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Estimation of general parameter in adaptive cluster sampling using two auxiliary variables

Authors:

Faryal Younis ,

LK
About Faryal
Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan
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Javid Shabbir

PK
About Javid
Department of Statistics, Quaid-i-Azam University, Islamabad, Pakistan.
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Abstract

In this article, exponential ratio type estimators are proposed for general parameter in adaptive cluster sampling. The estimators utilise information on two auxiliary variables in three different situations, i.e. partial, no and full information about population parameters of auxiliary variables. The proposed estimators for general parameter can be used to estimate population mean, coefficient of variation, standard deviation and variance of the variable of interest. The bias and mean square error equations for the proposed estimators are derived using first order approximation. The proposed estimators are more efficient than usual sample estimators and ratio estimators in all three situations under adaptive cluster sampling. Two different populations are used for numerical illustration.

How to Cite: Younis, F. and Shabbir, J., 2019. Estimation of general parameter in adaptive cluster sampling using two auxiliary variables. Journal of the National Science Foundation of Sri Lanka, 47(1), pp.89–103. DOI: http://doi.org/10.4038/jnsfsr.v47i1.8933
Published on 31 Mar 2019.
Peer Reviewed

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