Nonlinear cointegration and time series analysis represent a dynamic area of research that extends the classical framework of cointegration by allowing the long-run equilibrium relationships among ...

Various time-series decomposition techniques, including wavelet transform, singular spectrum analysis, empirical mode decomposition and independent component analysis, have been developed for ...

1. Difference Equations -- 2. Lag Operators -- 3. Stationary ARMA Processes -- 4. Forecasting -- 5. Maximum Likelihood Estimation -- 6. Spectral Analysis -- 7 ...

This course explores dynamical systems and the various ways to use a computer to investigate their behavior. It covers the standard computational and analytical tools used in nonlinear dynamics, ...

Time series analysis involves identifying attributes of your time series data, such as trend and seasonality, by measuring statistical properties. From stock market analysis to economic forecasting, ...