Ratio Method to the Mean Estimation Using Coefficient of Skewness of Auxiliary Variable

Efficient Ratio-Type Estimators of Finite Population Mean Based on Correlation Coefficient

“…To get more insight another important tool relative root mean square error (RRMSE) is computed in this study. It is most useful measure to compare the precision of the estimators (see, e.g., Yan and Tian [12], Munoz et al [27], Alvarez et al [28] and Irfan et al [22]). The RRMSE of an estimator can be calculated by the relation given below…”

“…On this issue extensive work has been done using auxiliary information such as population median, mean, quartiles, deciles, coefficient of variation, coefficient of correlation, coefficient of skewness and coefficient of kurtosis etc. As a solution of this issue various estimator(s) or classes of estimators have been proposed to get improved results by several authors including Sisodia and Dwivedi [2], Upadhyaya and Singh [3], Singh and Tailor [4], Kadilar and Cingi [5,6], Singh et al [7,8], Gupta and Shabbir [9], Koyuncu and Kadilar [10,11], Yan and Tian [12], Haq and Shabbir [13], Singh and Solanki [14], Yadav and Kadilar [15], Subramani and Kumarapandiyan [16,17], Subramani and Prabavathy [18], Yadav et al [19], Khan et al [20], Kumar [21], Irfan et al [22], Walia et al [23] and many more.…”

Improved Ratio Estimators Using Some Robust Measures

“…When the population parameters of the auxiliary variable, such as population mean, kurtosis, skewness, coefficient of variation, median, quartiles, correlation coefficient, deciles etc., are known, ratio estimators and their modifications are available in the literature which perform better than the usual sample mean under the SRSWOR. For further details on the modified ratio estimators, readers are referred to Abid et al [1], [2], [3] and [4], Subramani and Kumarapandiyan [29], [30], [31], [32] and [33], Yan and Tian [37], Kadilar and Cingi [10] and [13], Upadhyaya and Singh [35], and Sisodia and Dwivedi [26] and reference therein.…”

New Class of Almost Unbiased Modified Ratio Cum Product Estimators with Knownparameters of Auxiliary Variables

“…So we have suggested new class modified ratio cum product estimators for estimating the population mean of the study variable. To know more abouthistorical developments of the estimation of population mean are referred to Cochran [1,2], Subramani and Master Ajith [4,5], Murthy [7,8], Subramani[14], Subramani and kumarapandiyan [15,16,17], Upadhyaya and Singh [18], Yan and Tian [19] and the references cited there in. Consider a finite population U of size N consisting of 1 , 2 , 3 … .…”