These tools demonstrate recently developed data-driven nonlinear stochastic-dynamic methods for analysis, modeling and prediction of data from partially-observed systems.
1. Examples of Empirical Model Reduction [Kondrashov et al, 2005, Kravtsov et al. 2009] within a general class of nonlinear Multilayer Stochastic Models (MSM) with memory effects and complex noise structure [Kondrashov et al. 2015, Ghil et al. 2018].
2. “Past-noise forecasting” example [Chekroun et al. 2011].