Decomposing causality into its synergistic, unique, and redundant components.

ABSTRACT: Causality lies at the heart of scientific inquiry, serving as the fundamental basis for understanding interactions among variables in physical systems. Despite its central role, current methods for causal inference face significant challenges due to nonlinear dependencies, stochastic interactions, self-causation, collider effects, and influences from exogenous factors, among others. While existing methods can effectively address some of these challenges, no single approach has successfully integrated all these aspects. Here, we address these challenges with SURD: Synergistic-Unique-Redundant Decomposition of causality. SURD quantifies causality as the increments of redundant, unique, and synergistic information gained about future events from past observations. The formulation is non-intru

SUBMITTER: Martinez-Sanchez A 

PROVIDER: S-EPMC11530654 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature