Causal Discovery of Stochastic Dynamical Systems: A Markov Chain Approach
Marcell Stippinger,
Attila Bencze,
Ádám Zlatniczki,
Zoltán Somogyvári,
András Telcs
Affiliations
Marcell Stippinger
Wigner Research Centre for Physics, H-1121 Budapest, Hungary
Attila Bencze
Wigner Research Centre for Physics, H-1121 Budapest, Hungary
Ádám Zlatniczki
Department of Computer Science and Information Theory, Faculty of Electrical Engineering and Informatics, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
Zoltán Somogyvári
Wigner Research Centre for Physics, H-1121 Budapest, Hungary
András Telcs
Wigner Research Centre for Physics, H-1121 Budapest, Hungary
Our proposed method for exploring the causal discovery of stochastic dynamic systems is designed to overcome the limitations of existing methods in detecting hidden and common drivers. The method is based on a simple principle and is presented in a nonparametric structural vector autoregressive modeling framework.
