2026-04-30T00:21:04Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/643442025-09-19T07:30:01Zcom_10324_1191com_10324_931com_10324_894col_10324_1379
UVaDOC
author
Wollstadt, Patricia
author
Lizier, Joseph
author
Vicente, Raul
author
Finn, Conor
author
MartÃnez Zarzuela, Mario
author
Mediano, Pedro
author
Novelli, Leonardo
author
Wibral, Michael
2024-01-10T11:25:06Z
2024-01-10T11:25:06Z
2019
Wollstadt et al., (2019). IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks. Journal of Open Source Software, 4(34), 1081, https://doi.org/10.21105/joss.01081
2475-9066
https://uvadoc.uva.es/handle/10324/64344
10.21105/joss.01081
1081
34
Journal of Open Source Software
4
2475-9066
We present IDTxl (the Information Dynamics Toolkit xl), a new open source Python toolbox for effective network inference from multivariate time series using information theory, available from GitHub (https://github.com/pwollstadt/IDTxl).
Information theory (Cover & Thomas, 2006; MacKay, 2003; Shannon, 1948) is the math- ematical theory of information and its transmission over communication channels. In- formation theory provides quantitative measures of the information content of a single random variable (entropy) and of the information shared between two variables (mutual information). The defined measures build on probability theory and solely depend on the probability distributions of the variables involved. As a consequence, the dependence between two variables can be quantified as the information shared between them, without the need to explicitly model a specific type of dependence. Hence, mutual information is a model-free measure of dependence, which makes it a popular choice for the analysis of systems other than communication channels.
eng
Atribución 4.0 Internacional
IDTxl: The Information Dynamics Toolkit xl: a Python package for the efficient analysis of multivariate information dynamics in networks
info:eu-repo/semantics/article
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https://uvadoc.uva.es/bitstream/10324/64344/1/10.21105.joss.01081.pdf
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10.21105.joss.01081.pdf