Bayesian rule in the framework of uncertainty theory

Abstract In Bayesian rule an unknown parameter is thought to be a quantity whose variation can characterized by prior distribution. Then some data are observed from population distribution function indexed the and then updated according data. The named as posterior Based on uncertainty theory, this paper first makes connection between likelihood function, proposes new method obtain with given Some examples special distributions employed explain calculation. Furthermore, uncertain urn problem provided illustrate application of method.