Journals / Mugla Journal of Science and Technology / 2026 / Volume: 11 Issue: 1

UNIT FAV-JERRY DISTRIBUTION: PROPERTIES AND APPLICATIONS

BİRİM FAV-JERRY DAĞILIMI: ÖZELLİKLER VE UYGULAMALAR

Kadir Karakaya(SELÇUK ÜNİVERSİTESİ, FEN FAKÜLTESİ)0000-0002-0781-3587
Pages
—
Publication Date
2025-06-30
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally, the practical utility of the new model is demonstrated through two real data analyses.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper introduces a novel bounded statistical distribution and explores its key characteristics, including cumulative distribution, probability density, and hazard rate functions, illustrated using graphical representations.
📊
Key Findings & Data:Estimators for the unknown parameter of new models are assessed, with performance evaluated via bias, mean square errors, average absolute bias, and mean relative error in Monte Carlo simulations.
💡
Conclusion & Impact:Finally, the practical utility of the new model is demonstrated through two real data analyses.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Bounded Statistical Distribution · Bonferroni and Lorenz Curves · Moment Properties

Abstract

This paper introduces a novel bounded statistical distribution and explores its key characteristics, including cumulative distribution, probability density, and hazard rate functions, illustrated using graphical representations. The study examines mathematical properties such as moments, skewness, kurtosis, the Bonferroni and Lorenz curves, and order statistics. Estimators for the unknown parameter of new models are assessed, with performance evaluated via bias, mean square errors, average absolute bias, and mean relative error in Monte Carlo simulations. Finally, the practical utility of the new model is demonstrated through two real data analyses.

Özet

Bu makale yeni bir sınırlı istatistiksel dağılım sunmakta ve grafik gösterimler kullanılarak gösterilen kümülatif dağılım, olasılık yoğunluğu ve tehlike oranı fonksiyonları dahil olmak üzere temel özelliklerini araştırmaktadır. Çalışmada momentler, çarpıklık, basıklık, Bonferroni ve Lorenz eğrileri ve sıra istatistikleri gibi matematiksel özellikler incelenmektedir. Yeni modellerin bilinmeyen parametrelerine ilişkin tahminciler, Monte Carlo simülasyonlarında performans bias, ortalama karesel hatalar, ortalama mutlak bias ve ortalama bağıl hata üzerinden değerlendiriliyor. Son olarak, yeni modelin pratik uygulanabilirliği, iki gerçek veri analizi aracılığıyla gösterilmektedir.

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Cite This Article

Karakaya, K., Sağlam, Ş. (2025). UNIT FAV-JERRY DISTRIBUTION: PROPERTIES AND APPLICATIONS. Mugla Journal of Science and Technology, Volume: 11 Issue: 1. https://doi.org/10.22531/muglajsci.1600995

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