Estimating the Population Mean Using Searls Approach
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Abstract
The Searls approach was employed to develop the estimation of population mean based on the coefficient of variation of the known population. This approach leads to a higher efficiency of the Searls estimator than that of the traditional one. This article presents the Searls approach’s methods and provides examples of the population mean estimators using the Searls approach: the estimator using the Searls approach for simple random sampling without replacement and the estimator using the Searls approach for single-stage cluster sampling with simple random sampling without replacement
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References
[1] P. Suwutthee, Statistical Inference Theory, 3rd ed. Bangkok: WVO Officer of Printing Mill, 2010, pp. 57 (in Thai).
[2] D. T. Searls, “The utilization of a known coefficient of variation in the estimation procedure,” American Statistical Association Journal, vol. 56, pp. 1225–1226, 1964.
[3] C. Kongnam, J. Jitthavech, and V. Lorchirachoonkul, “Estimator in single-stage cluster sampling: Searls approach,” Burapha Science Journal, vol. 22, no. 1, pp. 135–150, 2017 (in Thai).
[4] H. Cingi and C. Kadilar, Advances in Sampling Theory - Ratio Method of Estimation, Bentham Science Publishers, 2009.
[5] B. Prasad, “Some improved ratio type estimators of population mean and ratio in finite population sample surveys,” Communications in Statistics: Theory and Methods, vol. 18, no. 1, pp. 379–392, 1989.
[6] W. G. Cochran, Sampling Techniques, 3rd ed. New York: John Wiley and Sons, 1977.
[7] J. Jitthavech and V. Lorchirachoonkul, “Estimators in simple random sampling: Searls approach,” Songklanakarin Journal of Science and Technology, vol. 35, no. 6, pp. 749–760, November–December 2013.
[8] C. Kadilar and H. Cingi, “A study on the chain ratio - type estimator,” Hacettepe Journal of Mathematics and Statistics, vol. 32, pp. 105–108, 2003.
[9] A. K. Gupta and D. G. Kabe, Theory of Sample Surveys. Singapore: World Scientific Publishing, 2011.
[10] P.V. Sukhatme, Sampling Theory of Surveys with Applications. Iowa: Iowa State University Press, 1954, pp. 278.
[2] D. T. Searls, “The utilization of a known coefficient of variation in the estimation procedure,” American Statistical Association Journal, vol. 56, pp. 1225–1226, 1964.
[3] C. Kongnam, J. Jitthavech, and V. Lorchirachoonkul, “Estimator in single-stage cluster sampling: Searls approach,” Burapha Science Journal, vol. 22, no. 1, pp. 135–150, 2017 (in Thai).
[4] H. Cingi and C. Kadilar, Advances in Sampling Theory - Ratio Method of Estimation, Bentham Science Publishers, 2009.
[5] B. Prasad, “Some improved ratio type estimators of population mean and ratio in finite population sample surveys,” Communications in Statistics: Theory and Methods, vol. 18, no. 1, pp. 379–392, 1989.
[6] W. G. Cochran, Sampling Techniques, 3rd ed. New York: John Wiley and Sons, 1977.
[7] J. Jitthavech and V. Lorchirachoonkul, “Estimators in simple random sampling: Searls approach,” Songklanakarin Journal of Science and Technology, vol. 35, no. 6, pp. 749–760, November–December 2013.
[8] C. Kadilar and H. Cingi, “A study on the chain ratio - type estimator,” Hacettepe Journal of Mathematics and Statistics, vol. 32, pp. 105–108, 2003.
[9] A. K. Gupta and D. G. Kabe, Theory of Sample Surveys. Singapore: World Scientific Publishing, 2011.
[10] P.V. Sukhatme, Sampling Theory of Surveys with Applications. Iowa: Iowa State University Press, 1954, pp. 278.
