MATH 843 (01) - Time Series Analysis

Time Series Analysis

Durham   Engineering&Physical Sciences :: Mathematics&Statistics
Credits: 3.0
Term: Spring 2021 - Full Term (02/01/2021 - 05/11/2021)
Grade Mode: Letter Grading
Class Size:   5  
CRN: 56055
An introduction to univariate time series models and associated methods of data analysis and inference in the time domain and frequency domain. Topics include: Auto regressive (AR), moving average (MA), ARMA and ARIMA processes, stationary and non-stationary processes, seasonal ARIMA processes, auto-correlation and partial auto-correlation functions, identification of models, estimation of parameters, diagnostic checking of fitted models, forecasting, spectral density function, periodogram and discrete Fourier transform, linear filters. parametric spectral estimation, dynamic Fourier analysis. Additional topics may include wavelets and long memory processes (FARIMA) and GARCH Models. The use of statistical software, such as JMP, or R, is fully integrated in to the course. Offered in alternate years in the spring.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Prerequisite(s): (MATH 835 with minimum grade of B- or MATH 839 with minimum grade of B- )
Instructors: Linyuan Li

Times & Locations

Start Date End Date Days Time Location
2/1/2021 5/11/2021 MWF 9:40am - 11:00am KING S320