On Non-Informative Robust Fuzzy Bayesian Estimators

Abstract

In this paper, Suggesting a general method for converting any continuous failure distribution into a fuzzy failure distribution to obtain a more accurate and flexible distribution of inaccurate observations. and suggesting a robust Bayesian method that depends on a non-informational primary distribution that depends on Jeffrey’s rule in finding the primary distributions so that the probability of obtaining the observation is conditional on its previous distribution, as the outliers observation will have a probability that differs from the probability of the another of the observations, and applying this method exponential distribution