Time Series and Spatial Statistics

Instructor

• Nan Zhang

Textbooks

• Shumway and Stoffer (2017). Time Series Analysis and Its Applications: with R Examples, Springer, 4th edition. tsa4
• Cressie and Wikle (2011). Statistics for Spatio-temporal Data, Wiley.

Reference

• Brockwell and Davis (2016). Introduction to Time Series and Forecasting, Springer, 4th edition.
• Wikle, Zammit-Mangion and Cressie (2019). Spatio-temporal Statistics with R, CRC Press. link

Schedule

• Week 1: Introduction to Time Series Analysis.
• Week 2: Characteristics of Time Series.
• Week 3: Time Series Regression.
• Week 4: Exploratory Data Analysis.
• Week 5: ARMA Models.
• Week 6: Difference Equations. Autocorrelation Function.
• Week 7: Partial Autocorrelation Function.
• Week 8: Forecasting.
• Week 9: Midterm.
• Week 10: Estimation: Yule-Walker Equation, Least Squares and MLE.
• Week 11: ARIMA.
• Week 12: Introduction to Gaussian Processes.
• Week 13: Covariance and Variogram.
• Week 14: Spatial Prediction: Kriging.
• Week 15: Forecasting with Deep Learning.
• Week 16: Spectral Analysis.