Elisângela C. Biazatti, G. Cordeiro, Maria do Carmo Soares de Lima
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引用次数: 3
Abstract
A new Dual-Dagum-G (DDa-G) family is defined as a good competitor to the Beta-G and Kumaraswamy-G generators, which are widely applied in several areas. Some of its mathematical properties are addressed. We obtain the maximum likelihood estimates, and some simulations prove the consistency of the estimates. The flexibility of this family is shown through a COVID-19 data set. We propose a new regression based on a special distribution of the DDa-G family, and provide a sensitivity analysis by using data from 1,951 COVID-19 patients collected in Curitiba, Brazil.
期刊介绍：
Model Assisted Statistics and Applications is a peer reviewed international journal. Model Assisted Statistics means an improvement of inference and analysis by use of correlated information, or an underlying theoretical or design model. This might be the design, adjustment, estimation, or analytical phase of statistical project. This information may be survey generated or coming from an independent source. Original papers in the field of sampling theory, econometrics, time-series, design of experiments, and multivariate analysis will be preferred. Papers of both applied and theoretical topics are acceptable.
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