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» Causal Search in Structural Vector Autoregressive Models
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CSDA
2007
124views more  CSDA 2007»
13 years 5 months ago
Wavelet based time-varying vector autoregressive modelling
Vector autoregressive (VAR) modelling is one of the most popular approaches in multivariate time series analysis. The parameters interpretation is simple, and provide an intuitive...
João Ricardo Sato, Pedro Alberto Morettin, ...
ICASSP
2011
IEEE
12 years 9 months ago
Learning and inference algorithms for partially observed structured switching vector autoregressive models
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Balakrishnan Varadarajan, Sanjeev Khudanpur
JGS
2010
106views more  JGS 2010»
13 years 1 days ago
On vector autoregressive modeling in space and time
Despite the fact that it provides a potentially useful analytical tool, allowing for the joint modeling of dynamic interdependencies within a group of connected areas, until latel...
Valter Di Giacinto
ISBI
2008
IEEE
14 years 6 months ago
Inferring brain dynamics using granger causality on fMRI data
Here we present a scalable method to compute the structure of causal links over large scale dynamical systems that achieves high efficiency in discovering actual functional connec...
Guillermo A. Cecchi, Rahul Garg, A. Ravishankar Ra...
KDD
2009
ACM
364views Data Mining» more  KDD 2009»
14 years 5 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi