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Variance estimation in the presence of measurement errors under stratified random sampling

Publication Type : Journal Article

Publisher : REVSTAT-Statistical Journal

Source : REVSTAT-Statistical Journal, 2021, ISSN: 1645-6726, National Statistics Institute, Statistics Portugal. (SCI-E).

Url : https://www.ine.pt/revstat/pdf/REVSTAT_v19-n2-06.pdf

Campus : Coimbatore

School : School of Physical Sciences

Department : Mathematics

Year : 2021

Abstract : This study focuses on the estimation of population variance of study variable in stratified random sampling using auxiliary information when the observations are contaminated by measurement errors. Three classes of estimators of variance under measurement error are proposed by using the approach of Srivastava and Jhajj [18] for the study variable. The properties of the estimator viz. bias and mean square error of the proposed classes of estimators are provided. The conditions for which proposed estimators are more efficient compared to usual estimators are discussed. It is shown that the proposed classes of estimators include a large number of estimators of the population variance of stratified random sampling and their bias and mean square error can be easily derived.

Cite this Research Publication : Vishwakarma, G.K., Singh, N (Corresponding Author). and Gangele, R.K., Variance estimation in the presence of measurement errors under stratified random sampling. REVSTAT-Statistical Journal, 2021, ISSN: 1645-6726, National Statistics Institute, Statistics Portugal. (SCI-E).

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