Marcelo Bourguignon | DeepAI

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Featured Co-authors

Roberto Vila
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Helton Saulo
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Manoel Santos-Neto
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Vera Tomazella
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Jeremias Leão
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Diego I. Gallardo
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Christian Caamaño Carrillo
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Francisco M. C. Medeiros
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Mehmet N. Çankaya
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∙ 07/13/2022

Parametric quantile regression for income data

Univariate normal regression models are statistical tools widely applied...

0 Helton Saulo, et al. ∙

∙ 06/26/2022

The shared weighted Lindley frailty model for cluster failure time data

The primary goal of this paper is to introduce a novel frailty model bas...

0 Diego I. Gallardo, et al. ∙

∙ 10/09/2021

A parametric quantile beta regression for modeling case fatality rates of COVID-19

Motivated by the case fatality rate (CFR) of COVID-19, in this paper, we...

0 Marcelo Bourguignon, et al. ∙

∙ 09/27/2021

A Bimodal Model for Extremes Data

In extreme values theory, for a sufficiently large block size, the maxim...

0 Cira E. G. Otiniano, et al. ∙

∙ 08/18/2021

A Model for Bimodal Rates and Proportions

The beta model is the most important distribution for fitting data with ...

0 Roberto Vila, et al. ∙

∙ 06/19/2021

On the bimodal Gumbel model with application to environmental data

The Gumbel model is a very popular statistical model due to its wide app...

0 Cira E. G. Otiniano, et al. ∙

∙ 03/12/2021

Parametric quantile regression models for fitting double bounded response with application to COVID-19 mortality rate data

In this paper, we develop two fully parametric quantile regression model...

0 Diego I. Gallardo, et al. ∙

∙ 08/26/2020

Improved estimators in beta prime regression models

In this paper, we consider the beta prime regression model recently prop...

0 Francisco M. C. Medeiros, et al. ∙

∙ 12/19/2018

The negative binomial beta prime regression model with cure rate

This paper introduces a cure rate survival model by assuming that the ti...

0 Jeremias Leão, et al. ∙

∙ 04/20/2018

A new regression model for positive data

In this paper, we propose a regression model where the response variable...

0 Marcelo Bourguignon, et al. ∙

∙ 12/12/2017

Zero-Modified Poisson-Lindley distribution with applications in zero-inflated and zero-deflated count data

The main object of this article is to present an extension of the zero-i...

0 Danillo Xavier, et al. ∙

∙ 11/29/2017

Extended Poisson INAR(1) processes with equidispersion, underdispersion and overdispersion

Real count data time series often show the phenomenon of the underdisper...

0 Marcelo Bourguignon, et al. ∙

∙ 11/29/2017

Fractional approaches for the distribution of innovation sequence of INAR(1) processes

In this paper, we present a fractional decomposition of the probability ...

0 Josemar Rodrigues, et al. ∙

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