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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
CSDA
2006
117views more  CSDA 2006»
13 years 5 months ago
Exact maximum likelihood estimation of structured or unit root multivariate time series models
TheexactlikelihoodfunctionofaGaussianvectorautoregressive-movingaverage(VARMA)model is evaluated in two nonstandard cases: (a) a parsimonious structured form, such as obtained in ...
Guy Mélard, Roch Roy, Abdessamad Saidi
ECML
1997
Springer
13 years 9 months ago
Parallel and Distributed Search for Structure in Multivariate Time Series
Abstract. E cient data mining algorithms are crucial fore ective knowledge discovery. We present the Multi-Stream Dependency Detection (msdd) data mining algorithm that performs a ...
Tim Oates, Matthew D. Schmill, Paul R. Cohen
SIGPRO
2011
229views Hardware» more  SIGPRO 2011»
12 years 12 months ago
Fast and exact synthesis of stationary multivariate Gaussian time series using circulant embedding
A fast and exact procedure for the numerical synthesis of stationary multivariate Gaussian time series with a priori prescribed and well controlled autoand cross-covariance functi...
Hannes Helgason, Vladas Pipiras, Patrice Abry
CSDA
2010
173views more  CSDA 2010»
13 years 5 months ago
Time-varying joint distribution through copulas
This paper deals with the analysis of temporal dependence in multivariate highfrequency time series data. The dependence structure between the marginal series is modelled through ...
M. Concepcion Ausin, Hedibert F. Lopes