Mixed predictability and cross-validation to assess non-linear Granger causality in short cardiovascular variability series
Mixed predictability and cross-validation to assess non-linear Granger causality in short cardiovascular variability series
复制标题
混合可预测性和交叉验证评估短心血管变异系列中的非线性格兰杰因果关系
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
G. Nollo
中科院分区：
文献类型：
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作者：
L. Faes;R. Cucino;G. Nollo
摘要提出了一种评价心血管和心肺两个变量序列因果交互作用方向和强度的方法。该方法基于使用最近邻局部线性近似来量化两个序列的自身和混合可预测性。它返回两个因果耦合指数，衡量正向和反向的可预测性的相对改善，以及一个方向性指数，指示交互的优先方向。该方法是通过交叉验证方法实现的，该方法允许在不限制序列嵌入的情况下量化方向性，并充分利用可用数据来最大化预测精度。对短的模拟双变量时间序列的验证表明，该方法能够捕捉到不同程度的单向和双向相互作用。此外，对心率、动脉收缩压和呼吸序列的典型例子的应用允许推断与已知生理机制和实验条件有关的因果关系。
Abstract A method to evaluate the direction and strength of causal interactions in bivariate cardiovascular and cardiorespiratory series is presented. The method is based on quantifying self and mixed predictability of the two series using nearest-neighbour local linear approximation. It returns two causal coupling indexes measuring the relative improvement in predictability along direct and reverse directions, and a directionality index indicating the preferential direction of interaction. The method was implemented through a cross-validation approach that allowed quantification of directionality without constraining the embedding of the series, and fully exploited the available data to maximise the prediction accuracy. Validation on short simulated bivariate time series demonstrated the ability of the method to capture different degrees of unidirectional and bidirectional interaction. Moreover, application to representative examples of heart rate, systolic arterial pressure and respiration series allowed the inference of causal relationships related to known physiological mechanisms and experimental conditions.
影响因子：
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作者：
HIRSCH, JA;BISHOP, B
通讯作者：
BISHOP, B