TMA4285 Time Series Models

(Fall 2006)

Textbook:   Peter J. Brockwell, Richard A. Davis. Introduction to Time Series and Forecasting, 2002, Springer Verlag.

Pensum:
Chapter 1
Chapter 2 (except 2.5.1, 2.6)
Chapter 3
Chapter 4
Chapter 5 (except 5.1.2, 5.1.3)
Chapter 6 (except 6.3, 6.6)

Exam (solutions)

Exam 2005

Schedule:
 Lectures: Monday 12:15-14:00, room F1 Thursday (group 1) 14:15-16:00, room EL2 Friday (group 2) 14:15-16:00, room S1 Exercises: Thursday (group 1) 16:15-17:00, room EL2 Friday (group 2) 16:15-17:00, room S1

Messages:

13.10.06: Results of the midterm exam and solutions are below.

2.10.06: Midterm exam is 9.10.06 (Monday), 12:15-14:00, room F1. Pensum: Chapter 1 (whole), Chapter 2 (without 2.5.1, 2.5.2, 2.6), Chapter 3 (3.1, 3.2). Tillatte hjelpemidler: alle trykte og håndskrevne hjelpemidler tillatt. Alle kalkulatorer tillatt. (By the way, calculator is necessary).

24.08.06: I have received the following information: "Mandager 14-15 kan du ikke legge undervisning. Da er det tillitsrepresentant time og skal være undervisningsfri for alle studenter." Therefore I transfer øvinger from Monday 14:15-15:00 to Thursday 16:15-17:00. Please let me know if this is not convenient.

23.08.06: I have received a message from one participant of our course. He asks for a change of the schedule, namely, to transfer our Friday lecture to Thursday (the same time 14:15 - 16:00). Is this OK for others? Please let me know (as soon as possible) if Thursday, 14:15 - 16:00, is not convenient. If I receive no messages I transfer the Friday lecture to Thursday. In this case the first lecture will be Monday 28 August.

17.08.06: Something is wrong with the schedule (collision with other courses) so we have to change the schedule. We meet August 22, 10:15 but in room F6 and define the new schedule. I would appreciate if each of you, who intends to take TMA4285, send me e-mail and indicate days/time which are not convenient.

15.08.06: First meeting is August 22, 10:15, room F3.

Midterm exam (solutions)

Midterm exam (results)

Plan:
 Lecture 1.(28.08.06) Introduction. Repetition from Probability theory. Appendix A Homework: - Lecture 2.(31.08.06/1.09.06) Repetition (continued). Time series models. Appendix A, Chapter 1 (1.1, 1.2, 1.3, 1.4). Homework: A3, 1.1, 1.3, 1.4, 1.5, 1.6 Lecture 3.(4.09.06) AR(1) process. Sample ACVF and ACF. Estimation of trend and seasonal components. Chapter 1 (1.4, 1.5). Homework: 1.7, 1.8, 1.11 Lecture 4.(7.09.06/8.09.06) Estimation of trend and seasonal components. Testing the noise. Chapter 1 (1.5, 1.6), Appendix B. Homework: 1.10, 1.13, 1.16 Lecture 5.(11.09.06) Basic properties of stationary processes. Linear process. Chapter 2 (2.1, 2.2), Appendix C. Homework: 2.1, 2.2, 2.3 Lecture 6.(14.09.06/15.09.06) Linear process (continued). Chapter 2 (2.2, 2.3). Homework: 2.4, 2.5 Lecture 7.(18.09.06) ARMA(1,1). Stationary processes (estimation, prediction). Chapter 2 (2.3, 2.4, 2.5). Homework: 2.8, 2.9a, 2.10 Lecture 8.(21.09.06/22.09.06) Stationary processes (prediction). Chapter 2 (2.5). Homework: 2.11, 2.12, 2.14 Lecture 9.(25.09.06) Prediction operator. ARMA models. Chapter 2 (2.5), Chapter 3 (3.1, 3.2). Homework: 2.13, 2.15 Lecture 10.(28.09.06/29.09.06) ARMA(p,q). ACF and PACF. Chapter 3 (3.1, 3.2). Homework: - Lecture 11.(2.10.06) ARMA models (ACF, PACF, Prediction). Chapter 3 (3.2, 3.3). Homework: 3.1, 3.2, 3.3 (something) Lecture 12.(5.10.06/6.10.06) ARMA models. Estimation in ARMA models. Chapter 3 (3.3), Chapter 5 (5.1). Homework: 3.4, 3.6 Midterm exam.(9.10.06) Lecture 13.(12.10.06/13.10.06) Estimation in ARMA models. Chapter 2 (2.5.2), Chapter 5 (5.1). Homework: 2.18, 2.20 Lecture 14.(16.10.06) Innovations algorithm. Chapter 2 (2.5.2), Chapter 3 (3.3). Homework: 3.7 Lecture 15.(19.10.06/20.10.06) Prediction and estimation in ARMA models. Chapter 3 (3.3), Chapter 5 (5.1). Homework: 5.1 Lecture 16.(23.10.06) Least squares and maximum likelihood methods in ARMA model estimation. Chapter 5 (5.1, 5.2). Homework: 5.3 Lecture 17.(26.10.06/27.10.06) Order selection for ARMA models. Chapter 5 (5.5). Homework: 5.8 Lecture 18.(30.10.06) The AICC criterion. Diagnostic checking and forecasting with ARMA processes. Chapter 5 (5.5.2, 5.3, 5.4). Homework: 3.5 Lecture 19.(2.11.06/3.11.06) Forecasting with ARMA processes. ARIMA models. Chapter 5 (5.4), Chapter 3 (3.3), Chapter 6 (6.1, 6.2, 6.3). Homework: 3.9 Lecture 20.(6.11.06) Forecasting ARIMA processes. Chapter 6 (6.4). Homework: 6.5 Lecture 21.(9.11.06/10.11.06) Seasonal ARIMA models. Spectral densities. Chapter 6 (6.5), Chapter 4 (4.1). Homework: 6.1 Lecture 22.(13.11.06) Spectral densities. Chapter 4 (4.1). Homework: 4.4 Lecture 23.(16.11.06/17.11.06) Spectral analysis. Chapter 4 (4.1, 4.2, 4.3, 4.4). Homework: - Lecture 24.(20.11.06) Repetition.