Transformation of bimodal probability distributions into possibility distributions

At the application level, it is important to be able to define around the measurement result an interval which will contain an important part of the distribution of the measured values, that is, a coverage interval. This practice acknowledged by the ISO Guide is a major shift from the probabilistic representation. It can be viewed as a probability-possibility transformation by viewing possibility distribution as encoding coverage intervals. In this paper, we extend previous works on unimodal distributions by proposing a possibility representation of bimodal probability distributions. Indeed, U-shaped distributions or Gaussian mixture distribution are not so rare in a context of physical measurements.