A BIVARIATE GENERALIZED EXPONENTIAL DISTRIBUTION DERIVED FROM COPULA FUNCTIONS IN THE PRESENCE OF CENSORED DATA AND COVARIATES
AUTOR(ES)
Achcar, Jorge Alberto, Moala, Fernando Antônio, Tarumoto, Mario Hissamitsu, Coladello, Leandro Fernandes
FONTE
Pesqui. Oper.
DATA DE PUBLICAÇÃO
2015-04
RESUMO
In this paper, we introduce a Bayesian analysis for a bivariate generalized exponential distribution in the presence of censored data and covariates derived from Copula functions. The generalized exponential distribution could be a good alternative to analyze lifetime data in comparison to usual existing parametric lifetime distributions as Weibull or Gamma distributions. We have being using standard existing MCMC (Markov Chain Monte Carlo) methods to simulate samples for the joint posterior of interest. Two examples are introduced to illustrate the proposed methodology: an example with simulated bivariate lifetime data and an example with a real lifetime data set.
Documentos Relacionados
- Bivariate Copula-based Linear Mixed-effects Models: An Application to Longitudinal Child Growth Data
- The log-exponentiated generalized gamma regression model with censored data
- On estimation and influence diagnostics for a bivariate promotion lifetime model based on the FGM copula: a fully bayesian computation
- Mapping Soil Cation Exchange Capacity in a Semiarid Region through Predictive Models and Covariates from Remote Sensing Data
- A new spreadsheet method for the analysis of bivariate flow cytometric data