Abstract-- the paper presents a possibility formulation of oneparameter estimation that unifies some usual probability formulations. Point and confidence interval estimation are un...
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
This article demonstrates the potential of using hierarchical Bayesian methods to relate models and data in the cognitive sciences. This is done using a worked example that consid...
Abstract. There exist several simple representations of uncertainty that are easier to handle than more general ones. Among them are random sets, possibility distributions, probabi...
There exist many tools for capturing imprecision in probabilistic representations. Among them are random sets, possibility distributions, probability intervals, and the more recen...