Yining Wang , Xintao Ma , Xiaowei Huang , ELsiddig Idriss Mohamed , Alhanouf Alburaikan , Huda M. Alshanbari
{"title":"一种新的蒙特卡罗模拟统计模型:在音乐教育和可靠性工程中的理论与应用","authors":"Yining Wang , Xintao Ma , Xiaowei Huang , ELsiddig Idriss Mohamed , Alhanouf Alburaikan , Huda M. Alshanbari","doi":"10.1016/j.aej.2025.04.055","DOIUrl":null,"url":null,"abstract":"<div><div>Probability distributions are fundamental to the study of real-world phenomena, but there are occasionally very few practical ways to achieve peak performance. As a result of this fact, therefore, numerous researchers have started to pursue new statistical models. This study also proposes a novel statistical model called arcsine tangent flexible Weibull (ASTF-Weibull) distribution. The ASTF-Weibull distribution is the product of combining the flexible Weibull extension distribution with an established trigonometric distributional method. Certain distributional properties, particularly those related to quartiles, are derived for the ASTF-Weibull distribution. The maximum likelihood estimation method is employed to obtain the estimators for the parameters of the ASTF-Weibull distribution. In addition, a simulation study is performed to evaluate the reliability of these estimators. Finally, we conduct a practical exploration of the practicality of the ASTF-Weibull distribution by analyzing two different data sets. Music education is the subject of the first data set, while reliability engineering is the subject of the second data set. Our empirical study provides convincing evidence that the ASTF-Weibull distribution is suitable for modeling both data sets. When comparing the ASTF-Weibull distribution with the conventional and unconventional probability distributions, it is clear that the ASTF-Weibull distribution is superior.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"127 ","pages":"Pages 550-561"},"PeriodicalIF":6.2000,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A new statistical model with Monte Carlo simulation: Theory and applications in music education and reliability engineering\",\"authors\":\"Yining Wang , Xintao Ma , Xiaowei Huang , ELsiddig Idriss Mohamed , Alhanouf Alburaikan , Huda M. Alshanbari\",\"doi\":\"10.1016/j.aej.2025.04.055\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Probability distributions are fundamental to the study of real-world phenomena, but there are occasionally very few practical ways to achieve peak performance. As a result of this fact, therefore, numerous researchers have started to pursue new statistical models. This study also proposes a novel statistical model called arcsine tangent flexible Weibull (ASTF-Weibull) distribution. The ASTF-Weibull distribution is the product of combining the flexible Weibull extension distribution with an established trigonometric distributional method. Certain distributional properties, particularly those related to quartiles, are derived for the ASTF-Weibull distribution. The maximum likelihood estimation method is employed to obtain the estimators for the parameters of the ASTF-Weibull distribution. In addition, a simulation study is performed to evaluate the reliability of these estimators. Finally, we conduct a practical exploration of the practicality of the ASTF-Weibull distribution by analyzing two different data sets. Music education is the subject of the first data set, while reliability engineering is the subject of the second data set. Our empirical study provides convincing evidence that the ASTF-Weibull distribution is suitable for modeling both data sets. When comparing the ASTF-Weibull distribution with the conventional and unconventional probability distributions, it is clear that the ASTF-Weibull distribution is superior.</div></div>\",\"PeriodicalId\":7484,\"journal\":{\"name\":\"alexandria engineering journal\",\"volume\":\"127 \",\"pages\":\"Pages 550-561\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2025-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"alexandria engineering journal\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1110016825005496\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"alexandria engineering journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1110016825005496","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
A new statistical model with Monte Carlo simulation: Theory and applications in music education and reliability engineering
Probability distributions are fundamental to the study of real-world phenomena, but there are occasionally very few practical ways to achieve peak performance. As a result of this fact, therefore, numerous researchers have started to pursue new statistical models. This study also proposes a novel statistical model called arcsine tangent flexible Weibull (ASTF-Weibull) distribution. The ASTF-Weibull distribution is the product of combining the flexible Weibull extension distribution with an established trigonometric distributional method. Certain distributional properties, particularly those related to quartiles, are derived for the ASTF-Weibull distribution. The maximum likelihood estimation method is employed to obtain the estimators for the parameters of the ASTF-Weibull distribution. In addition, a simulation study is performed to evaluate the reliability of these estimators. Finally, we conduct a practical exploration of the practicality of the ASTF-Weibull distribution by analyzing two different data sets. Music education is the subject of the first data set, while reliability engineering is the subject of the second data set. Our empirical study provides convincing evidence that the ASTF-Weibull distribution is suitable for modeling both data sets. When comparing the ASTF-Weibull distribution with the conventional and unconventional probability distributions, it is clear that the ASTF-Weibull distribution is superior.
期刊介绍:
Alexandria Engineering Journal is an international journal devoted to publishing high quality papers in the field of engineering and applied science. Alexandria Engineering Journal is cited in the Engineering Information Services (EIS) and the Chemical Abstracts (CA). The papers published in Alexandria Engineering Journal are grouped into five sections, according to the following classification:
• Mechanical, Production, Marine and Textile Engineering
• Electrical Engineering, Computer Science and Nuclear Engineering
• Civil and Architecture Engineering
• Chemical Engineering and Applied Sciences
• Environmental Engineering