Time Series Analysis 7.5 credits
About the course
The main purpose of the course is that the student should be well aquainted with the basic notions, theory, models and methods for solutions, in time series analysis. The course covers models for time dependent data. Such data frequently occurs in financial (e.g. the price development of a merchandise) and scientific (e.g. metheorological observations, radar signales) applications.
The course consists of two parts.
Module 1 (4.5 hp) Theory.
The module consists of general theory of time series, stationary and non-stationary models, such as ARMA, ARIMA, SARIMA, and GARCH models including exogeneous variables, multivariate models, state-space models, parameter estimation and prediction.
Module 2 (3 hp) Lab Assignments. The module consists of analysis of time series using suitable software.
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