In this article, a competing risk model is analyzed in the presence of complete and censored data when the causes of failures follow different family of failure time distributions. We derive the maximum likelihood and Bayes estimators of the parameters involved in the model and the relative risks. The goodness-of-fit of the competing risks model with the considered failure time distributions to a real data set is also demonstrated
Bayesian analysis of system failure data from engineering applications under a competing risks frame...
Abstract. We discuss the maximum likelihood estimator (MLE) for competing risk prob-lems under vario...
In reliability theory, the most important problem is to determine the reliability of a complex syste...
In several studies in Survival Analysis, the cause of failure / death of items or individuals may be...
Competing risks are frequently overlooked, and the event of interest is analyzed with conventional s...
In the competing risks model, a unit is exposed to several risks at the same time, but it is assumed...
In medical studies or in reliability analysis an investigator is often interested in the assessment ...
We present a Bayesian approach for analysis of competing risks survival data with masked causes of f...
We consider a nonparametric and a semiparametric (in presence of covariates) additive hazards rate c...
Abstract: In reliability or life-testing experiments, the cause of failure of an individual or item ...
We consider a nonparametric and a semiparametric (in presence of covariates) additive hazards rate c...
The theory of competing risks has been developed to asses a specific risk in presence of other risk ...
Competing risk or "multiple cause" survival data arise in medical, criminological, financial, engine...
In survival analysis or medical studies each person can be exposed to more than one type of outcomes...
Competing risks data usually arises in studies in which the failure of an individual may be classifi...
Bayesian analysis of system failure data from engineering applications under a competing risks frame...
Abstract. We discuss the maximum likelihood estimator (MLE) for competing risk prob-lems under vario...
In reliability theory, the most important problem is to determine the reliability of a complex syste...
In several studies in Survival Analysis, the cause of failure / death of items or individuals may be...
Competing risks are frequently overlooked, and the event of interest is analyzed with conventional s...
In the competing risks model, a unit is exposed to several risks at the same time, but it is assumed...
In medical studies or in reliability analysis an investigator is often interested in the assessment ...
We present a Bayesian approach for analysis of competing risks survival data with masked causes of f...
We consider a nonparametric and a semiparametric (in presence of covariates) additive hazards rate c...
Abstract: In reliability or life-testing experiments, the cause of failure of an individual or item ...
We consider a nonparametric and a semiparametric (in presence of covariates) additive hazards rate c...
The theory of competing risks has been developed to asses a specific risk in presence of other risk ...
Competing risk or "multiple cause" survival data arise in medical, criminological, financial, engine...
In survival analysis or medical studies each person can be exposed to more than one type of outcomes...
Competing risks data usually arises in studies in which the failure of an individual may be classifi...
Bayesian analysis of system failure data from engineering applications under a competing risks frame...
Abstract. We discuss the maximum likelihood estimator (MLE) for competing risk prob-lems under vario...
In reliability theory, the most important problem is to determine the reliability of a complex syste...