Moreover, a simulation study is accomplished when some population parameters are assumed to be unknown.
📌 3 Key Takeaways
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Objective & Hypothesis:In this paper we consider the problem of estimation of population mean in circular systematic sampling design along with the non-responseproblem.
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Key Findings & Data:The biases and the mean square errors of the suggested classes of estimators are obtained and compared with sample mean, linear regression estimators, [23] estimator and [21] estimators.
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Conclusion & Impact:Moreover, a simulation study is accomplished when some population parameters are assumed to be unknown.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Bias · Mean square error · Ratio function
Abstract
In this paper we consider the problem of estimation of population mean in circular systematic sampling design along with the non-responseproblem. For the population mean using auxiliary information three generalized classes of estimators are suggested. The biases and the mean square errors of the suggested classes of estimators are obtained and compared with sample mean, linear regression estimators, [23] estimator and [21] estimators. A numerical study is provided to Show that the proposed classes of estimators based on circular systematic design can be more efficient than the estimators based on simple random sampling. Moreover, a simulation study is accomplished when some population parameters are assumed to be unknown.
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