Maximum Likelihood Estimation for System Identification of Networks of Dynamical Systems

Anders Hansson; João Victor Galvão da Mata; Martin S. Andersen

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arXiv · 2506.20628

Maximum Likelihood Estimation for System Identification of Networks of Dynamical Systems

Anders Hansson·João Victor Galvão da Mata·Martin S. Andersen

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Abstract

This paper investigates maximum likelihood estimation for direct system identification in networks of dynamical systems. We establish that the proposed approach is both consistent and efficient. In addition, it is more generally applicable than existing methods, since it can be employed even when measurements are unavailable for all network nodes, provided that network identifiability is satisfied. Finally, we demonstrate that the maximum likelihood problem can be formulated without relying on a predictor, which is key to achieving computationally efficient numerical solutions.

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Anders Hansson, João Victor Galvão da Mata, Martin S. Andersen. 2025-06-25. Maximum Likelihood Estimation for System Identification of Networks of Dynamical Systems. https://arxiv.org/abs/2506.20628

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