In this thesis, we introduce a methodology based on zero-inflated survival data for the purposes of dealing with propensity to default (credit risk) in bank loan portfolios. Our approach enables us to accommodate three ...

In this thesis, we construct distribution functions for analysis of lifetimes with the focus in scenes of latent risks inspired in models of the carcinogenesis process. Some properties of these distribution functions are ...

Modeling of a cure fraction, also known as long-term survivors, is a part of survival analysis. It studies cases where supposedly there are observations not susceptible to the event of interest. Such cases require special ...

In this thesis it is proposed to analyze recurrent event data, recurrent event data with cure fraction and recurrent event data with censoring and competing causes. For the recurrent event data analysis it is proposed a ...

In survival analysis, some studies are characterized by having a significant fraction of units that will never suffer the event of interest, even if accompanied by a long period of time. For the analysis of long-term data, ...

In this work we present a bayesian approach for the survival model with cure rate in the presence of covariates. In this perspective, the modelling is a direct extension of the long-term model of (Chen et al., 1999). This ...

In this work, we introduce a Bayesian Analysis for survival multivariate data in the presence of a covariate vector and censored observations. Different frailties or latent variables are considered to capture the correlation ...

In survival data analysis it is common the occurrence of a large number of individuals to the right. This fact can indicate that, in a fraction of the individuals the event of interest will never happen, in other words, a ...

In this work we consider the long-term survival model introduced by Berkson & Gage (1952), for modeling survival data of nonhomogeneous populations, where a subpopulation does not present the event of interest, despite a ...