Titre:	Reparameterized extended Maxwell regression: Properties, estimation and application
Auteur(s):	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
Date de publication:	24-fév-2022
Editeur:	Taylor & Francis
Référence bibliographique:	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
Collection(s) :	Artigos publicados em periódicos e afins

Tous les documents dans DSpace sont protégés par copyright, avec tous droits réservés.