Strategic Point Processes

Spatial point processes provide a way for researchers to describe event-based outcomes in a bounded study window. Commonly used processes, such as the Neyman-Scott processes, however, often lack the behavioral frameworks that social scientists need to analyze strategic interactions between cohorts of actors. Strategic point processes address this issue by framing spatial point processes as a fixed set of players who engage in a countably infinite number of sequential games in a bounded study window. In this setup, each player receives a random function as their spatial strategy and their observed joint strategies generate the point pattern formations researchers record from the real world. To introduce the logic of strategic point processes, this paper describes the basic assumptions of Neyman-Scott (NS) spatial games, which model the clustering tendencies of strategic actors. Next, this paper discusses how researchers can reconstruct NS spatial games using observational datasets. Finally, this paper discusses how researchers can use complete spatial randomness (CSR) as an analytic baseline to draw inferences from NS spatial games.