課程大綱 Syllabus |
分配時數 (小時) |
備註 Notes |
單元主題 Unit topic |
內容綱要 Content summary |
講授 |
示範 |
習作 |
其他 |
INTRODUCTION |
INTRODUCTION |
2 |
0 |
1 |
0 |
|
Classical Methods |
1.Weighted Average Method
2.Exponential Smoothing Method
3.Decomposition Model |
2 |
0 |
1 |
0 |
|
Stationary Processes |
1.Weak Stationary
2.Strong Stationary |
2 |
0 |
1 |
0 |
|
Stationary Time Series |
Stationary Time Series |
4 |
0 |
2 |
0 |
|
ARMA Models |
1.ARMA(p,q) process
2.The ACF and PACF of an ARMA(p,q) process
3.Forecasting ARMA(p,q) process |
4 |
0 |
2 |
0 |
|
Modeling and Forecasting with ARIMA(p,q) process |
1.Yule-Walker Estimation
2.Diagnostic Checking
3.Forecasting
4.Order Selection |
2 |
0 |
1 |
0 |
|
Midterm |
ch1~ch5 |
3 |
0 |
0 |
0 |
|
Case Study:Applications of ARMA Models |
Case Study:Applications of ARIMA Models |
1 |
0 |
2 |
0 |
|
Nonstationary Time Series |
1. Introduction to Nonstationary Time Series
2.ARIMA Models
3.Identification Techniques |
4 |
0 |
2 |
0 |
|
Seasonal Time Series |
1.Seasonal Time Series
2.Seasonal ARIMA Models |
2 |
0 |
1 |
0 |
|
Case Study: Seasonal Time Series |
Case Study: Seasonal Time Series |
1 |
0 |
2 |
0 |
|
Transfer Function Models |
Transfer Function Models |
2 |
0 |
1 |
0 |
|
Case Study: Transfer Function Models |
Case Study: Transfer Function Models |
1 |
0 |
2 |
0 |
|
Nonlinear Models |
Nonlinear Models |
2 |
0 |
1 |
0 |
|
Final |
Real Data Analysis |
3 |
0 |
0 |
0 |
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