Almost unbiased ratio-cum-product estimators for the finite population mean
type: Item
instance of: scholarly article
title: Almost unbiased ratio-cum-product estimators for the finite population mean
zbMATH Open document ID: 0765.62017
DOI: 10.1007/BF02562658
author: R. S. Biradar
author: Housila P. Singh
published in: Test
publication date: 1993-05-16T00:00:00Z
review text: We have proposed a class of almost unbiased ratio-cum-product estimators for the finite population mean using jackknife techniques. An asymptotic expression for the variance of the proposed estimator is derived and the optimum estimator in the class is also identified. The conditions for the proposed estimator to be more efficient than the sample mean and some biased estimator are obtained. Two illustrative examples are given to demonstrate the superiority of the proposed estimator.
Mathematics Subject Classification ID: 62D05
zbMATH DE Number: 168787
zbMATH Keywords: almost unbiased ratio-cum-product estimators
zbMATH Keywords: finite population mean
zbMATH Keywords: jackknife
zbMATH Keywords: optimum estimator
zbMATH Keywords: sample mean
MaRDI profile type: Publication
cites work: Estimating the Mean of a Normal Distribution with Known Coefficient of Variation
cites work: Estimation of variance of mean using known coefficient of variation
cites work: Some Finite Population Unbiased Ratio and Regression Estimators
cites work: NOTES ON BIAS IN ESTIMATION
cites work: Q3959261
cites work: On Bias Reduction in Estimation
cites work: Almost unibiased product-type estimator
cites work: Ratio cum product method of estimation
cites work: The Precision of Some Unbiased Regression Estimators
description: scientific article; zbMATH DE number 168787