Estimating hidden relationships in dynamical systems: Discovering drivers of infection rates of COVID-19
Description
Discovering causal influences among internal variables is a fundamental goal of complex systems research. This paper presents a framework for uncovering hidden relationships from limited time-series data by combining methods from nonlinear estimation
