Dictionary-Based Pattern Entropy for Causal Direction Discovery

Harikrishnan, Nellippallil Balakrishnan and Bhilare, Shubham and Kathpalia, Aditi and Nagaraj, Nithin (2026) Dictionary-Based Pattern Entropy for Causal Direction Discovery. arXiv..

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Abstract: Discovering causal direction from temporal observational data is particularly challenging for symbolic sequences, where functional models and noise assumptions are often unavailable. We propose a novel \emph{Dictionary Based Pattern Entropy ()} framework that infers both the direction of causation and the specific subpatterns driving changes in the effect variable. The framework integrates \emph{Algorithmic Information Theory} (AIT) and \emph{Shannon Information Theory}. Causation is interpreted as the emergence of compact, rule based patterns in the candidate cause that systematically constrain the effect. constructs direction-specific dictionaries and quantifies their influence using entropy-based measures, enabling a principled link between deterministic pattern structure and stochastic variability. Causal direction is inferred via a minimum-uncertainty criterion, selecting the direction exhibiting stronger and more consistent pattern-driven organization. As summarized in Table 7, consistently achieves reliable performance across diverse synthetic systems, including delayed bit-flip perturbations, AR(1) coupling, 1D skew-tent maps, and sparse processes, outperforming or matching competing AIT-based methods (, , ). In biological and ecological datasets, performance is competitive, while alternative methods show advantages in specific genomic settings. Overall, the results demonstrate that minimizing pattern level uncertainty yields a robust, interpretable, and broadly applicable framework for causal discovery.
Item Type: Journal Paper
Subjects: School of Natural and Engineering Sciences > Complex Systems
Divisions: Schools > Humanities
Date Deposited: 13 Apr 2026 06:30
Last Modified: 13 Apr 2026 06:30
Official URL: https://arxiv.org/abs/2603.04473
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    DOI: https://doi.org/10.48550/arXiv.2603.04473
    URI: http://eprints.nias.res.in/id/eprint/3303

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