Memory type general class of estimators for population variance under simple random sampling

Kumar, Anoop; Anshika,; Emam, Walid; Tashkandy, Yusra

doi:10.1016/j.heliyon.2024.e36090

Heliyon

2024

DOI: 10.1016/j.heliyon.2024.e36090

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Memory type general class of estimators for population variance under simple random sampling

Anoop Kumar,

Anshika,

Walid Emam

et al.

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2024

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Optimal class of memory type imputation methods for time-based surveys using EWMA statistics

Kumar,

Bhushan,

Alomair

2024

Sci Rep

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Time-based surveys often experience missing data due to several reasons, like non-response or data collection limitations. Imputation methods play an essential role in incorporating these missing values to secure the accuracy and reliability of the survey outcomes. This manuscript proposes some optimal class of memory type imputation methods for imputing missing data in time-based surveys by utilizing exponentially weighted moving average (EWMA) statistics. The insights into the optimal conditions for incorporating our proposed methods are provided. A comprehensive examination of the proposed method utilizing simulated and real-life datasets is conducted. Comparative analyses against the existing imputation methods exhibit the superior performance of our methods, particularly in the scenarios characterized by developing trends and dynamic response patterns. The outcomes highlight the effectiveness of utilizing EWMA statistics into memory type imputation methods, displaying their flexibility to changing survey dynamics.

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Optimal class of memory type imputation methods for time-based surveys using EWMA statistics

Kumar,

Bhushan,

Alomair

2024

Sci Rep

View full text Add to dashboard Cite

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scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Memory type general class of estimators for population variance under simple random sampling

Cited by 1 publication

References 24 publications

Optimal class of memory type imputation methods for time-based surveys using EWMA statistics

Optimal class of memory type imputation methods for time-based surveys using EWMA statistics

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