Time Series Prediction
The course is not on the list Without time-table
| Code | Completion | Credits | Range |
|---|---|---|---|
| 14YPCR | KZ | 3 | 2+1 |
- Garant předmětu:
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- Department of Applied Informatics in Transportation
- Synopsis:
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Quantitative and qualitative forecasting, causal models, time-series methods, least squares\r\nestimates. Useful descriptive statistics, accuracy of forecasting methods, MAE, MAPE, RMSE, entropy measures, naive predictions (persistency). Linear forecasting models, covariance and correlation coefficients, smoothing methods, regression methods, Box-Jenkins time series methods, AR, MA, ARMA,ARIMA models. Input variable selections, statistical tests.
- Requirements:
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- Note:
- Further information:
- No time-table has been prepared for this course
- The course is a part of the following study plans: