[This article was first published on Econometrics Beat: Dave Giles' Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
If you have an interest in forecasting, especially economic forecasting, the Rob Hyndman’s name will be familiar to you. Hailing from my old stamping ground – Monash University – Rob is one of the world’s top forecasting experts.
Last year, Rob taught an on-line forecasting course, titled, “Time Series Forecasting Using R”. It comprised 12 one-hour lectures, on the following topics (with exercises):
- Introduction to forecasting
- The forecaster’s toolbox
- Autocorrelation and seasonality
- White noise and time series decomposition
- Exponential smoothing methods
- ETS models
- Transformations and adjustments
- Stationarity and differencing
- Non-seasonal ARIMA models
- Seasonal ARIMA models
- Dynamic regression
- Advanced methods
The really good news? You can access these presentations right here!
To leave a comment for the author, please follow the link and comment on their blog: Econometrics Beat: Dave Giles' Blog.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.