eLsherpieny, E. A., E. M. Almetwally, and H. Z. Muhammed,
" Bivariate Weibull-G Family Based on Copula Function: Properties, Bayesian and non-Bayesian Estimation and Applications ",
STATISTICS, OPTIMIZATION AND INFORMATION COMPUTING , vol. x, issue May, pp. 0 - 31, 2021.
Muhammed, H. Z., E. A. eLsherpieny, and E. M. Almetwally,
" Dependency Measures For New Bivariate Models Based on Copula Function",
Information Sciences Letters, An International Journal, vol. 10, issue 3, pp. 511 - 526, 2021.
eLsherpieny, E. A., E. M. Almetwally, and H. Z. Muhammed,
"Bivariate Weibull-G Family Based on Copula Function: Properties, Bayesian and non-Bayesian Estimation and Applications",
STATISTICS, OPTIMIZATION AND INFORMATION COMPUTING, vol. 10, issue June, pp. 678 - 709, 2022.
Hassan, A. S., M. A. A, H. Zaher, and E. A. Elsherpieny,
"Comparison of Estimators for Exponentiated Inverted Weibull Distribution Based on Grouped Data",
International Journal of Engineering Research and Applications, vol. 4, issue 4, pp. 77-90, 2014.
Hassan, A. S., E. A. Elsherpieny, and R. E. Mohamed,
"Cumulative Residual Extropy for Pareto Distribution in the Presence of Outliers: Bayesian and Non-Bayesian Methods",
STATISTICS, OPTIMIZATION AND INFORMATION COMPUTING , vol. 10, issue Sept., pp. 1095 -1109, 2022.
eLsherpieny, E. A., S. A. Ibrahim, and N. U. Radwan,
"DISCRIMINATING BETWEEN WEIBULL AND LOG-LOGISTIC DISTRIBUTIONS",
International Journal of Innovative Research in Science, Engineering and Technology, vol. 2,, issue 8,, pp. 3358-3371, 2013.
Kholif, A. M., D. A. E. S. Hassan, M. A. Khorshid, E. A. eLsherpieny, and O. A. Olafadehan,
"Implementation of model for improvement (PDCA-cycle) in dairy laboratories",
Journal of Food Safety, vol. 38, issue 1, pp. 1-6, 2018.
Abd-Elfattah, A. M., E. A. El-Sherpieny, S. M. Mohamed, and O. F. Abdou,
"Improvement in estimating the population mean in simple random sampling using information on auxiliary attribute",
Applied Mathematics and Computation, vol. 215, pp. 4198–4202, 2010.
AbstractThis paper proposes some estimators for the population mean by adapting the estimator in Singh et al. (2008) [5] to the ratio estimators presented in Kadilar and Cingi 2006 [2]. We obtain mean square error (MSE) equation for all proposed estimators, and show that all proposed estimators are always more efficient than ratio estimator in Naik and Gupta (1996) [3], and Singh et al. (2008) [5]. The results have been illustrated numerically by taking some empirical population considered in the literature.