Time series analysis

Official Course Description

Description

Stationary and nonstationary processes, ARIMA processes, seasonal variation, prediction, filtering and reconstruction in transfer function models and state space models, parameter and structure estimation by least squares, maximum likelihood and predictive error methods, spectral analysis, recursive estimation, adaptive techniques, robustness and outlier detection, multivariate time series, spectral density estimation

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