An Improvement in Regression Estimator Through Exponential Estimator Using Two Auxiliary Variables
DOI:
https://doi.org/10.13052/jrss0974-8024.1627Keywords:
Mean square error (MSE), auxiliary variables, ratio estimator and regression estimatorAbstract
For the case of simple random sampling, we are introducing a new regression estimator for the population mean with the supporting values of two auxiliary variables. The results for the mean square error (MSE) of the new form of regression estimator is fined. The mean square error’s results have also been checked through numerical illustration. It is observed that our introduced estimator is having less mean square error than the traditional ratio and regression estimator for two auxiliary variables.
Downloads
References
Cochran WG. Sampling Techniques. New York: John Wiley & Sons; 1977.
Murthy MN. Sampling Theory and Methods. Calcutta: Statistical Publishing Society; 1967.
Akingbade T., Okafor F. (2019): A class of Ratio-Type Estimator Using Two Auxiliary Variables for Estimating the Population Mean with Sum Known Population Parameters, Pakistan Journal of statistics and operation research, Vol. XV, No. 2, 329–340.
M. Amin, M. Hanif and C. Kadilar (2014): Improved Exponential Type Estimators using the Information of Two Auxiliary Variables, Middle-East Journal of Scientific Research 19(12): 1711–1715.
C. Kadilar, H. Cingi (2005): A new estimator using two auxiliary variables, Applied Mathematics and Computation 162, 901–908.
Subramani J. (2018): Two parameter modified ratio estimators with two auxiliary variables for the estimation of finite population mean, Biometrics & Biostatistics International Journal, Volume 7 Issue 6 559–568.
Manoj K. Chaudhary and Amit Kumar (2020): An Improvement in Estimation of Population Mean using Two Auxiliary Variables and Two- Phase Sampling Scheme under Non-Response, Journal of Reliability and Statistical Studies, Vol. 13, 349–362.
Singh D, Chaudhary FS. Theory and analysis of sample survey designs. New Age International Publisher. 1986.
Kadilar C, Cingi H. Advances in Sampling Theory – Ratio Method of Estimation. Bentham Science Publishers. 2009.
