1 citations · 3 across the 7 of their papers we have counts for
7 papers
Semiparametric Modeling for Multivariate Survival Data via Copulas
W. D. R. Miranda Filho, F. N. Demarqui
We propose a new class of multivariate survival models based on archimedean copulas with margins modeled by the Yang and Prentice (YP) model. The Ali-Mikhail-Haq (AMH), Clayton, Fr…
Product Partition Dynamic Generalized Linear Models
Victor S. Comitti, Fábio N. Demarqui, Thiago R. dos Santos +1
Detection and modeling of change-points in time-series can be considerably challenging. In this paper we approach this problem by incorporating the class of Dynamic Generalized Lin…
pexm: a JAGS module for applications involving the piecewise exponential distribution
Vinícius D. Mayrink, João Daniel N. Duarte, Fábio N. Demarqui
In this study, we present a new module built for users interested in a programming language similar to BUGS to fit a Bayesian model based on the piecewise exponential (PE) distribu…
An Unified Semiparametric Approach to Model Lifetime Data with Crossing Survival Curves
Fabio N. Demarqui, Vinicius D. Mayrink, Sujit K. Ghosh
The proportional hazards (PH), proportional odds (PO) and accelerated failure time (AFT) models have been widely used in different applications of survival analysis. Despite their…
A fully likelihood-based approach to model survival data with crossing survival curves
Fabio N. Demarqui, Vinicius D. Mayrink
Proportional hazards (PH), proportional odds (PO) and accelerated failure time (AFT) models have been widely used to deal with survival data in different fields of knowledge. Despi…
Modeling the Association Structure in Doubly Robust GEE for Longitudinal Ordinal Missing Data
José Luiz P. da Silva, Enrico A. Colosimo, Fábio N. Demarqui
Generalized Estimation Equations (GEE) are a well-known method for the analysis of categorical longitudinal responses. GEE method has computational simplicity and population parame…