Author

Shigeki Kishi

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Open access Oct 2026

Forest-weighted causal correlation: A scalable framework for causal inference in ecological time series

Detecting causal relationships from ecological time series remains challenging because community dynamics are often nonlinear, high-dimensional, noisy, and strongly synchronized. These characteristics can reduce the reliability of existing causal inference methods and complicate the identification of ecological interac...

Shigeki Kishi · bioRxiv · 0 citations

Open access Oct 2026

Forward time-series causal inference based on forest weights and conditional dependence

Unveiling directional causality in complex, high-dimensional dynamical systems remains a fundamental challenge. Conventional nonparametric approaches, such as Convergent Cross Mapping, require computationally intensive surrogate tests and frequently yield false-positive detections under strong coupling due to generaliz...

Shigeki Kishi · bioRxiv · 0 citations

Open access Sep 2026

Forest-weighted non-linear causal inference for high-dimensional and multimodal time series

Forecasting and causal inference in complex, non-linear dynamical systems are fundamentally challenging due to noisy and high-dimensional time-series data. While Empirical Dynamic Modeling addresses this via state-space reconstruction in Euclidean space, it suffers from the “curse of dimensionality,” distorting distanc...

Shigeki Kishi · bioRxiv · 0 citations