LINEAR AND NONLINEAR TIME SERIES ANALYSIS
Linear time series analysis - modelling time series using stochastic processes, stationarity, autocovariance, auto correlation, multivariate analysis - AR, MA, ARMA, AIC criterion for order selection; spectral analysis - deterministic processes, concentration problem, stochastic spectral analysis, nonparametric spectral estimation (periodogram, tapering, windowing), multitaper spectral estimation; parametric spectral estimation (Yule-Walker equations, Levinson Durbin)(recursions); multivariate analysis - coherence, causality relations; bootstrap techniques for estimation of parameters; nonlinear time series analysis - Lyapunov Xexponents, correlation dimension, embedding methods, surrogate data analysis.
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