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An Alternative Class of Estimators in Double Sampling

Senapati, S.C., and Sahoo, L.N., (2006) An Alternative Class of Estimators in Double Sampling. Bulletin of the Malaysian Mathematical Sciences Society, 29 (1). pp. 89-94. ISSN 0126-6705

Full text not available from this repository.

Official URL: http://math.usm.my/bulletin/pdf/v29n1/v29n1p11.pdf

Affiliations

Ravenshaw College, Dept. of Statistics
Utkal University, Dept. of Statistics

Abstract

Using double sampling procedure, this paper presents a general class of estimators for the finite population mean when the population mean of the main auxiliary variable $x$ is unknown but that of an additional auxiliary variable $z$ is known. The proposed class of estimators is superior to some of the previously studied classes under minimum variance criterion.


2000 Mathematics Subject Classification: 62D05

Item Type:Journal
Keywords:Auxiliary variable, bias, double sampling, minimum variance bound, variance.
Subjects:Q Science, Computer Science
ID Code:1437

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[11] T.P. Tripathi and M.S. Ahmed, A class of estimators for a finite population mean based on multivariate information and general two-phase sampling, Calcutta Stat. Assoc. Bull. 45 (1995), 203—218.

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