Exploratory time series analysis using R
Many organisations collect huge amounts of data over time, and we need time series analysis tools capable of handling the scale, frequency and structure of the data collected. In this workshop, we will look at some R packages and methods that have been developed to handle the analysis of large collections of time series. We will look at the tsibble data structure for flexibly managing collections of related time series, and consider how to do data wrangling, data visualisation, and exploratory data analysis to analyse time series data in high dimensions.
Rob Hyndman is Professor of Statistics in the Department of Econometrics and Business Statistics at Monash University. From 2005 to 2018 he was Editor-in-Chief of the International Journal of Forecasting and a Director of the International Institute of Forecasters. Rob is the author of over 200 research papers and 5 books in statistical science. He is an elected Fellow of both the Australian Academy of Science and the Academy of Social Sciences in Australia. In 2007, he received the Moran medal from the Australian Academy of Science for his contributions to statistical research, especially in the area of statistical forecasting. In 2021, he received the Pitman medal from the Statistical Society of Australia. For over 30 years, Rob has maintained an active consulting practice, assisting hundreds of companies and organizations around the world. He has won awards for his research, teaching, consulting and graduate supervision.
- Session 1: How to wrangle time series data with familiar tidy tools.
- Session 2: How to visualize the trend and seasonal patterns in individual time series.
- Session 3: How to compute time series features and visualize large collections of time series.