Bayesian modeling and prior sensitivity analysis for zero–one augmented beta regression models with an application to psychometric data

Bayesian modeling and prior sensitivity analysis for zero–one augmented beta regression models with an application to psychometric data

Danilo Covaes Nogarotto, Caio Lucidius Naberezny Azevedo, Jorge Luis Bazán

ARTIGO

Inglês

The interest on the analysis of the zero–one augmented beta regression (ZOABR) model has been increasing over the last few years. In this work, we developed a Bayesian inference for the ZOABR model, providing some contributions, namely: we explored the use of Jeffreys-rule and independence Jeffreys...

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ

FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESP

Fechado

Bayesian modeling and prior sensitivity analysis for zero–one augmented beta regression models with an application to psychometric data

Danilo Covaes Nogarotto, Caio Lucidius Naberezny Azevedo, Jorge Luis Bazán


										

Bayesian modeling and prior sensitivity analysis for zero–one augmented beta regression models with an application to psychometric data

Danilo Covaes Nogarotto, Caio Lucidius Naberezny Azevedo, Jorge Luis Bazán

    Fontes

    Revista brasileira de probabilidade e estatística

    Vol. 34, no. 2 (May, 2020), p. 304-322