Usually, the exact time at which an event occurs cannot be observed for several reasons; for instance, it is not possible to constantly monitor a characteristic of interest.This generates a phenomenon known as censoring that can be classified as having a left censor, right censor or interval censor.When one is working with Bowl / Banger Stand survival data in the presence of arbitrary censoring, the survival time of interest is defined as the elapsed time between an initial event and the next event that is generally unknown.This problem has been widely studied in the statistic literature and some progress has been made, toward resolving and the formulation of a bivariate likelihood to estimate parameters in a parametric regression model offers positive development opportunities.In this paper, we construct a 85 BURGUNDY BLISS bivariate likelihood for the Weibull regression model in the presence of interval censoring.
Finally, its performance is illustrated by means of a simulation study.