Bayesian complementary clustering, MCMC and Anglo-Saxon placenames

TL;DR

This paper develops a Bayesian model for analyzing Anglo-Saxon settlement data, focusing on clusters formed by different types of placenames, and demonstrates its effectiveness through advanced MCMC techniques and real historical data.

Contribution

It introduces a novel Bayesian complementary clustering model for multi-type point processes and improves MCMC sampling methods for complex hypergraph matchings.

Findings

Supports hypothesis of settlement organization by complementary names

Estimates number of clusters and intra-cluster dispersion

Provides insights into historical settlement patterns

Abstract

Common cluster models for multi-type point processes model the aggregation of points of the same type. In complete contrast, in the study of Anglo-Saxon settlements it is hypothesized that administrative clusters involving complementary names tend to appear. We investigate the evidence for such an hypothesis by developing a Bayesian Random Partition Model based on clusters formed by points of different types (complementary clustering). As a result we obtain an intractable posterior distribution on the space of matchings contained in a k-partite hypergraph. We apply the Metropolis-Hastings (MH) algorithm to sample from this posterior. We consider the problem of choosing an efficient MH proposal distribution and we obtain consistent mixing improvements compared to the choices found in the literature. Simulated Tempering techniques can be used to overcome multimodality and a multiple proposal scheme is developed to allow for parallel programming. Finally, we discuss results arising from the careful use of convergence diagnostic techniques. This allows us to study a dataset including locations and placenames of 1316 Anglo-Saxon settlements dated approximately around 750-850 AD. Without strong prior knowledge, the model allows for explicit estimation of the number of clusters, the average intra-cluster dispersion and the level of interaction among placenames. The results support the hypothesis of organization of settlements into administrative clusters based on complementary names.