Time series are found widely in engineering and science. We study multiagent forecasting in time series, drawing from literature on time series, graphical models, and multiagent s...
This review focuses on dynamic causal analysis of functional magnetic resonance (fMRI) data to infer brain connectivity from a time series analysis and dynamical systems perspecti...
Alard Roebroeck, Anil K. Seth, Pedro A. Valdes-Sos...
— A new standpoint on financial time series, without the use of any mathematical model and of probabilistic tools, yields not only a rigorous approach of trends and volatility, ...
This paper presents a fuzzy system approach to the prediction of nonlinear time series and dynamical systems based on a fuzzy model that includes its derivative information. The u...
In time series analysis, inference about causeeffect relationships among multiple times series is commonly based on the concept of Granger causality, which exploits temporal struc...