Inference on the Beta Type I Generalized Half Logistic Distribution under Right-Censored Observation with Application to COVID-19

被引：0

作者：

Awodutire, Phillip Oluwatobi ^{[1
]}

Nduka, Ethelbert Chinaka ^{[2
]}

Ijomah, Maxwell Azubike ^{[2
]}

Ilori, Oluwatosin Ruth ^{[3
]}

Balogun, Oluwafemi Samson ^{[4
]}

机构：

[1] Univ Africa, Dept Math & Comp Sci, Toru Orua, Bayelsa State, Nigeria

[2] Univ Port Harcourt, Dept Math & Stat, Port Harcourt, Rivers State, Nigeria

[3] Ladoke Akintola Univ Technol, Teaching Hosp, Dept Community Med, Ogbomosho, Nigeria

[4] Univ Eastern Finland, Sch Comp, Kuopio, Finland

来源：

INTERNATIONAL JOURNAL OF MATHEMATICS AND MATHEMATICAL SCIENCES | 2022年 / 2022卷

关键词：

D O I：

10.1155/2022/6858109

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In real-life situations, censoring issues do arise due to the incompleteness of data. This article examined the inferences on right-censored beta type I generalized half logistic distribution. In this work, some statistical properties of the beta type I generalized half logistic distribution were derived. Furthermore, the beta type I generalized half logistic distribution was studied under a censoring situation in the presence and absence of covariates. Estimation of model parameters was conducted using the maximum likelihood estimation method. A simulation study was carried out to assess the performance of the parameters of the model in terms of efficiency and consistency. In a real-life application, the model was applied to COVID-19 data and the necessary inferences were drawn.

引用

页数：13

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