A New Estimator for Mean Estimation in Simple Random Sampling
Abstract
Nowadays, the decision makers are interested in the computation of population mean to develop certain decision making policies in the various field of business, agriculture, medical science, economics, demography and engineering. In this paper, authors suggest a new estimator for estimating the population mean in simple random sampling and determine the mean square error (MSE) of this estimator. The authors also show that the suggested estimator is more efficient than the existing ratio estimators theoretically and numerically.
How to cite this article: Aggarwal S, Soni SS. A New Estimator for Mean Estimation in Simple Random Sampling J Adv Res Appl Math Stat 2022; 7(1&2): 1-4.
DOI: https://doi.org/10.24321/2455.7021.202201
References
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information, Biometrika. 1981; 68(1): 341-343.
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6. Kadilar C, Cingi H. Ratio estimators in simple random sampling. Applied Mathematics and Computation 2004;
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8. Kadilar C, Cingi H. Ratio estimators for the population variance in simple and stratified random sampling, Applied Mathematics and Computation 2006; 173(2): 1047-1059.
9. Wolter KM. Introduction to variance estimation, 2ed, Springer, New York, USA. 2005.
10. Cochran WG. Sampling techniques, 1ed, Asian Publishing House, Bombay. 1953.
11. Koyuncu N, Kadilar C. On improvement in estimating population mean in stratified random sampling. Journal of Applied Statistics 2010; 37(6): 999-1013.
12. Singh HP, Tailor R, Kakran MS. An improved estimator of population mean using power transformation. Journal of Indian Society of Agricultural Statistics 2004; 58(2): 223-230.
13. Suleiman SA, Adewara AA. Improved modified ratio estimation of population mean using information on size of the sample. Tanzania Journal of Science 2021; 47(5), 1753-1765.
14. Verma HK, Sharma P, Singh R. Improved estimator of finite population mean using auxiliary attribute in stratified random sampling. Journal of Scientific Research 2014; 58: 99-105.
15. Solanki RS, Singh HP, Pal SK. Improved estimation of finite population mean in sample surveys. Columbia
International Publishing Journal of Advanced Computing 2013; 1: 70-78.
16. Solanki RS, Singh HP. Improved estimation of population mean in using population proportion of an auxiliary
character. Chilean Journal of Statistics 2013; 4(1): 3-17.
17. Irfan M, Javed M, Lin Z. Enhanced estimation of population mean in the presence of auxiliary information. Journal of King Saud University-Science 2019; 31: 1373-1378.
18. Solanki RS, Singh HP. An improved class of estimators for the general population parameter using auxiliary
information. Communications in Statistics-Theory and Methods 2015; 44(20): 4241-4262.
19. Aggarwal S, Soni SS, Chaubey RS. Estimation of the population mean by developing a new estimator. Bulletin of Pure and Applied Sciences Section-E-Mathematics & Statistics 2022; 41E(1): 11-15.
2. Srivastava SK. A class of estimators using auxiliary information in sample surveys, Canadian Journal of Statistics, 1980; 8(2), 253-254.
3. Srivastava SK, Jhajj HS. A class of estimators of the population mean in survey sampling using auxiliary
information, Biometrika. 1981; 68(1): 341-343.
4. Bahl S, Tuteja RK. Ratio and product type exponential estimators. Information and Optimization Sciences 1991;
12(1): 159-163.
5. Singh HP, Tailor R. Use of known correlation coefficient in estimating the finite population mean. Statistics in
Transition 2003; 6: 555-560.
6. Kadilar C, Cingi H. Ratio estimators in simple random sampling. Applied Mathematics and Computation 2004;
151(3): 893-902.
7. Sisodia BVS, Dwivedi VK. A modified ratio estimator using coefficient of variation of auxiliary variable. Journal of Indian Society of Agricultural Statistics 1981; 33: 13-18.
8. Kadilar C, Cingi H. Ratio estimators for the population variance in simple and stratified random sampling, Applied Mathematics and Computation 2006; 173(2): 1047-1059.
9. Wolter KM. Introduction to variance estimation, 2ed, Springer, New York, USA. 2005.
10. Cochran WG. Sampling techniques, 1ed, Asian Publishing House, Bombay. 1953.
11. Koyuncu N, Kadilar C. On improvement in estimating population mean in stratified random sampling. Journal of Applied Statistics 2010; 37(6): 999-1013.
12. Singh HP, Tailor R, Kakran MS. An improved estimator of population mean using power transformation. Journal of Indian Society of Agricultural Statistics 2004; 58(2): 223-230.
13. Suleiman SA, Adewara AA. Improved modified ratio estimation of population mean using information on size of the sample. Tanzania Journal of Science 2021; 47(5), 1753-1765.
14. Verma HK, Sharma P, Singh R. Improved estimator of finite population mean using auxiliary attribute in stratified random sampling. Journal of Scientific Research 2014; 58: 99-105.
15. Solanki RS, Singh HP, Pal SK. Improved estimation of finite population mean in sample surveys. Columbia
International Publishing Journal of Advanced Computing 2013; 1: 70-78.
16. Solanki RS, Singh HP. Improved estimation of population mean in using population proportion of an auxiliary
character. Chilean Journal of Statistics 2013; 4(1): 3-17.
17. Irfan M, Javed M, Lin Z. Enhanced estimation of population mean in the presence of auxiliary information. Journal of King Saud University-Science 2019; 31: 1373-1378.
18. Solanki RS, Singh HP. An improved class of estimators for the general population parameter using auxiliary
information. Communications in Statistics-Theory and Methods 2015; 44(20): 4241-4262.
19. Aggarwal S, Soni SS, Chaubey RS. Estimation of the population mean by developing a new estimator. Bulletin of Pure and Applied Sciences Section-E-Mathematics & Statistics 2022; 41E(1): 11-15.
Published
2022-08-31
How to Cite
AGGARWAL, Sudhanshu; SONI, Shiv Shankar.
A New Estimator for Mean Estimation in Simple Random Sampling.
Journal of Advanced Research in Applied Mathematics and Statistics, [S.l.], v. 7, n. 1&2, p. 1-4, aug. 2022.
ISSN 2455-7021.
Available at: <http://thejournalshouse.com/index.php/Journal-Maths-Stats/article/view/592>. Date accessed: 22 dec. 2024.
Section
Research Article
