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2013•Journal of Mathematics and StatisticsOpen access

ADAPTIVE CLUSTER SAMPLING USING AUXILIARY VARIABLE

Chutiman

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Abstract

In this study we study the estimators of the population mean in adaptive cluster sampling by using the information of the auxiliary variable.The estimators in this study are the classical ratio estimator, the ratio estimator using the population coefficient of variation and the coefficient of kurtosis of the auxiliary variable, the regression estimator and the difference estimator.Simulations showed that the difference estimator had the smallest estimated mean square error when compared to the ratio estimators and the regression estimator.

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What this paper is about

In this study we study the estimators of the population mean in adaptive cluster sampling by using the information of the auxiliary variable.The estimators in this study are the classical ratio estimator, the ratio estimator using the population coefficient of variation and the coefficient of kurtosis of the auxiliary variable, the regression estimator and the difference estimator.Simulations showed that the difference estimator had the smallest estimated mean square error when compared to the ratio estimators and the regression estimator.

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Available abstract

In this study we study the estimators of the population mean in adaptive cluster sampling by using the information of the auxiliary variable.The estimators in this study are the classical ratio estimator, the ratio estimator using the population coefficient of variation and the coefficient of kurtosis of the auxiliary variable, the regression estimator and the difference estimator.Simulations showed that the difference estimator had the smallest estimated mean square error when compared to the ratio estimators and the regression estimator.

Key concepts: Mathematics, Estimator, Statistics, Kurtosis, Ratio estimator, Mean squared error, Efficient estimator, Trimmed estimator

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