A statistical model for the joint inference of vertical stability and horizontal diffusibility of typological features

Abstract

A major pursuit within the study of language evolution is to advance understanding of the historical behavior of typological features. Previous studies have identified at least three factors that determine the typological similarity of a pair of languages: (1) vertical stability, (2) horizontal diffusibility, and (3) uni-versality. Of these factors, the first two are of particular interest. Although observed data are affected by all three factors to a greater or lesser degree, previous studies have not jointly modeled them in a straightforward manner. Here, we propose a solution that is derived from the field of cultural anthropology. We present a simple and extensible Bayesian autologistic model to jointly infer the three factors from observed data. Although a large number of missing values in the dataset pose serious difficulties for statistical modeling, the proposed model can robustly estimate these parameters as well as missing values. Applying missing value imputation to indirectly evaluate the estimated parameters, we quantitatively demonstrated that they were meaningful. In conclusion, we briefly compare our findings with those of previous studies and discuss future directions.