Abstract
Diversities are an extension of the concept of a metric space, where a non-negative value is assigned to any finite set of points, rather than just pairs. Sometimes, diversity theory closely parallels metric theory; other times it veers off in new directions. Here we explore diversities on Euclidean space, particularly those which are Minkowski linear or sublinear. Many well-known functions in convex analysis turn out to be Minkowski linear or Minkowski sublinear diversities, including diameter, circumradius and mean width. We derive characterizations of these classes. Motivated by classical results in metric geometry, and connections with combinatorial optimization, we examine embeddability of finite diversities. We prove that a finite diversity can be embedded into a linear diversity exactly when it has negative type and that it can be embedded into a sublinear diversity exactly when it corresponds to a generalized circumradius.