Time series analysis
Time Series Toolbox
25 April 2019
Outline: Time Series in Practice
- When and why do we need time series models?
- Basic models and definitions: white noise, AR1, MA, random walk, stationarity.
- 3 approaches to time series modelling: ARIMA, Regression, Structural time series / state-space models
understand basic difficulties with time series, construct a few simple but useful models
Hyndman, R.J., & Athanasopoulos, G. (2018) Forecasting: Principles and Practice, 2nd edition, OTexts: Melbourne, Australia. https://otexts.com/fpp2
Applied Time Series Analysis for Fisheries and Environmental Sciences. E. E. Holmes, M. D. Scheuerell, and E. J. Ward. (2019). https://nwfsc-timeseries.github.io/atsa-labs/index.html
- Shumway, R.H. and Stoffer, D.S., 2017. Time series analysis and its applications: with R examples. Springer. https://www.stat.pitt.edu/stoffer/tsa4/
Motivating Example: Mauna Loa Atmospheric CO2 Concentration
fpp2 is the package for the book by Hyndman: Forecasting: Principles and Practice, 2nd edition.