Kernel-based prediction of non-Markovian time series
Authors:
- Faheem GilaniFGFaheem Gilani
- Dimitrios GiannakisDGDimitrios Giannakis
- John HarlimJHJohn Harlim
- 1 April 2021
- journal article
- research article
- Published by Elsevier in Physica D: Nonlinear Phenomena
- Vol. 418
Abstract
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Funding Information
- National Science Foundation (DMS-1854299)
- National Science Foundation (DMS-1854383)
- National Science Foundation (1842538)
- Office of Naval Research (N00014-16-1-2649)
This publication has 35 references indexed in Scilit:
- A mechanism for catastrophic filter divergence in data assimilation for sparse observation networksNonlinear Processes in Geophysics, 2013
- Mori–Zwanzig formalism as a practical computational toolFaraday Discussions, 2009
- Computing generalized Langevin equations and generalized Fokker–Planck equationsProceedings of the National Academy of Sciences, 2009
- Diffusion mapsApplied and Computational Harmonic Analysis, 2006
- Optimal prediction with memoryPhysica D: Nonlinear Phenomena, 2002
- Application of support vector machines in financial time series forecastingOmega, 2001
- Sequential data assimilation with a nonlinear quasi‐geostrophic model using Monte Carlo methods to forecast error statisticsJournal of Geophysical Research: Oceans, 1994
- EmbedologyJournal of Statistical Physics, 1991
- Analysis methods for numerical weather predictionQuarterly Journal of the Royal Meteorological Society, 1986
- Convergence of Distributions Generated by Stationary Stochastic ProcessesTheory of Probability & Its Applications, 1968