A new model was developed to analyze data on how things move between different places. This model considers the influence of nearby locations on the movement of things without assuming a specific type of data distribution. By using a special method to estimate the model's parameters, researchers can account for differences in how spread out the data is. The results show that the model can accurately capture the effects of both direct and indirect influences between locations. Tests using simulated data suggest that the model works well with different types of data and becomes more accurate with larger datasets. The model was applied to study how patents are shared among regions in Europe.