Open Access
Research Article
An efficient class of regression estimators using conventional measures
*Muhammad IjazCorresponding authorm.ijaz@uoh.edu.pkDepartment of Mathematics and StatisticsUniversity of HaripurHaripur, PakistanView full profile → , Syed Muhammad AsimDepartment of Mathematics and StatisticsUniversity of HaripurHaripur, PakistanView full profile → , Bushra HaiderDepartment of Mathematics and StatisticsUniversity of HaripurHaripur, PakistanView full profile → , Samir BrahimDivision of Information and Computing TechnologyCollege of Science and EngineeringHamad Bin Khalifa UniversityQatarView full profile → , Tolga ZamanDepartment of StatisticsCankiri Karatekin UniversityTurkeyView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 31 Dec 2020
- Accepted:
- 31 Dec 2021
- Published Online:
- 10 Aug 2023
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JSMS-928
- Pages:
- 823–832
Abstract
The study suggests a class of regression type estimators for estimating the population mean when there exist either a positive or negative correlation between a study and auxiliary variable. The auxiliary attributes have been used in the form of the standard deviation, coefficient of kurtosis, mean deviation, quartile deviation, median and 10th decile. The bias and mean squared error has studied up to the first order of approximation. A comparison is made both theoretically and numerically with some existing regression estimators. It is observed that the suggested class of estimators provides more reliable and efficient results than others.
Keywords
Subject Classifications
62D05
References
[1]Cochran, W. G. (1940). The estimation of the yields of cereal experiments by sampling for the ratio of grain to total produce. The Journal of Agricultural Science, 30(2), 262-275.
[2]Kadilar, C., & Cingi, H. (2004). Ratio estimators in simple random sampling. Applied Mathematics and Computation, 151(3), 893-902.
[3]Kadilar, C. & Cingi, H. (2006), ‘An improvement in estimating the population mean by using the correlation coefficient’, Hacettepe Journal of Mathematics and Statistics 35(1), 103–109
[4]Yan, Z. and Tian, B. (2010). Ratio Method to the Mean Estimation Using Coefficient of Skewness of Auxiliary Variable, ICICA 2010, Part II, CCIS 106, pp. 103–110
[5]Subramani, J. and Kumarapandiyan, G. (2012a). Estimation of Population Mean using Co-efficient of variation and Median of an Auxiliary Variable. International Journal of Probability and Statistics, (1), 111–118.
[6]Subramani, J. and Kumarapandiyan, G. (2012b). Estimation of population mean using known median and co-efficient of skewness. American Journal of Mathematics and Statistics, (2), 101-107.
[7]Subramani, J. and Kumarapandiyan, G. (2012c). Modified ratio estimators using known median and co-efficient of kurtosis. American Journal of Mathematics and Statistics, (2), 95–100.
[8]Jeelani, M. I. Maqbool, S. and Mir, S. A. (2013). Modified ratio estimators of population mean using linear combination of coefficient of skewness and quartile deviation. International Journal of Modern Mathematical Sciences, (6), 174–183.
[9]Subzar, M. A., Maqbool, S., Raja, T. A., Shabeer, M., & Lone, B. A. (2017). A Class of Improved Ratio Estimators for Population Mean using Conventional Location parameters. Int. J. Modern Math. Sci, 15(2), 187-205.
[10] Ünal, C., & Kadilar, C. (2020). Exponential type estimator for the population mean in the presence of non-response. Journal of Statistics and Management Systems, 23(3), 603-615.
[11] Pal, S.K., Singh, H.P. & Solanki, R.S. (2020). A new efficient class of estimators of finite population mean in simple random sampling. Afr. Mat. 31, 595–607.
[12] Irfan, M., Javed, M., Bhatti, S. H., Raza, M. A., & Ahmad, T. (2020). Almost unbiased optimum estimators for population mean using dual auxiliary information. Journal of King Saud University-Science, 32(6), 2835-2844.
[13] Zamanzade, E., & Mahdizadeh, M. (2020). Using ranked set sampling with extreme ranks in estimating the population proportion. Statistical Methods in Medical Research, 29(1), 165-177.
[14] Cekim, H. O., & Kadilar, C. (2020). In-type estimators for the population variance in stratified random sampling. Communications in Statistics-Simulation and Computation, 49(7), 1665-1677.
[15] Yadav, S. K., & Zaman, T. (2021). Use of some conventional and non-conventional parameters for improving the efficiency of ratio-type estimators. Journal of Statistics and Management Systems, 24(5), 1077-1100.
[16] Singh, D., & Chaudhary, F. S. (1986). Theory and analysis of sample survey designs. John Wiley & Sons.
[17] Subzar, M., Maqbool, S., Verma, M. R., & Raja, T. A. (2017). An improved class of ratio estimators for estimating population mean using auxiliary information in survey sampling. Journal of Reliability and Statistical Studies, 10(2), 65-82.
Views: 162Downloads: 73Citations: 0
