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Choosing the optimal model parameters for Granger causality in application to time series with main timescale

机译:选择Granger因果关系的最佳模型参数以应用于主要时间尺度的时间序列

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摘要

The problem of determining the presence and direction of coupling between experimentally observed time series is of immediate interest in many relevant areas of knowledge. One of the approaches to its solution is the method of nonlinear Granger causality. The algorithm is based on the construction of predictive models and its effectiveness depends on the proper selection of model parameters.
机译:在许多相关的知识领域,确定实验观察到的时间序列之间的耦合的存在和方向的问题是紧迫的问题。解决该问题的方法之一是非线性格兰杰因果关系方法。该算法基于预测模型的构建,其有效性取决于模型参数的正确选择。

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