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

Abstract

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.

Sampled to Death? The Rise and Fall of Probability Sampling in Archaeology

“…One other does, but without naming it (Drennan 2010:88–92). In archaeological research literature, I was only able to find a single example (Collins-Elliott 2017). Clearly, those who have eschewed probability sampling have not been aware of this concept.…”