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JMLR
2011
187views more  JMLR 2011»
13 years 1 months ago
Robust Statistics for Describing Causality in Multivariate Time Series
A widely agreed upon definition of time series causality inference, established in the seminal 1969 article of Clive Granger (1969), is based on the relative ability of the histor...
Florin Popescu
JMLR
2010
194views more  JMLR 2010»
13 years 1 months ago
Graphical Gaussian modelling of multivariate time series with latent variables
In time series analysis, inference about causeeffect relationships among multiple times series is commonly based on the concept of Granger causality, which exploits temporal struc...
Michael Eichler
BMCBI
2007
215views more  BMCBI 2007»
13 years 6 months ago
Learning causal networks from systems biology time course data: an effective model selection procedure for the vector autoregres
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
Rainer Opgen-Rhein, Korbinian Strimmer
ARTMED
2002
92views more  ARTMED 2002»
13 years 6 months ago
Predicting glaucomatous visual field deterioration through short multivariate time series modelling
In bio-medical domains there are many applications involving the modelling of multivariate time series (MTS) data. One area that has been largely overlooked so far is the particul...
Stephen Swift, Xiaohui Liu
NC
2006
132views Neural Networks» more  NC 2006»
13 years 6 months ago
Learning short multivariate time series models through evolutionary and sparse matrix computation
Multivariate Time Series (MTS) data are widely available in different fields including medicine, finance, bioinformatics, science and engineering. Modelling MTS data accurately is...
Stephen Swift, Joost N. Kok, Xiaohui Liu