Vücut Yağı Verisi Kullanılarak Sıralı Küme Örneklemesine Dayalı Dağılım Fonksiyonu Kestiricilerinin Performansları

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.