Testing for spatial association of qualitative data using symbolic dynamics

Qualitative spatial variables are important in many fields of research. However, unlike the decades-worth of research devoted to the spatial association of quantitative variables, the exploratory analysis of spatial qualitative variables is relatively less developed. The objective of the present paper is to propose a new test (Q) for spatial independence. This is a simple, consistent, and powerful statistic for qualitative spatial independence that we develop using concepts from symbolic dynamics and symbolic entropy. The Q test can be used to detect, given a spatial distribution of events, patterns of spatial association of qualitative variables in a wide variety of settings. In order to enable hypothesis testing, we give a standard asymptotic distribution of an affine transformation of the symbolic entropy under the null hypothesis of independence in the spatial qualitative process. We include numerical experiments to demonstrate the finite sample behaviour of the test, and show its application by means of an empirical example that explores the spatial association of fast food establishments in the Greater Toronto Area in Canada.