Estimation on dependent right censoring scheme in an ordinary bivariate geometric distribution
Research output: Contribution to journal › Article › Academic › peer-review
Discrete lifetime data are very common in engineering and medical researches. In many cases the lifetime is censored at a random or predetermined time and we do not know the complete survival time. There are many situations that the lifetime variable could be dependent on the time of censoring. In this paper we propose the dependent right censoring scheme in discrete setup when the lifetime and censoring variables have a bivariate geometric distribution. We obtain the maximum likelihood estimators of the unknown parameters with their risks in closed forms. The Bayes estimators as well as the constrained Bayes estimates of the unknown parameters under the squared error loss function are also obtained. We considered an extension to the case where covariates are present along with the data. Finally we provided a simulation study and an illustrative example with a real data.
- BAYESIAN-INFERENCE, Bayes estimation, COMPETING-RISKS, CONSTRAINED BAYES, COVARIATE-INFORMATION, EXPONENTIAL-DISTRIBUTION, MODEL, PROSTATE-CANCER, bivariate geometric distribution, dependent right censoring, discrete lifetime