包含协变量和删节数据的COVID-19数据建模的Weibull-Beta Prime分布

IF 0.9 Q4 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Stats Pub Date : 2022-11-17 DOI:10.3390/stats5040069
Elisângela C. Biazatti, G. Cordeiro, Gabriela M. Rodrigues, E. Ortega, L. H. de Santana
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引用次数: 3

摘要

由于近年来β素数分布的普及,提出了一种更灵活的泛化方法来拟合对称或非对称和双峰数据,以及非单调故障率。由此,定义了Weibull-beta素数分布,并得到了它的一些结构性质。采用极大似然法对参数进行估计,提出了一种新的回归模型。一些模拟表明,估计量是一致的,对删减的COVID-19数据的应用表明了模型的充分性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Weibull-Beta Prime Distribution to Model COVID-19 Data with the Presence of Covariates and Censored Data
Motivated by the recent popularization of the beta prime distribution, a more flexible generalization is presented to fit symmetrical or asymmetrical and bimodal data, and a non-monotonic failure rate. Thus, the Weibull-beta prime distribution is defined, and some of its structural properties are obtained. The parameters are estimated by maximum likelihood, and a new regression model is proposed. Some simulations reveal that the estimators are consistent, and applications to censored COVID-19 data show the adequacy of the models.
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来源期刊
CiteScore
0.60
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