The idea of hierarchical Bayesian modeling (Gelman et al 2013) relates naturally to the Bayesian comparison of Carnapian prediction rules (e.g., Skyrms 1993 and 1996, Festa 1996), and also to the estimation of optimum inductive methods (Kuipers 1986, Festa 1993). Hierarchical Bayesian modeling can also be related to another tool for choosing a particular prior distribution over hypotheses, namely the method of empirical Bayes, which estimates the prior that leads to the maximal marginal likelihood of the model. In the philosophy of science, hierarchical Bayesian modeling has made a first appearance due to Henderson et al (2010).