Year-end Sale % OFF 
Abstract
In this study, an application of empirical distribution function (EDF) estimators based on ranked set sampling (RSS) using real-life data set (body fat data) is illustrated. In this application, three variables which are percentage of body fat (Y), abdomen circumference (X1) and age (X2) are used. Age and abdomen circumference are separately used in ranking process as auxiliary variables which have correlation 0.813 (for perfect ranking) and 0.291 (for imperfect ranking) with the percentage of body fat, respectively. Ranked set samples are constructed by using three different sampling designs which are level-0 level-1 and level-2. The effects of perfect and imperfect ranking on the estimators of the sampling designs are investigated. Relative efficiencies of the EDF estimators are obtained by using their mean squared errors (MSE) and integrated mean squared errors (IMSE), numerically. For both perfect and imperfect ranking, these EDF estimators based on sampling designs have outperformance against EDF estimator based on SRS.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
