Statistical Inference for Interval-Valued Spatial Error Models

In recent years, there is a growing need to analyze interval-valued data, and many scholars are also paying attention to the research on interval-valued data modeling and analysis. In this paper, we shall introduce a new model aimed at handling interval-valued data with spatial dependencies. Based on the idea of least square method of single-valued case, we give the parameter estimator for interval-valued spatial error model. Then we prove the estimator’s properties. Finally, we give the numerical simulation analysis. Also the proposed model was applied to three real datasets, and the empirical analysis demonstrates the effectiveness of the proposed model.