SDS 461 Time Series Analysis

Instructor: Likai Chen (likai.chen[at]wustl.edu)

Lectures: Cupples II Room 230, 1:00p.m-1:50 p.m on Mondays, Wednesdays, and Fridays

Office hour: TBD

Schedule

Topics covered

Generalities of time series and exploratory data analysis: data types, trend, seasonality, nonstationarity and stationarity; Time-series in the time domain and autocorrelation; autoregressive integrated moving average (ARIMA) models; model selection methods; forecasting; frequency domain and spectral analysis; State-Space Models and Kalman Filter; Nonlinear time series; multivariate time series. More advanced topics if time allows it.

Prerequisites

Math 493 (Probability) and 494 (Mathematical Statistics); or permission of the instructor. Some programming experience in R is useful but not essential.

Textbook

Time Series Analysis and Its Applications (with R examples).
R.H. Shumway and D.S.Stoffer, 4th Edition, Springer.
Available for free download on Springer Link through our library website.

Exams

There will be one midterm and one comprehensive final. The final is scheduled Dec 6 2024 1:00PM - 3:00PM.

Make-up exams are strongly discouraged. If you are aware of a conflict, please inform the instructor before the exam. Make-up exam will only be given if (1) within 1 week of the standard exam and (2) suitable documentation is provided within 2 days.

Homeworks

The homework assignments will be given bi-weekly and are due on Wednesday midnight. NO LATE HOMEWORK WILL BE ACCEPTED.

Homework collection via Canvas

Please submit hws through canvas. Solutions will be posted to our course website.

Grades

Your grade will be based on homework, midterm and final exam.

Midterms 30%
Final 40%
Homework 30%

The threshold for each grade

A A- B+ B B- C + C C -
90 or above88-90 86-88 77-86 75-77 73-75 65-73 60-65
Only very few top students will get A+.

Software

Open-source software R for statistical computing, and its manual .
Download R from Wustl's software.
Download R Studio from its developer's website.