A Treatise on Measuring Wiener-Granger Causality
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Wiener-Granger causality is a well-established concept of causality based on stochasticity and the flow of time, with applications in a broad array of quantitative sciences. The majority of methods used to measure Wiener-Granger causality are based on linear premises and hence insensitive to non-linear signals. Other frameworks based on non-parametric techniques are often computationally expensive and susceptible to overfitting or lack of sensitivity.
In this thesis, Paper I investigates the application of linear Wiener-Granger causality to migrating cancer cell data obtained using a Systems Microscopy experimental platform. Paper II represents a review of non-parametric measures based on information theory and discusses a number of related bottlenecks and potential routes of circumvention. Paper III studies the properties of a frequently used non-parametric information theoretical measure for a class of non-Gaussian distributions. Paper IV introduces a new efficient scheme for non-parametric analysis of Wiener-Granger causality based on kernel canonical correlations, and studies the connection between this new scheme and the information theoretical approach. Lastly, Paper V draws upon the results in the preceding paper to discuss non-parametric analysis of Wiener-Granger causality in partially observed systems.
Altogether, the work presented in this thesis constitutes a comprehensive review on measures of Wiener-Granger causality in general, and in particular, features new insights on efficient non-parametric analysis of Wiener-Granger causality in high-dimensional settings.
Place, publisher, year, edition, pages
Stockholm: Department of Mathematics, Stockholm University , 2014. , 44 p.
Wiener-Granger causality, Information theory, Kernel canonical correlation, Systems Microscopy, Cell migration.
Probability Theory and Statistics Cell Biology
Research subject Mathematical Statistics
IdentifiersURN: urn:nbn:se:su:diva-101595ISBN: 978-91-7447-861-7OAI: oai:DiVA.org:su-101595DiVA: diva2:704532
2014-04-16, sal 14 hus 5, Kräftriket, Roslagsvägen 101, Stockholm, 10:00 (English)
Stramaglia, Sebastiano, Professor
Tyrcha, Joanna, Professor
FunderEU, FP7, Seventh Framework ProgrammeSwedish Research Council
At the time of the doctoral defence, the following papers were unpublished and had a status as follows: Paper 3: Accepted Paper 4: Manuscript; Paper 5: Accepted2014-03-252014-03-122014-03-13Bibliographically approved
List of papers