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CPD153 - Time series analysis and forecasting using R

  • 9 Nov 2022
  • (AEDT)
  • 10 Nov 2022
  • (AEDT)
  • 2 sessions
  • 9 Nov 2022, 9:00 AM 5:00 PM (AEDT)
  • 10 Nov 2022, 9:00 AM 5:00 PM (AEDT)
  • Venue: Room 5.02, Marie Reay Teaching Building, The Australian National University
  • 5

Registration

  • Registration for a non-member of SSA.
  • Only available to staff and students at RSFAS, ANU
  • Registration for SSA ECSS/transitional members.
  • Registration for both days for an SSA regular member.

Registration is closed

The SSA Canberra Branch warmly invites you to an in-person workshop on Time series analysis and forecasting using R , taught by Professor Rob J Hyndman (Monash University) and Associate Professor Bahman Rostami-Tabar (Cardiff University, UK). 


**Places for this in-person workshop in Canberra are limited; please register ASAP to secure your place!**


About the workshop:


It is becoming increasingly common for organizations to collect huge amounts of data over time, and existing time series analysis tools are not always suitable to handle the scale, frequency and structure of the data collected. In this workshop, we will look at some packages and methods that have been developed to handle the analysis of large collections of time series.

On day 1, we will look at the tsibble data structure for flexibly managing collections of related time series. We will look at how to do data wrangling, data visualizations and exploratory data analysis. We will explore feature-based methods to explore time series data in high dimensions. A similar feature-based approach can be used to identify anomalous time series within a collection of time series, or to cluster or classify time series. Primary packages for day 1 will be tsibble, lubridate and feasts (along with the tidyverse of course).

Day 2 will be about forecasting. We will look at some classical time series models and how they are automated in the fable package. We will look at creating ensemble forecasts and hybrid forecasts, as well as some new forecasting methods that have performed well in large-scale forecasting competitions. Finally, we will look at forecast reconciliation, allowing millions of time series to be forecast in a relatively short time while accounting for constraints on how the series are related.

About the presenters:

Rob J Hyndman FAA FASSA is Professor of Statistics in the Department of Econometrics and Business Statistics at Monash University. He 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.

Bahman Rostami-Tabar is Associate Professor in Management Science & Analytics at Cardiff Business School, Cardiff University, UK. He is the founder and Chair of the Forecasting for Social Good initiatives sponsored by the International Institute of Forecasters. He has provided forecasting training in some of the world’s least developed countries, and for many organizations with social missions. He develops and uses management science and analytic tools and techniques to improve decision-making in healthcare, humanitarian operations and supply chain sectors.


Target audience:

This course will be appropriate for you if you answer yes to these questions:

  1. Do you already use R regularly, especially the tidyverse packages, or are willing to do suitable pre-course training in R and tidyverse?

  2. Do you need to analyse large collections of related time series?

  3. Would you like to learn how to use some new tidy tools for time series analysis including visualization, decomposition and forecasting?

People who don't use R regularly, or don't know the tidyverse packages, are recommended to do the tutorials at learnr.numbat.space beforehand.


Learning objectives:

  • How to wrangle time series data with familiar tidy tools.

  • How to compute time series features and visualize large collections of time series.

  • How to select a good forecasting algorithm for your time series.

  • How to ensure forecasts of a large collection of time series are coherent.


Requirements:

You will need to bring your own laptop to the workshop. Please make sure you have the required packages installed before you arrive. The following command will install the packages you need. 

install.packages(c(

  "tidyverse",

  "fpp3",

  "GGally",

  "sugrrants"

))


Say no more and sign me up!:

The workshop is strictly in person, running from 9am to 5pm (with breaks in between) on November 9-10, 2022. The workshop will be run in Room 5.02, Marie Reay Teaching Building, The Australian National University in Canberra.


Registration costs are as listed on this event website. Note registration includes morning and afternoon teas, but not lunch. Students enrolled in any tertiary institution can become SSA Student members for an annual fee of only $20. Early career people (less than 3 years after completing their degree) can become SSA Early Career members for $125. The cost of membership provides a substantial discount on the full workshop rate in both cases.


Registrations close midnight Canberra time, Friday 28 October.


Cancellations received prior to midnight Canberra time Tuesday 1 November 2022 will be refunded, minus an administration fee. From then onwards, no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to eo@statsoc.org.au.


If you have any questions, please SSA Canberra (ssacanberra@gmail.com) or Marie-Louise Rankin (eo@statsoc.org.au)

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