Liangyue Cao , Alistair Mees , Kevin Judd, Dynamics from multivariate time series, Physica D, v.121 n.1-2, p.75-88, Oct. 1, 1998Cao, L.Y., Mees, A., Judd, K.: Dynamics from multivariate time series. Physica D 121, 75–88 (1998) MATH...
Joint modeling of local and global temporal dynamics for multivariate time series forecasting with missing values Proceedings of the AAAI Conference on Artificial Intelligence, 2020. 论文链接: Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values...
Note that a multivariate time series e(t) is ‘white’ if it has no statistical dependence across time (that is, e(s) and e(t) are independent if s ≠ t) even though it can have arbitrary statistical dependence across channels (that is, ei(t) and ej(t) can be dependent at ...
Land transitions from multivariate time series: using seasonal trend analysis and segmentation to detect land-cover changes The detection of land-cover change over large areas using short time series is a challenging and important task in global change studies. This paper introd... B Parmentier,JR...
The dynamics of the equal-time cross-correlation matrix of multivariate financial time series is explored by examination of the eigenvalue spectrum over sliding time windows. Empirical results for the S&P 500 and the Dow Jones Euro Stoxx 50 indices reveal that the dynamics of the small eigenvalues...
In reality, the GNN computes its outcome from the complete multivariate state of the neighbors of a node. The interacting contagion and the metapopulation dynamics, unlike the simple and complex contagions, are examples of such multivariate cases. Their outcome is thus harder to visualize in a ...
Because the observed differences are subtle and yet systematic, correlations between planform expression and vegetation density might emerge more clearly from multivariate analyses of meander morphometries. Following a tested approach in river morphodynamics33,34,35,39, we applied Principal Component Analy...
Nonlinearities are detected not only in a univariate setting but also in some preliminary investigations dealing with a multivariate case. Certain differences seem to exist between nominal and real variables in nonlinear behaviour. Some differences are also detected in terms of short and long-term ...
Observability of multivariate differential embeddings. J. Phys. A: Mathematical and General 38, 6311–6326 (2005). Article MathSciNet MATH Google Scholar Aguirre, L. A., Portes, L. L. & Letellier, C. Structural, dynamical and symbolic observability: From dynamical systems to networks. Plos...
Time series were subsequently transformed into the phase-space and individual autoregressive (AR) models were applied to predict glucose values over 30-minute and 60-minute prediction horizons (PH). The logistic smooth transition AR (LSTAR) model provided the best prediction accuracy for patients ...