Liangyue Cao,Alistair Mees,Kevin Judd.Dynamics from multivariate time series. Physica D Nonlinear Phenomena . 1998CAO, L., MEES, A., JUDD, K. `Dynamics from multivariate time series,' Physica D., vol 121, 1998. pp. 75-88.Cao L., Mees A. & Judd K. 1998, Dynamics from multivariate...
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 ...
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 ...
Using multivariate regressions (Table 5), the inclusion of AT to PRCP or A to AT explains marginally better the variability in greenness for various grassland communities in semi-arid Kenya. These findings support previous research on the role of precipitation, temperature, and grazing in the ...
Forecasting tourism using univariate and multivariate structural time series models Tourism Economics, 7 (2001), pp. 135-147 CrossrefView in ScopusGoogle Scholar Twining-Ward, L., 2002 Twining-Ward, L. (2002) Monitoring sustainable tourism development: a comprehensive, stakeholder-driven, adaptive ap...
2.2Multivariate singular spectrum analysis (MSSA) To identify complex patterns of spatio-temporal behavior in the CESM simulation summarized above, we rely here on MSSA, which provides an efficient and robust tool to extract dynamics from short, noisy time series. MSSA relies on the classical Karhun...
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For example, as a disease progresses, the brain dynamics may be gradually altered to transit from one phase to another, or to approach or repel from a phase transition curve. In fact, the method is applicable to general multivariate time series. Deployment of the present method to other ...
Higher-order organization of multivariate time series Article 02 January 2023 Exploiting deterministic features in apparently stochastic data Article Open access 18 November 2022 A flexible Bayesian framework for unbiased estimation of timescales Article Open access 24 March 2022 Introduction...