In the first part of this work, a Survival function is considered which is supposed to be an Exponential Gamma Process. The main statistical and probability properties of this process and its Bayesian interpretation are considered. In the second part, the problem to estimate, from a Bayesian view point, the Survival function is considered, looking for the Bayes rule inside of the set of linear combinations of a given set of sample functions. We finish with an estimation, in the same situation like before, of the survival mean time, and the i-th moment about the origin of the Survival functio
This work concerns some problems in the area of survival analysis that arise in real clinical or epi...
International audienceBayesian nonparametric marginal methods are very popular since they lead to fa...
AbstractWe propose a random censorship model which permits uncertainty in the cause of death assessm...
In the first part of this work, a Survival function is considered which is supposed to be an Exponen...
In this paper, the Bayesian analysis of the survival data arising from a Rayleigh model is carried o...
The study and research of survival or reliability or life time belong to the same area of study but ...
In survival analysis interest lies in modeling data that describe the time to a particular event. In...
We introduce a semi-parametric Bayesian model for survival analysis. The model is centred on a param...
In the past decade applications of the statistical methods for survival data analysis have been exte...
summary:In this work, a parametric sequential estimation method of survival functions is proposed in...
Survival analysis is one of the main areas of focus in medical research in recent years. Survival an...
The paper proposes a new nonparametric prior for two–dimensional vectors of survival functions (S1, ...
In this note we propose an estimator of the survival function at a given time point using a Bayesian...
In this article we consider the problem of estimating the survival and mean residual life functions ...
The central statistical problem of survival analysis is to determine and characterize the conditiona...
This work concerns some problems in the area of survival analysis that arise in real clinical or epi...
International audienceBayesian nonparametric marginal methods are very popular since they lead to fa...
AbstractWe propose a random censorship model which permits uncertainty in the cause of death assessm...
In the first part of this work, a Survival function is considered which is supposed to be an Exponen...
In this paper, the Bayesian analysis of the survival data arising from a Rayleigh model is carried o...
The study and research of survival or reliability or life time belong to the same area of study but ...
In survival analysis interest lies in modeling data that describe the time to a particular event. In...
We introduce a semi-parametric Bayesian model for survival analysis. The model is centred on a param...
In the past decade applications of the statistical methods for survival data analysis have been exte...
summary:In this work, a parametric sequential estimation method of survival functions is proposed in...
Survival analysis is one of the main areas of focus in medical research in recent years. Survival an...
The paper proposes a new nonparametric prior for two–dimensional vectors of survival functions (S1, ...
In this note we propose an estimator of the survival function at a given time point using a Bayesian...
In this article we consider the problem of estimating the survival and mean residual life functions ...
The central statistical problem of survival analysis is to determine and characterize the conditiona...
This work concerns some problems in the area of survival analysis that arise in real clinical or epi...
International audienceBayesian nonparametric marginal methods are very popular since they lead to fa...
AbstractWe propose a random censorship model which permits uncertainty in the cause of death assessm...