Add to ORKGThe purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real ...
The goals of assessing the influence of individual observations in statistical analysis are not only...
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as d...
In this study, firstly, consideration is given to the traditional maximum likelihood estimator and...
The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regr...
We propose Bayesian case influence diagnostics for complex survival models. We develop case deletion...
The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders...
In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regr...
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as d...
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as d...
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as d...
In statistical modelling, it is often important to know how much parameter estimates are influenced ...
We utilize the Bayesian approach to estimate the parameters of the Birnbaum-Saunders (BS) distributi...
We utilize the Bayesian approach to estimate the parameters of the Birnbaum-Saunders (BS) distributi...
The goals of assessing the influence of individual observations in statistical analysis are not only...
We develop a Bayesian analysis based on two different Jeffreys priors for the Student-t regression m...
The goals of assessing the influence of individual observations in statistical analysis are not only...
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as d...
In this study, firstly, consideration is given to the traditional maximum likelihood estimator and...
The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regr...
We propose Bayesian case influence diagnostics for complex survival models. We develop case deletion...
The beta-Birnbaum-Saunders (Cordeiro and Lemonte, 2011) and Birnbaum-Saunders (Birnbaum and Saunders...
In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regr...
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as d...
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as d...
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as d...
In statistical modelling, it is often important to know how much parameter estimates are influenced ...
We utilize the Bayesian approach to estimate the parameters of the Birnbaum-Saunders (BS) distributi...
We utilize the Bayesian approach to estimate the parameters of the Birnbaum-Saunders (BS) distributi...
The goals of assessing the influence of individual observations in statistical analysis are not only...
We develop a Bayesian analysis based on two different Jeffreys priors for the Student-t regression m...
The goals of assessing the influence of individual observations in statistical analysis are not only...
Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as d...
In this study, firstly, consideration is given to the traditional maximum likelihood estimator and...