evaluate the performance and the usefulness of the proposed estimator. The study reveals that the proposed estimator with multi-auxiliary information is the most efficient estimator of the population mean when compared to other estimators as it provides least estimated variance and highest gain in relative efficiency (RE).

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences
Depositing User:	Ms Shalni Sanjana
Date Deposited:	18 Oct 2018 03:40
Last Modified:	18 Oct 2018 03:40
URI:	https://repository.usp.ac.fj/id/eprint/11142

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