Characterising directed and undirected metrics of high-order interdependence
<|reference_start|>Characterising directed and undirected metrics of high-order interdependence: Systems of interest for theoretical or experimental work often exhibit high-order interactions, corresponding to statistical interdependencies in groups of variables that cannot be reduced to dependencies in subsets of them. While still under active development, the framework of partial information decomposition (PID) has emerged as the dominant approach to conceptualise and calculate high-order interdependencies. PID approaches can be grouped in two types: directed approaches that divide variables into sources and targets, and undirected approaches that treat all variables equally. Directed and undirected approaches are usually employed to investigate different scenarios, and hence little is known about how these two types of approaches may relate to each other, or if their corresponding quantities are linked in some way. In this paper we investigate the relationship between the redundancy-synergy index (RSI) and the O-information, which are practical metrics of directed and undirected high-order interdependencies, respectively. Our results reveal tight links between these two quantities, and provide interpretations of them in terms of likelihood ratios in a hypothesis testing setting, as well as in terms of projections in information geometry.<|reference_end|>
@article{rosas2024characterising,
    title={Characterising directed and undirected metrics of high-order
  interdependence},
    author={Fernando E. Rosas, Pedro A.M. Mediano, Michael Gastpar},
    journal={arXiv preprint arXiv:2404.07140},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.07140},
    primaryClass={cs.IT math.IT}
}