A general procedure of estimating the population variance when coefficient of variation of an auxiliary variable is known in sample surveys

A general procedure of estimating the population variance when coefficient of variation of an... This paper deals with the problem of estimating population variance $${{S}_{\rm y}^2}$$ of the study variable y. We have suggested a family of estimators of population variance $${{S}_{\rm y}^2}$$ using the transformations on both the study variable and the auxiliary variable when coefficient of variation of an auxiliary variable x is known. The suggested family of estimators is very wide from which we can generate many estimators by putting the suitable values of scalars. The bias and mean squared error have been obtained upto the first order of approximation. The empirical study is carried out to the support of the suggested family of estimators. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

A general procedure of estimating the population variance when coefficient of variation of an auxiliary variable is known in sample surveys

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Publisher
Springer Netherlands
Copyright
Copyright © 2012 by Springer Science+Business Media B.V.
Subject
Social Sciences, general; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-012-9659-6
Publisher site
See Article on Publisher Site

Abstract

This paper deals with the problem of estimating population variance $${{S}_{\rm y}^2}$$ of the study variable y. We have suggested a family of estimators of population variance $${{S}_{\rm y}^2}$$ using the transformations on both the study variable and the auxiliary variable when coefficient of variation of an auxiliary variable x is known. The suggested family of estimators is very wide from which we can generate many estimators by putting the suitable values of scalars. The bias and mean squared error have been obtained upto the first order of approximation. The empirical study is carried out to the support of the suggested family of estimators.

Journal

Quality & QuantitySpringer Journals

Published: Jan 19, 2012

References

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