A novel cosine-derived probability distribution: Theory and data modeling with computer knowledge graph

Jianping Zhu, Xuxun Cai, Eslam Hussam, Jin Taek Seong, Fatimah A. Almulhima, Afaf Alrashidi

Research output: Contribution to journalArticlepeer-review

Abstract

It is a deep-rooted and already observed reality that probabilistic models play an important role in describing and explaining the events/situations under consideration. Focusing attention on the fundamental role and applicability of the probabilistic models, this article considers the development of a new probability model derived through the implementation of a trigonometric function. The suggested model is named as a new cosine flexible Weibull (NCF-Weibull) distribution. This model is accomplished by exploiting the cosine functional approach. Some statistical characteristics of the NCF-Weibull distribution are given. Alongside, the estimates of the NCF-Weibull model are also obtained. Besides them, a simulation study for different settings of the parameter values of the NCF-Weibull model is also provided. Through the simulation study it is evidenced that the estimators of the NCF-Weibull distribution consistently perform well in terms of stability, consistency, and efficiency. Finally, the optimality of the NCF-Weibull distribution is judged by using two applications from different sectors. Based on five evaluation criteria alongside the p-value, the NCF-Weibull distribution shows optimal performances for both data sets.

Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalAlexandria Engineering Journal
Volume103
DOIs
StatePublished - Sep 2024

Keywords

  • Distributional characteristics
  • Flexible Weibull distribution
  • Reliability data analysis
  • Simulation
  • Trigonometric approached

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