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Holiday
GEN III綜三 837 M2M3M4
This course introduces statistical modeling and inferences for analyzing time series data. The topics include ARIMA modeling and best linear forecasting; state-space model and Kalman filter; volatility model; model selection and diagnostics; multivariate time series, and frequency domain analysis. The course will focus on both theory and applications. Students need to code for their homework and projects extensively using R or other toolboxes. Students taking this course must be familiar with regression and have at least one year of learning experience in statistics and related courses in advance.
MON | TUE | WED | THU | FRI | |
| 08:00108:50 | |||||
| 09:00209:50 | |||||
| 10:10311:00 | |||||
| 11:10412:00 | |||||
| 12:10n13:00 | |||||
| 13:20514:10 | |||||
| 14:20615:10 | |||||
| 15:30716:20 | |||||
| 16:30817:20 | |||||
| 17:30918:20 | |||||
| 18:30a19:20 | |||||
| 19:30b20:20 | |||||
| 20:30c21:20 |
Average GPA 3.35
Std. Deviation 1.06
本課程為 16 週課程
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