Melbourne Data Science Week - 29 May - 2nd June 2017

Time Series in R, Forecasting and Visualisation

29 May 2017
09:00 - 17:00
KPMG, Tower Two, Collins Square, 727 Collins St.

Time Series in R, Forecasting and Visualisation

Prerequisites: An introductory level statistics knowledge. Basic R language programming.

Requirements: Laptop loaded with latest version of R, and a selection of packages to be provided later. Workshop is hands-on.

  1. As workshop is hands-on, please bring a laptop loaded with a latest version of R and RStudio.
  2. You should also have installed the fpp2 package and its dependencies for the forecasting part.
  3. You should also have installed the following packages for the visualisation part: tidyverse, plotly, stringr, forecast, lubridate, broom, zoo, shiny, devtools, and knitr.

You may find a collection of cheat sheets provided by RStudio are helpful for getting started with R and the packages.

We’ll make a webpage available for the workshop, where you can download the slides, data, and lab exercises.

Content Summary:

1. Time series and R
2. Visualising temporal data
3. Some automatic forecasting algorithms
4.  Forecast evaluation

 

Rob Hyndman: Professor of Statistics, Econometrics and Business Statistics, Monash University. World’s leading forecaster. Editor of the International Journal of Forecasting. Author of two major monographs, and several R packages.

Earo Wang: PhD student, Econometrics and Business Statistics, Monash University. Author of two R packages for time series modeling and visualisation