Against the Flow of Time with Multi-Output Models
References
- Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: journal of the Econometric Society 424–438. https://doi.org/10.2307/1912791.
- Paluš, M., Krakovská, A., Jakubík, J., Chvosteková, M. (2018). Causality, dynamical systems and the arrow of time. Chaos: An Interdisciplinary Journal of Nonlinear Science 28(7), 075307. https://doi.org/10.1063/1.5019944.
- Haufe, S., Nikulin, V. V., Müller, K.-R., Nolte, G. (2013). A critical assessment of connectivity measures for eeg data: a simulation study. Neuroimage 64, 120–133. https://doi.org/10.1016/j.neuroimage.2012.09.036.
- Winkler, I., Panknin, D., Bartz, D., Müller, K.-R., Haufe, S. (2016). Validity of time reversal for testing granger causality. IEEE Transactions on Signal Processing 64(11), 2746–2760. https://doi.org/10.1109/TSP.2016.2531628.
- Riek, R. (2020). Entropy derived from causality. Entropy 22(6), 647. https://doi.org/10.3390/e22060647.
- Chvosteková, M., Jakubík, J., Krakovská, A. (2021). Granger causality on forward and reversed time series. Entropy 23(4), 409. https://doi.org/10.3390/e23040409.
- Kořenek, J., Hlinka, J. (2021). Causality in reversed time series: Reversed or conserved? Entropy 23(8), 1067. https://doi.org/10.3390/e23081067.
- Marinazzo, D., Pellicoro, M., Stramaglia, S. (2008). Kernel method for nonlinear granger causality. Physical review letters 100(14), 144103. https://doi.org/10.1103/PhysRevLett.100.144103.
- Krakovská, A., Hanzely, F. (2016). Testing for causality in reconstructed state spaces by an optimized mixed prediction method. Physical Review E 94(5), 052203. https://doi.org/10.1103/PhysRevE.94.052203.
- Chicharro, D., Andrzejak, R. G. (2009). Reliable detection of directional couplings using rank statistics. Physical Review E 80(2), 026217. https://doi.org/10.1103/PhysRevE.80.026217.
- Sugihara, G., May, R., Ye, H., Hsieh, C.-h., Deyle, E., Fogarty, M., Munch, S. (2012). Detecting causality in complex ecosystems. science 338(6106), 496–500. https://doi.org/10.1126/science.1227079 .
- Krakovská, A., Jakubík, J. (2020). Implementation of two causal methods based on predictions in reconstructed state spaces. Physical Review E 102(2), 022203. https://doi.org/10.1103/PhysRevE.102.022203.
- Walker, J. (2019). Tutorial: Time series analysis with pandas. https://www.dataquest.io/blog/tutorial-time-series-analysis-with-pandas/.
- Thorndike, R. L. (1953). Who belongs in the family. In Psychometrika. https://doi.org/10.1007/BF02289263.
- Takens, F. (1981). Detecting strange attractors in turbulence. In Dynamical systems and turbulence, Warwick 1980. Springer, 366–381.
DOI: https://doi.org/10.2478/msr-2023-0023 | Journal eISSN: 1335-8871
Language: English
Page range: 175 - 183
Submitted on: Jan 16, 2023
Accepted on: Jul 26, 2023
Published on: Sep 21, 2023
Published by: Slovak Academy of Sciences
In partnership with: Paradigm Publishing Services
Publication frequency: 6 times per year
Related subjects:
© 2023 Jozef Jakubík, Mary Phuong, Martina Chvosteková, Anna Krakovská, published by Slovak Academy of Sciences
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.