Título:	Reparameterized extended Maxwell regression: Properties, estimation and application
Autor(es):	Prataviera, Fábio Vila Gabriel, Roberto Cancho, Vicente G. Ortega, Edwin M. M. Cordeiro, Gauss M.
ORCID:	https://orcid.org/ 0000-0001-8190-1086 https://orcid.org/ 0000-0003-1073-0114 https://orcid.org/ 0000-0003-3999-7402 https://orcid.org/ 0000-0002-3052-6551
Assunto:	Inferência bayesiana Dados experimentais inferência de probabilidade Mediana Modelo de regressão
Data de publicação:	24-Fev-2022
Editora:	Taylor & Francis
Referência:	PRATAVIERA, Fábio et al. Reparameterized extended Maxwell regression: properties, estimation and application. Communications in Statistics - Theory and Methods, 2022. DOI: https://doi.org/10.1080/03610926.2022.2042561.
Abstract:	We propose a reparameterized regression for the median of an extended Maxwell distribution that can be used when the response variable has a positive support. We obtain some structural properties of the distribution. The parameter estimates are obtained by maximum likelihood and Bayesian methods. Some influence measures and quantile residuals are defined. Several Monte Carlo simulations are reported for inference purposes. The new regression is applied to an experimental data set.
DOI:	https://doi.org/10.1080/03610926.2022.2042561
Versão da editora:	https://www.tandfonline.com/doi/abs/10.1080/03610926.2022.2042561
Aparece nas coleções:	Artigos publicados em periódicos e afins

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