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JMLR
2010
194views more  JMLR 2010»
13 years 6 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
ICML
2007
IEEE
14 years 12 months ago
Modeling changing dependency structure in multivariate time series
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...
Xiang Xuan, Kevin P. Murphy
JMLR
2010
173views more  JMLR 2010»
13 years 6 months ago
Elliptical slice sampling
Many probabilistic models introduce strong dependencies between variables using a latent multivariate Gaussian distribution or a Gaussian process. We present a new Markov chain Mo...
Iain Murray, Ryan Prescott Adams, David J. C. MacK...
ICASSP
2011
IEEE
13 years 2 months ago
Sparse graphical modeling of piecewise-stationary time series
Graphical models are useful for capturing interdependencies of statistical variables in various fields. Estimating parameters describing sparse graphical models of stationary mul...
Daniele Angelosante, Georgios B. Giannakis
JMLR
2010
158views more  JMLR 2010»
13 years 6 months ago
Topology Selection in Graphical Models of Autoregressive Processes
An algorithm is presented for topology selection in graphical models of autoregressive Gaussian time series. The graph topology of the model represents the sparsity pattern of the...
Jitkomut Songsiri, Lieven Vandenberghe