Stochastic Methods for Modeling and Predicting Complex Dynamical Systems: Uncertainty Quantification, State Estimation, and Reduced-Order Models (Hardcover, 2023)

Introduction to Complex Systems, Stochastic Methods, and Model Error.- Basic Stochastic Toolkits.- Introduction to Information Theory.- Numerical Schemes for Solving Stochastic Differential Equations.- Gaussian and Non-Gaussian Processes.- Data Assimilation.- Simple Data-driven Stochastic Models.- Conditional Gaussian Nonlinear Systems.- Parameter Estimation with Uncertainty Quantification.- Ensemble Forecast.- Combining Stochastic Models with Machine Learning.