時間序列(Time Series Master Level 1)
Master of Statistics
Course of Announcement
Text Books: Introduction to Time Series and Forecasting by
P.J. Brockwell and R.A. Davis., Springer
ISBN 0-387-94719-1 (滄海代理 04-2588787)
Reference:
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Time Series Analysis: Univariate and Multivariate Methods
by W. W. S. Wei, Addison Wesley 1990. ISBN
0-201-15911-2.
Applied Econometric Time Series, Second Edition, Walter
Enders, Wiley
Papers: Announce in appropriate time (will focus on estimation and
model selections)
Software: for the course:
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A CD containing the time series package ITSM2000, is contained
in the text. Installation instructions for ITSM2000, which requires a
PC running Windows 95/98/00, Windows NT or a more recent
version of Windows, are given at the back of the text. The
professional version, which can be used to analyze data sets
longer than 250.
R/S: might important for Master Student research.
Instructor: Tsair-chuan Lin 林財川
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Office:商 0714
office hours:Tu, Th am10~12
Tel: 02-86746775; 03-3277568
E-mail: tsair@mail.ntpu.edu.tw
web.ntpu.edu.tw/~tsair
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Course Main Contents: (80% theory; 20% application):
 Examples,
objectives, general approaches, stationary
models. [1.1,1.2, 1.3, 1.4]
 Removing trend and/or seasonality, testing an estimated
noise sequence. [1.5, 1.6]
 Stationary random processes: basic properties, linear
processes, introduction to ARMA processes,
properties of the sample mean and autocorrelation
function. [2.1, 2.2, 2.3, 2.4]
 Forecasting stationary time series, the Wold
decomposition. [2.5, 2.6]
 ARMA models: ARMA(p,q) processes, the ACF and
PACF, forecasting ARMA processes [3.1-3.3]
 Introduction to spectral theory and linear filtering.
Spectral densities of ARMA processes. [4.1-4.4]
 Modelling and forecasting with ARMA processes.
[5.1-5.5]
 Non-stationary and seasonal time series models:
ARIMA models, identification, unit roots, seasonal
models, regression with time series errors. [6.1-6.6]
Required: Regresssion
Other References:
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Time Series: Theory and Methods, 2nd Edition, Brockwell and
Davis
The Analysis of Time Series, An Introduction, Chatfield
Introduction to Statistical Time Series, Fuller
Time Series Analysis: Forecasting and Control, Box, Jenkins and
Reinsel
Time Series Analysis and its Applications, Shumway and Stoffer
Grading: Homework30%; Exams 35%; Final Exam 35%
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週數 日期
內容
講義自行列印
1
09/20 課程介紹
2
09/27 Ch1. Introduction
3
10/04 Ch1. Introduction
ch1.pdf
4
10/11 Ch2. Stationary Process
ch2.pdf
5
10/18 Ch2. Stationary Process
6
10/25 Ch2. Stationary Process
7
11/01 Ch3. ARMA Model
8
11/08 Ch3. ARMA Model
9
11/15 暫定期中考 2(Ch3-6)
10
11/22 Ch4. Spectral Analysis
11
11/29 Ch4. Spectral Analysis
12
12/06 Ch5. Modeling and Forecasting
13
12/13 Ch5. Modeling and Forecasting
14
12/20 Ch6. Non-stationary Time Series
15
12/27 Ch6. Non-stationary Time Series
16
01/03 Ch7. Multivariate Time Series
17
01/10 Ch7. Multivariate Time Series
18
01/17 暫定 Final Test
習 題
課程大綱
Splus for time series
ch3.pdf
當然要考啦!!
import data
ch5.pdf
unit root test
ch6.pdf
ITSM.rar
PEST Package
Introduction
範例: 書面(.doc) 簡報(.ppt)
【最新公告】
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12/09, 期末計畫使用資料何處尋?
3
o
(92 年使
用) http://www-personal.buseco.monash.edu.au/~hyndman/TSDL/ 選擇
Finance 或 Macro-Econ 大項
o
(91 年使用) http://www.economagic.com/
o
Splus: ARIMA modeling
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10/12, 期末計畫如何書寫? 範例: 書面(.doc)
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1012, 如何 oral? 範例: 簡報(.ppt)
Some Other Resources
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Introduction to Time Series Analysis and Forecasting With Applications
of SAS and Spss
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Seasonal Model for the Airline Series
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Subset, Seasonal, and Factored ARMA Models
Fine
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