Formulation of estimator for population mean in stratified successive sampling using memory-based information

• Authors: Sanjoy Majumder , Arnab Bandyopadhyay , Arindam Gupta

Abstracts

EN

In study described in this article, we developed a memory type estimator for the population mean in stratified successive sampling. We used the past sample information together with the current sample information through hybrid exponentially weighted moving averages statistics. We have also used the information available on auxiliary variable to construct the proposed estimator. We studied the properties of the proposed estimator. Further, we examined the performance of the proposed estimator in comparison with conventional estimator of the population mean and the results are demonstrated by using the data set of simulation as well as natural population. After observing the auspicious findings, we suggest that the proposed estimator can be applied to solve real-life problems.

Keywords

EN

successive sampling; HEWMA; regression estimator; variance; minimum variance; efficiency

• Publisher: Główny Urząd Statystyczny
• Journal: Statistics in Transition new series
• Year: 2025
• Volume: 26
• Issue: 2
• Pages: 39-56

Dates

published

2025

Contributors

author

Sanjoy Majumder

• Department of Mathematics and Statistics, Aliah University, Kolkata-700160, India

• https://orcid.org/000000018320003X

author

Arnab Bandyopadhyay

• Department of Basic Science and Humanities (Mathematics), Dr. B. C. Roy Engineering College, Durgapur 713206, India

• https://orcid.org/0000000207697491

author

Arindam Gupta

• Department of Statistics, The University of Burdwan, Burdwan-713104, India

• https://orcid.org/0000000193815150

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Identifiers

DOI

10.59139/stattrans-2025-015

Biblioteka Nauki

61791517