Time series cross-validation using fable

Time series cross-validation is handled in the fable package using the stretch_tsibble() function to generate the data folds. In this post I will give two examples of how to use it, one without covariates and one with covariates. Quarterly Australian beer production Here is a simple example using quarterly Australian beer production from 1956 Q1 to 2010 Q2. First we create a data object containing many training sets starting with 3 years (12 observations), and adding one quarter at a time until all data are included.

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Forecasting podcasts

I’ve been interviewed for several podcasts over the last year or so. It’s always fun to talk about my work, and I hope there is enough differences between them to make it interesting for listeners. Here is a full list of them.

Date Podcast Episode
12 April 2021 Seriously Social Forecasting the future: the science of prediction
6 February 2021 Forecasting Impact Rob Hyndman
19 July 2020 The Curious Quant Forecasting COVID, time series, and why causality doesnt matter as much as you think‪
27 May 2020 The Random Sample Forecasting the future & the future of forecasting
9 October 2019 Thought Capital Forecasts are always wrong (but we need them anyway)

Call for papers: Innovations in hierarchical forecasting

There is a new call for papers for a special issue of the International Journal of Forecasting on “Innovations in hierarchical forecasting”.

Guest editors: George Athanasopoulos, Rob J Hyndman, Anastasios Panagiotelis, and Nikolaos Kourentzes.

Submission deadline: 31 August 2021.

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Recent papers

  • Rob J Hyndman (2021) Quantile forecasting with ensembles and combinations. Chapter in Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning, eds. Gilliland, Tashman & Sglavo. pp.371-375, John Wiley & Sons. Abstract Amazon  pdf  code
  • Pablo Montero-Manso, Rob J Hyndman (2021) Principles and Algorithms for Forecasting Groups of Time Series: Locality and Globality. International J Forecasting, to appear. Abstract  pdf
  • Rob J Hyndman, Yijun Zeng, Han Lin Shang (2021) Forecasting the old-age dependency ratio to determine a sustainable pension age. Australian & New Zealand Journal of Statistics, to appear. Abstract  pdf  code
  • Sevvandi Kandanaarachchi, Rob J Hyndman (2021) Dimension reduction for outlier detection using DOBIN. J Computational & Graphical Statistics, 30(1), 204-219. Abstract DOI  pdf  code
  • Bahman Rostami-Tabar, Mohammad M Ali, Tao Hong, Rob J Hyndman, Michael D Porter, Aris Syntetos (2021) Forecasting for Social Good. International Journal of Forecasting, to appear. Abstract  pdf

Recent and upcoming seminars