Abstract
In this paper, we propose a model for analysing the bivariate left-censored data incorporating the dependence enjoyed between the components. This is achieved through the dynamic bivariate vector reversed hazard rate by Gürler (J Am Stat Assoc 91:1152–1165, 1996). The properties of the proposed model is studied. The maximum likelihood method of estimation and the Bayesian method of estimation of parameters is presented. The complexity of the likelihood function is handled through the Metropolis - Hastings algorithm. Interval estimation techniques of the parameters are also considered. Applications of this model is demonstrated by illustrating the usefulness of the model in analysing Australian twin dataset (Duffy in Am J Human Genet 47:530, 1990).
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