The Analysis of Time Series (4)
Some more details re the project
Course homepage: http://www.stat.berkeley.edu/~brill/Stat248/index.html
Classes: TuTh 1400-1530 in 310 Hearst Mining
Lab Section: Fri 1100-1300 in 330 Evans
Meant for graduate students in Statistics and other Departments.
A recommended text is:
Brillinger, D. R. (2001). Time Series Data Analysis and Theory. SIAM Reprint.
A text that will be followed to some degree is:
L. Ljung (1999). System Identification: Theory for the User. Second Edition, Prentice Hall.
Text for Lab: W.N. Venables and B.D. Ripley. Modern Applied Statistics with S-Plus, Springer. A recent edition.
The statistical packages R and Splus will be used. Some may choose to use Matlab.
The focal topic of the course will be system identification. This is the random process analog of regression analysis. There will be consideration of the cases: time series, point processes, spatial processes, spatial-temporal processes and others.
The grade will come from a combination of Homeworks, a Project Proposal and an Independent Project.
Prerequisites: Statistics 101&102 or 134&135 or equivalents.
Instructor: David R. Brillinger
Office Hours:Wed 1500-1800. In 417 Evans.
GSI: Apratim Guha
Office Hours: M 2-4, Tu 3:30-4:30 and F 1-2
2/2/2004