The Dual-Dagum family of distributions: Properties, regression and applications to COVID-19 data

Autor:	Elisângela Candeias Biazatti, Gauss Moutinho Cordeiro, Maria do Carmo Soares de Lima
Rok vydání:	2022
Předmět:	Statistics and Probability Applied Mathematics Modeling and Simulation
Zdroj:	Model Assisted Statistics and Applications. 17:199-210
ISSN:	1875-9068 1574-1699
DOI:	10.3233/mas-221354
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::0624b08c7e927e6a294da1d563c24818 https://doi.org/10.3233/mas-221354 Zobrazit plný text záznamu