Modified Exponential Type Estimator for Population Mean Using Auxiliary Variables in Stratified Random Sampling

Bu çalışmada, kitle ortalaması için yardımcı değişken bilgisi kullanarak yeni bir üstel tip tahmin edici tabakalı örneklemede geliştirilmiştir. Elde edilen tahmin edicinin etkinliğini değerlendirebilmek için, ilk olarak literatürdeki bazı tahmin ediciler incelenmiş ve önerilen stratejinin optimum özelliği incelenmiştir. Önerilen tahmin edicinin özelliğini değerlendirebilmek için optimallik koşulu altında benzetim çalışması ve gerçek veri uygulamaları yapılmıştır. Sonuçlar elde edilen tahmin edicinin var olan oran ve çarpım tahmin edicilerinden ve tabakalı örnekleme düzeninde yansız tahmin ediciden daha etkin olduğunu göstermiştir

Tabakalı Rasgele Örneklemede Yardımcı Değişkenler Kullanarak Kitle Ortalaması İçin Değiştirilmiş Üstel Tip Tahmin Edici

Technology s perpetual vicissitude and product models distinction in industrial market have a crucial effect on forecasting demand for spare components. In order to set forth the future demand rates for products, inventory managers repetitively update their prognostications. Bayesian model is utilizing a prior probability distribution for the injunctive authorization rate which was habituated in order to get optimum levels of account over a number of periods. However, under sundry demand rates like intermittent demand, Bayesian Model s performance has not been analyzed. With the help of a research question, the study investigates that circumstance.

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