Time Series Causality Inference Using the Phase Slope Index

author: Florin Popescu, Fraunhofer FIT
published: Jan. 19, 2010,   recorded: December 2009,   views: 5903
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Delicious Bibliography

Description

A method recently introduced by Nolte et. al (Phys Rev Lett 100:23401, 2008) estimates the causal direction of interactions robustly with respect to instantaneous mixtures of independent sources with arbitrary spectral content, i.e. in observations which are dominated by non-white spatially correlated noise and in which dynamic structural interaction plays little part. The method, named Phase Slope Index (PSI), is unlikely to assign causality in the case of lack of dynamic interaction among time series, unlike Granger causality for linear systems. Results show that PSI does not yield false positives even in the case of nonlinear interactions. The meaning of instaneous noise mixtures in different data domains will be discussed in the context of correct correlation vs. causation inference, and the theoretical relationship of PSI to other time-series causality inference methods will be expanded upon.

See Also:

Download slides icon Download slides: nips09_popescu_tsciupsi_01.pdf (1.1 MB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: