ST534 - Applied Time Series Analysis
- Prerequisites: ST 512 or ST 514 or ST 515 or ST 517
- Term & Frequency: Fall semester, every year
- Student Audience: Graduate students in Statistics and in other quantitative fields who plan to work with time series data
- Credit: 3 credits
- Recent Texts: Time Series Analysis and Its Applications, by Robert H. Shumway and David S. Stoffer; Springer.
- Recent Instructors: Peter Bloomfield, Soumendra Lahiri
- Background and Goals: The goal of this course is to introduce the student to the most important methods for analyzing time series data, from both the time domain and frequency domain perspectives.
- Content: Exploratory analysis of time series; Time domain methods, such as ARIMA models; Frequency domain methods, including periodogram and spectrum analysis, filtering, and transfer functions; Transfer function modelling in the time domain; Further topics, such as long memory and conditional heteroscedasticity models
- Alternatives: None
- Subsequent Courses: ST 730 is now a PhD level course..
S1 2017 Sections:
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