Time Series Analysis




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Course Contents

Linear stationary processes, AR, MA, ARMA and ARIMA; identification, estimation of the models; forecasting time series regression; Fourier analysis, spectral representation of a stochastic process, properties of ARMA processes in the frequency domain; estimation of the spectrum, Kalman filter. 



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