ABSTRACT
In this chapter, the authors describe methods for assessing the hyperparameters for prior distributions used to quantify available prior knowledge regarding parameter values. They quantify available prior knowledge regarding values of parameters of the model which is specified with a likelihood. The authors also quantify how likely the values of the parameters in the likelihood are, prior to seeing any current data. This can be accomplished by using data from a previous similar experiment or by using subjective expert opinion in the form of a virtual set of data. There are two ways the hyperparameters can be assessed, either in a pure subjective way which expresses expert knowledge and beliefs or by use of data from a previous similar experiment.
