provide a framework within which pre-existing knowledge about the parameters of
a model (the prior distribution) can be combined with observed data and the model
output. The results in a probability distribution on the parameter space (called the
posterior distribution), that summarizes uncertainty about the parameters
(Marshall et al., 2004)