課程資訊
課程名稱
時間序列分析
Time Series Analysis 
開課學期
101-2 
授課對象
社會科學院  經濟學研究所  
授課教師
銀慶剛 
課號
ECON5007 
課程識別碼
323 U0600 
班次
 
學分
全/半年
半年 
必/選修
選修 
上課時間
星期二5,6,7(12:20~15:10) 
上課地點
社科2 
備註
限學士班三年級以上 或 限碩士班以上
總人數上限:50人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1012tsa 
課程簡介影片
 
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課程概述

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, autoregressive moving average models, estimation and prediction in the time domain, spectral analysis, nonstationary time series analysis, and regression models with time series error.  

課程目標
The aim of this course is to provide specific techniques for handling data and at the same time to provide a thorough understanding of the theoretical basis for the techniques. Since this is a master's-/undergraduate-level course, we will make our mathematical treatments as comprehensive/simple as possible.  
課程要求
 
預期每週課後學習時數
 
Office Hours
 
參考書目
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.
4. W. A. Fuller (1996). Introduction to statistical Time Series, Wiley.
5. J. D. Hamilton (1994). Time Series Analysis, Princeton.
6. N. H. Chan (2010). Time Series, Wiley. 
指定閱讀
 
評量方式
(僅供參考)
 
No.
項目
百分比
說明
1. 
Midterm Examination 
35% 
This is an in-class open-book test. There is "No" make-up examination!! 
2. 
Final Examination 
35% 
This is a take-home test.  
3. 
Homework Assignments 
30% 
There are about 6 homework assignments. Each assignment contains 5-8 questions. 
 
課程進度
週次
日期
單元主題
第1週
2/19  Introduction 
第2週
2/26  Time Series Regression and Exploratory Data Analysis 
第3週
3/05  Stationary Time Series, ACF and PACF 
第4週
3/12  Sample ACF and PACF  
第5週
3/19  Autoregressive Models: Modelling and Estimation 
第6週
3/26  Moving Average Model : Modelling and Estimation  
第7週
4/02  ARMA Model: Modelling, Estimation and Prediction 
第8週
4/09  Model Selection  
第9週
4/16  Midterm Examination 
第10週
4/23  Introduction to Spectral Analysis 
第11週
4/30  Nonstationary Time Series I 
第12週
5/07  Nonstationary Time Series II 
第13週
5/14  Nonstationary Time Series III  
第14週
5/21  Regression Models with Time Series Error I  
第15週
5/28  Regression Models with Time Series Error II  
第16週
6/04  Regression Models with Time Series Error III 
第17週
6/11  Final Examination