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304193 (v.3) Time Series Modelling 504
Area: Department of Mathematics and Statistics Contact Hours: 3.0 Credits: 25.0 Lecture: 1 x 3 Hours Weekly Anti Requisite(s): 302387 (v.2) Time Series Modelling 404 or any previous version
Prerequisite(s): 302315 (v.2) Mathematical Statistics 202 or any previous version
Stationary stochastic processes. Autocorrelation. Auto regressive integrated moving average (ARIMA) models. Spectral analysis. Fast Fourier transform estimation in time domain. Linear filters. Time series models in frequency domain. Multivariate time series. Optimal filters - Kolmogorov, Weiner, Kalman. Concepts of stochastic control. Practical application of foregoing to modelling.
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