Causal inference of gene expression data using a clustering-based extension of kernel-granger causality
FN Haredasht, F Ghassemi… - 2016 23rd Iranian …, 2016 - ieeexplore.ieee.org
Detecting causal relationships between time series data has been widely studied in many
areas, including biology, neuroscience, economics, and climatology. One of the most
popular causality inference methods is Granger causality approach that is a linear
regression based model for determining whether one time series is useful in forecasting
another; however, this approach cannot detect nonlinear relations in the data. Different
extensions of Granger causality have been proposed for nonlinear dynamics of the time …
areas, including biology, neuroscience, economics, and climatology. One of the most
popular causality inference methods is Granger causality approach that is a linear
regression based model for determining whether one time series is useful in forecasting
another; however, this approach cannot detect nonlinear relations in the data. Different
extensions of Granger causality have been proposed for nonlinear dynamics of the time …
[引用][C] Causal inference of gene expression data using a clustering-based extension of Kernel-Granger causality
F Nateghi Haredasht, F Ghassemi, MH Moradi - https://ieeexplore. ieee. org …, 2016 - IEEE
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