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Convergent Cross Mapping

Convergent Cross Mapping (CCM) is a nonlinear, state-space method for detecting causality between time-series variables embedded in a shared dynamical system. Introduced by George Sugihara and colleagues in their landmark 2012 Science paper, CCM exploits Takens' embedding theorem: if variable X causally influences Y, the historical record of Y contains enough information to recover the states of X. Causality is confirmed when cross-map skill improves—converges—as the time-series library grows longer.

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Convergent Cross Mapping (CCM)

Rekod kaedah taksonomik · ml-model / causal-inference

Sugihara, G., et al. (2012). Detecting causality in complex ecosystems. Science, 338(6106), 496–500. · DOI 10.1126/science.1227079

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