Time Series Analysis
This course mainly introduces algorithms and applications related to time series, including data decomposition and basic preprocessing, (non)linear stationary models, spectral analysis in the frequency domain, deep learning-based prediction, time series clustering, changepoint, and outlier detection, multivariate time series analysis and state space models.
Additionally, we will introduce two unsolved problems in real applications. One is the changepoint in medical insurance analysis with 北京市医疗保障局. The other is a multivariable correlation problem in the braking system with COMAC. I will introduce these problems in the first class and provide some related models in the subsequent courses. You are welcome to join and share your ideas!
Additionally, we will introduce two unsolved problems in real applications. One is the changepoint in medical insurance analysis with 北京市医疗保障局. The other is a multivariable correlation problem in the braking system with COMAC. I will introduce these problems in the first class and provide some related models in the subsequent courses. You are welcome to join and share your ideas!
Lecturer
Date
24th September ~ 12th December, 2024
Location
| Weekday | Time | Venue | Online | ID | Password |
|---|---|---|---|---|---|
| Thursday | 15:20 - 16:55 | A3-3-201 | ZOOM 13 | 637 734 0280 | BIMSA |
Prerequisite
Basic knowledge of analysis and neural networks
Syllabus
1. Introduction and Two Examples
2. Data Decomposition and Processing
3. Linear Stationary Models
4. Nonlinear Stationary Models: ARIMA
5. Spectral Analysis and Filtering
6. Forecasting-1: Prophet and its variants
7. Forecasting-2: LSTM and Transformer
8. Forecasting-3: TKAN and its variants
9. Time Series Clustering
10. Changepoint and Outlier Detection
11. Multivariate Time Series Analysis
12. State Space Models
2. Data Decomposition and Processing
3. Linear Stationary Models
4. Nonlinear Stationary Models: ARIMA
5. Spectral Analysis and Filtering
6. Forecasting-1: Prophet and its variants
7. Forecasting-2: LSTM and Transformer
8. Forecasting-3: TKAN and its variants
9. Time Series Clustering
10. Changepoint and Outlier Detection
11. Multivariate Time Series Analysis
12. State Space Models
Reference
[1] Time Series Analysis Forecasting and Control, Fifth Edition, George E. P. Box, Gwilym M. Jenkins, Gregory C. Reinsel, Greta M. Ljung
[2] Time Series Analysis and Its Applications With R Examples, Fourth Edition, Robert H. Shumway David S. Stoffer
[3] The Latest Related Papers
[2] Time Series Analysis and Its Applications With R Examples, Fourth Edition, Robert H. Shumway David S. Stoffer
[3] The Latest Related Papers
Audience
Undergraduate
, Advanced Undergraduate
, Graduate
, Postdoc
, Researcher
Video Public
No
Notes Public
Yes
Language
Chinese