Bayesian inference with Monte Carlo approximation: Measuring regional differentiation in ceramic and glass vessel assemblages in Republican Italy, ca. 200 BCE - 20 CE

Methods of measuring differentiation in archaeological assemblages have long been based on attribute-level analyses of assemblages. This paper considers a method of comparing assemblages as probability distributions via the Hellinger distance, as calculated through a Dirichlet-categorical model of inference using Monte Carlo methods of approximation. This method has application within practice-theory traditions of archaeology, an approach which seeks to measure and associate different factors that comprise the habitus of society. It is implemented here focusing on the question of regional food consumption habits in Republican Italy in the last two centuries BCE, toward informing a perspective on mass social change.