A Generalized Class of Ratio Type Exponential Estimators of Population Mean Under Linear Transformation of Auxiliary Variable

Hartley-Ross Type Unbiased Estimators of Population Mean Using Two Auxiliary Variables

“…A comparison between all unbiased/Hartley-Rosstype unbiased estimators, i.e., y (u) 0 , y (u) HR , y (u) S1 , y (u) S2 , y (u) CK1 , y (u) CK2 , and y (u) P reveals that y (u) P provides maximum gain in PREs as compared to others. This gain in PREs is based on the fact that the proposed estimators use the information on two auxiliary variables, while the others use the information on only one auxiliary variable; The proposed family of estimators also provides greater PREs than the well-known Grover and Kaur [23] class of biased estimators, i.e., y GK . This class considers the information on only one auxiliary variable;…”

“…Var y (u) HR = Y 2 C 2 y + C 2 x 2 yx C y C x : (5) -Grover and Kaur [23] followed the lines of Gupta and Shabbir [24] and Shabbir and Gupta [25] and suggested a generalized class based on ratio-type exponential estimators as follows:…”

A control chart using an auxiliary variable and repetitive sampling for monitoring process mean

“…For more details, readers may refer to Isaki, [12] Naik and Gupta, [13] Upadhyaya and Singh, [14] Magnus, [15] Singh et al, [16] Shu et al, [17] Riaz, [18,19] Cheng and Chen, [20] Sodipo, [21] Riaz, [22] Yadav, [23] Singh and Solanki, [24] Grover and Kaur. [25] Riaz [18] proposed the Vr control chart for monitoring process variability using the information of an auxiliary variable based on a regression-type estimator of variance and showed that its performance increases as the correlation between the main variable and the auxiliary variable increases. Riaz [19] proposed a control chart to monitor process variability using the auxiliary information.…”

A new estimator based on auxiliary information through quantitative randomized response techniques

“…Diana andPerri (2011), Sousa, Shabbir, Real, andGupta (2010), and Gupta, Shabbir, Sousa, and Real (2012) suggested mean estimators using the auxiliary variable for estimating of the quantitative sensitive variable in RRT. Bahl and Tuteja (1991), Gupta (2011), Grover andKaur (2014), and Özgül and Cingi (2014) studied exponential-type estimators to obtain more efficient estimates for various sampling methods. In the current study, an exponential-type estimator of the mean of a sensitive variable is proposed using a non-sensitive auxiliary variable for generalized partial quantitative RRT.…”