This course provides an introduction to time series analysis at the graduate level. The course is about modeling based on three main families of techniques: (i) the classical decomposition into trend, seasonal and noise components; (ii) ARIMA processes and the Box and Jenkins methodology; (iii) Fourier analysis. If time permits, other possible topics include state space modeling and fractional processes. The course is focused on the theory, but some key examples and applications are also covered and implemented in the software package R.pre-rec:
One course from MATH 6020/7240, MATH 6040/7260 or MATH 7360; one course from MATH 7550, MATH 6050/3050 or MATH 6710/7210. Exceptions to these prerequisites may be granted by permission of the instructor.