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This project implements the MCDTS algorithm outlined in the paper Nonlinear Dynamics volume 108, pages 1525–1545 (2022).

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JuliaDynamics/TreeEmbedding.jl

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TreeEmbedding.jl - a Monte Carlo Decision Tree Search (MCDTS) for optimal embedding

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TreeEmbedding.jl implements the MCDTS algorithm outlined in Kraemer, K.H., Gelbrecht, M. et al. 2022 and is one of the packages composing DynamicalSystems.jl. It aims to provide an optimal time delay state space reconstruction from time series data with the help of decisions trees and suitable statistics that guide the decisions done during the rollout of these trees. For all details of the algorithm the reader is referred to the accompanying paper. Here we provide an implementation of all the variants described in the paper.

For more details please see our detailed documentation pages.

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This project implements the MCDTS algorithm outlined in the paper Nonlinear Dynamics volume 108, pages 1525–1545 (2022).

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