Time Series Analysis

Definition of Time Series. Components of Time Series. Methods of Time Series Analysis. Forecasting. Stationarity-Autocovarianve-Autocorellation-Partial Autocorellation. White Noise-Random Walk. Autoregressive Models AR(1), AR(2), AR(p). Moving Average Models ΜΑ(1), ΜΑ(2), ΜΑ(q). Mixed autoregressive/Moving Average Models ARMA(p,q). ARIMA(p,d,q). SARIMA (P,D,Q), x(p,d,q). Identification of ARIMA Models. Estimation of ARIMA Models, Diagnostic Test. Criterion of Model Selection. Forecasting with AR(1), MA(1), ARMA(1,1), ARMA(p,q), ARIMA(p,d,q). Confidence Interval of Forecasting.-Measures of Evaluation.
Box-Jenkins Methodology with SPSS.

Division: Statistics, Probability and Operational Research

Recommended Literature:

Program of Studies:
Semester: B
ECTS: 7.5
Hours per week (Lec/Tut/L): 3/0/0
Code: MCDA113
Erasmus students: No