Fuzzy-Weighted Ranked Set Sampling Method

Author:

Cetintav Bekir1,Gürler Selma2,Demirel Neslihan2

Affiliation:

1. Burdur Mehmet Akif Ersoy University, Turkey

2. Dokuz Eylul University, Turkey

Abstract

Sampling method plays an important role for data collection in a scientific research. Ranked set sampling (RSS), which was first introduced by McIntyre, is an advanced method to obtain data for getting information and inference about the population of interest. The main impact of RSS is to use the ranking information of the units in the sampling mechanism. Even though most of theoretical inferences are made based on exact measurement of the variable of interest, the ranking process is done with an expert judgment or concomitant variable (without exact measurement) in practice. Because of the ambiguity in discriminating the rank of one unit with another, ranking the units could not be perfect, and it may cause uncertainty. There are some studies focused on the modeling of this uncertainty with a probabilistic perspective in the literature. In this chapter, another perspective, a fuzzy-set-inspired approach, for the uncertainty in the ranking mechanism of RSS is introduced.

Publisher

IGI Global

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