Memory type ratio and product estimators for population mean for time-based surveys

Abstract

The use of auxiliary variable is common at estimation stage in the form of ratio and product type estimators. All such estimators use the current sample information to estimate the population characteristics. In this study, we utilized the past samples information along with the current sample information in the form of hybrid exponentially weighted moving averages to construct memory type ratio and product estimators for time-based surveys. The mean square error expressions of the proposed estimators are derived and mathematical conditions are established to prove the efficiency of proposed estimators. An extensive simulation study is conducted to examine the performance of the proposed estimators. It is revealed from the results that use of past sample information along with the current sample excels the performance of estimator in terms of efficiency. A real life example is given to demonstrate the use of proposed estimators.

KEYWORDS:

• HEWMA
• ratio estimator
• product estimator
• memory type

Acknowledgment

The authors are grateful to the reviewers for their suggestions which helped in improving substantially, the earlier version of this article.

Disclosure statement

No potential conflict of interest was reported by the author(s).