Title:	Reparameterized extended Maxwell regression: Properties, estimation and application
Authors:	Prataviera, Fábio Vila Gabriel, Roberto Cancho, Vicente G. Ortega, Edwin M. M. Cordeiro, Gauss M.
metadata.dc.identifier.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
Issue Date:	24-Feb-2022
Publisher:	Taylor & Francis
Citation:	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
metadata.dc.relation.publisherversion:	https://www.tandfonline.com/doi/abs/10.1080/03610926.2022.2042561
Appears in Collections:	Artigos publicados em periódicos e afins

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