Median Estimation Using Double Sampling

Abstract

This paper proposes a general class of estimators for estimating the median in double sampling. The position estimator, stratification estimator and regression type estimator attain the minimum variance of the general class of estimators. The optimum values of the first-phase and second-phase sample sizes are also obtained for the fixed cost and the fixed variance cases. An empirical study examines the performance of the double sampling strategies for median estimation. Finally, an extension of the methods of Chen & Qin (1993) and Kuk & Mak (1994) is considered for the double sampling strategy.

Effective estimation strategy of finite population variance using multi-auxiliary variables in double sampling

“…Three sets of independent random numbers were generated of size N (N = 100), k x , k y , and k z (k = 1, 2, 3,…, N) from a standard normal distribution via R. Motivated by the artificial data set generation techniques adopted by S. Singh and Deo (2003) and S. Singh, Joarder, and Tracy (2001), the following transformed variables of U were generated with the values of …”

A quantile estimator under two-phase sampling for stratification

“…Singh et al [14] defined a quantile estimator under two-phase sampling based upon stratification. We now introduce this stratification estimator and its variance estimator, which were only defined for the case β = 0.5, i.e.…”

Estimation of Median in the Presence of Three Known Quartiles of an Auxiliary Variable

“…While the problem of estimating a population mean in the presence of an auxiliary variable has been widely discussed in the finite population sampling literature, relatively less effort has been devoted to the development of efficient methods for estimating a finite population median. Chambers and Dunstan (1986), Kuk and Mak (1989), Mak and Kuk (1993), Rao et al (1990), Meeden and Vardeman (1991), Meeden (1995), Garcia and Cebrian (2001), Singh et al (2001, Rueda and Arcos (2002), Allen et al (2002), Singh and Puertas (2003), , Singh, Sidhu and Singh (2006), Singh, Singh and Puertas (2006), Singh, Tailor, Singh and Kim (2007), Singh and Solanki (2013) and Sharma and Singh (2014) addressed the importance of estimating the population median in the presence of an auxiliary variable.…”