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

Phillip Oluwatobi Awodutire, Ethelbert Chinaka Nduka, Maxwell Azubike Ijomah, Oluwatosin Ruth Ilori, Oluwafemi Samson Balogun and Niansheng Tang

International Journal of Mathematics and Mathematical Sciences, 2022, vol. 2022, 1-13

Abstract: 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.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jijmms:6858109

DOI: 10.1155/2022/6858109

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