A new distributional approach: estimation, Monte Carlo simulation and applications to the biomedical data sets

被引:3
|
作者
Kamal, Mustafa [1 ]
Alsolmi, Meshayil M. [2 ]
Nayabuddin [3 ]
Al Mutairi, Aned [4 ]
Hussam, Eslam [5 ]
Mustafa, Manahil SidAhmed [6 ]
Nassr, Said G. [7 ]
机构
[1] Saudi Elect Univ, Dept Basic Sci, Coll Sci & Theoret Studies, Dammam 32256, Saudi Arabia
[2] Univ Jeddah, Dept Math, Coll Arts & Sci Khulis, Jeddah, Saudi Arabia
[3] Jazan Univ, Dept Epidemiol, Coll Publ Hlth & Trop Med, Jizan, Saudi Arabia
[4] Princess Nourah Bint Abdulrahman Univ, Dept Math Sci, Coll Sci, POB 84428, Riyadh 11671, Saudi Arabia
[5] Helwan Univ, Dept Math, Fac Sci, Helwan, Egypt
[6] Univ Tabuk, Dept Stat, Fac Sci, Tabuk, Saudi Arabia
[7] Arish Univ, Fac Commerce, Dept Stat & Insurance, Al Arish 45511, Egypt
关键词
Weibull distribution; heavy-tailed distributions; T-X family; healthcare sector; data modeling; China; Mexico; Holland; COVID-19; IMPACT;
D O I
10.3934/nhm.2023069
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper introduces the generalized exponential-U family of distributions as a novel methodological approach to enhance the distributional flexibility of existing classical and modified distributions. The new family is derived by combining the T-X family method with the exponential model. The paper presents the generalized exponential-Weibull model, an updated version of the Weibull model. Estimators and heavy-tailed characteristics of the proposed method are derived. The new model is applied to three healthcare data sets, including COVID-19 patient survival times and mortality rate data set from Mexico and Holland. The proposed model outperforms other models in terms of analyzing healthcare data sets by evaluating the best model selection measures. The findings suggest that the proposed model holds promise for broader utilization in the area of predicting and modeling healthcare phenomena.
引用
收藏
页码:1575 / 1599
页数:25
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