Volume 6 • Issue 2 • PP: 08-15 • 2022
An Innovative Additive Mathematical Model Using Auxiliary Information
Open Access & Copyright
© 2022 The Author(s). Published by ASPG. This article is licensed under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
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This article proposes innovative ratio and regression estimators based on additive randomized response model. Expressions for the biases and mean squared errors of the recommended estimators are derived. It has been revealed that the advised groundbreaking ratio and regression estimators are improved than ratio and regression estimators under a very realistic condition. Numerical illustrations and simulation study are also given in support of the present study.
Keywords
References
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