12th International Statistics Days Congress (ISDC2022), İzmir, Türkiye, 13 - 16 Ekim 2022
Ranked set sampling (RSS), suggested by McIntyre
(1952), is a popular sampling strategy when the measurements of the sample
units are relatively difficult (expensive and/or time-consuming). The
estimation of distribution function has received considerable attention in the
literature of RSS. Because many practical problems involve estimation of
distribution function from experimental data. Many authors have proposed
empirical distribution functions (EDFs) based on RSS and its modifications
(see, for example, Stokes and Sager, 1988; Samawi and Al-Sagher, 2001, Nazari
et al., 2016 and Zamanzade, 2019). For finite population setting, there are a
few studies on estimation of distribution function (see, for example, Sevil and
Yildiz, 2017, 2020; Yildiz and Sevil, 2019). In this study, design-based
estimators for distribution function have been developed using RSS designs
(level-0, level-1 and level-2). Some of their asymptotic properties have been
investigated. Theoretical and numerical results show that the level-2 sampling
design provides a more efficient EDF estimator than its counterparts of
level-0, leve-1 and simple random sampling.