A generalized residual technique for analyzing complex movement models using earth mover's distance

1. Complex systems of moving and interacting objects are ubiquitous in the natural and social sciences. Predicting their behavior often requires models that mimic these systems with sufficient accuracy, while accounting for their inherent stochasticity. Though tools exist to determine which of a set of candidate models is best relative to the others, there is currently no generic goodness-of-fit framework for testing how close the best model is to the real complex stochastic system. 2. We propose such a framework, using a novel application of the Earth mover's distance, also known as the Wasserstein metric. It is applicable to any stochastic process where the probability of the model's state at time t is a function of the state at previous times. It generalizes the concept of a residual, often used to analyze 1D summary statistics, to situations where the complexity of the underlying model's probability distribution makes standard residual analysis too imprecise for practical use. 3. We...