Computing the effect of measurement errors on efficient variant of the product and ratio estimators of mean using auxiliary information

Neha Singh, Gajendra K. Vishwakarma, Jong Min Kim

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

This article presents an efficient variant of the usual product and ratio methods of estimation of population mean of a study variable Y in the context of simple random sampling when the observations of both study variable and auxiliary variable are supposed to be commingled with measurement error. The bias and mean squared error of proposed class of estimators have been derived and studied under measurement error. Monte Carlo simulation and numerical studies have been carried out to study the properties of the estimators and compared with mean square error and percentage relative efficiency of the estimator when variables are free from measurement errors.

Original languageEnglish (US)
Pages (from-to)604-625
Number of pages22
JournalCommunications in Statistics: Simulation and Computation
Volume51
Issue number2
DOIs
StatePublished - 2022

Bibliographical note

Funding Information:
Authors are deeply indebted to the editor-in-chief Prof. N. Balakrishnan and learned referees for their valuable suggestions leading to improving the quality of contents and presentation of the original manuscript.

Publisher Copyright:
© 2019 Taylor & Francis Group, LLC.

Keywords

  • 62D05
  • Design parameter
  • Measurement error
  • Monte Carlo simulation
  • Percentage relative efficiency

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