Time Series and Forcasting

MATH4826, STAT3830 (Department of Mathematics, Hong Kong Baptist University)

Topics

• Chapter 1. Introduction to Time Series. [Slides]
  • Example 1.1 Sunspots data (built-in Matlab, see slides)
  • Example 1.2 Canadian lynx data [download]
  • Example 1.3 Interest rate data [download]
  • Example 1.4 The Standard and Poor's 500 Index [download]
• Chapter 2. An overview of predictive learning and functional approximation. [Slides]
• Chapter 3. Regression analysis.
  • Chapter 3 A: A quick review of classical linear regression. [Slides]
    • Advertising data [download]
    • Auto data [download]
    • Credit data [download]
  • Chapter 3 B: Regularized linear regression and model selection. [Slides]
• Chapter 4. Stochastic Time Series Model.
  • A. Stationary ARMA process [Slides]
  • B. Forecasting [Slides]
  • C. Application and Examples about Building ARIMA models [Slides]
    • Suggested game: Google Correlate. [Tutorial: A Hands-on Guide to Google Data]
  • D. Parameter Estimation [Slides]
    • Suggested reading: Frequentism and Bayesianism Part I; Part II; Part III; Part IV.
    • Suggested reading: Points of Significance: Bayes' Theorem. Nature Methods. 2015.
    • Suggested reading: Chapters 1-5 of Doing Bayesian Data Analysis. By John K. Kruschke. [e-Book HKBU library link][Book website]
    • Suggested reading: How Computers Trawl a Sea of Data for Stock Picks [English Version][Chinese Version (translated)]
• Epilogue: Beyond Time Series analysis, where to go from here [Slides]
  • An interesting blog: The Non-parametric Bootstrap as a Bayesian Model.
  • Naked Statistics: Stripping the Dread from the Data by Charles Wheelan.
  • Learning from Data by Yaser S. Abu-Mostafa, Malik Magdon-Ismail and Hsuan-Tien Lin. [On-line course by Yaser S. Abu-Mostafa]
  • Pattern recognition and machine learning by Christopher M. Bishop.
  • Elements of Statistical Learning by Trevor Hastie, Robert Tibshrani and Jerome Friedman.

Reference Books

Assignment

• Assignment 1. [pdf; Assigned reading on Big Data: 1. The rise of Big Data. 2. "Machine-Learning Maestro Michael Jordan on the Delusions of Big Data and Other Huge Engineering Efforts"; please also check here for more comments from Michael Jordan] [Solution]
• Assignment 2. [pdf] [Solution]
• Assignment 3. [pdf]

TA

• Min ZHOU
• Email: 14485494@life.hkbu.edu.hk