一、課程說明(Course Description)
This course attempts to give a systematic account of several important time
series models and their applications to the modelling and prediction of data
obtained sequentially in time. Topics to be covered include: time series
regression and exploratory data analysis, a brief review of linear
(regression)models, autoregressive moving average models, estimation and
prediction in the time domain, nonstationary time series analysis, ARCH models,
GARCH models, and regression models with time series error.

二、指定用書(Text Books)

1. William WS Wei (2006). Time Series Analysis : Univariate and Multivariate
Methods (2nd Edition), Addison Wesley.
2. P. J. Brockwell and R. A. Davis (1987). Time Series: Theory and Methods,
Springer-Verlag.
3. R. H. Shumway and D. S. Stoffer (2006). Time Series Analysis and Its
Applications, Springer.


三、參考書籍(References)

4. W. A. Fuller (1996). Introduction to statistical Time Series, Wiley.
5. J. D. Hamilton (1994). Time Series Analysis, Princeton.
6. C.-K. Ing's lecture notes in statistical inference.
http://mx.nthu.edu.tw/~cking/


四、教學方式(Teaching Method)(必填)

口述


五、教學進度(Syllabus)(必填)

1. Time Series Regression and Exploratory Data Analysis
2. Review of linear (regression) models
3. Stationary Time Series, Regression Analysis, Autocorrelation Function (ACF)
and Partial Autocorrelation Function (PACF)
4. Autoregressive Models: Modelling and Point Estimation
5. Autoregressive Models: Interval Estimation
6. Prediction and Model Selection
7. An Introduction to Nonlinear Least Squares Estimates
8. ARMA Model: Modelling, Estimation and Prediction
9. Nonstationary Time Series
10. ARCH and GARCH models
11. Regression model with time series error
12. Multivariate Time Series
13. An Introduction to High-Dimensional Time Series


六、成績考核(Evaluation)(必填)

Midterm Examination 20%
Midterm Project Report 40%
Final Project Report 40%


七、可連結之網頁位址(必填)
無