Preface "Extreme Events: Nonlinear Dynamics and Time Series Analysis"

Methods of nonstationary nonlinear time series forecasting under bounded a priori information provide an interdisciplinary applications area that is concerned with learning

Our aim is to extend standard principal component analysis for non-time series data to explore and highlight the main structure of multiple sets of multivariate time series.. To

Time-Domain Simulation of Sampled Weakly Nonlinear Systems Using Analytical Integration and Orthogonal Polynomial Series.. Ewout Martens ∗ and

(2019) SARI: interactive GNSS position time series analysis software.. Synthetic series with an annual cycle of varying amplitude superimposed on a sinusoid-like varying trend

For this reasons, matrix factorization was used in multivariate time series analysis beyond econometrics: electricity

A novel probabilistic risk analysis to determine the vulnerability of ecosystems to extreme climatic events.. Marcel van Oijen, Christian Beer, Wolfgang Cramer, Anja Rammig,

In this work, several models based on NNs for the analysis of TO time series have been presented for different appli- cations concerning missing data treatment and time

Using all the data (through December 2000), this prediction shows no strong ENSO events (positive or negative) during the time period January 2001 through December 2004..