Terminology matters

I was reminded again this week that getting the right terminology is important. Some of my colleagues who work in machine learning wrote a paper entitled “Time series regression” which began with “This paper introduces Time Series Regression (TSR): a little-studied task …”. Statisticians and econometricians have done time series regression for many decades, so this beginning led to the paper being lampooned on Twitter. The problem arose due to clashes in terminology being used in different fields.

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Seasonal mortality rates

The weekly mortality data recently published by the Human Mortality Database can be used to explore seasonality in mortality rates. Mortality rates are known to be seasonal due to temperatures and other weather-related effects (Healy 2003).

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Excess deaths for 2020

The reported COVID19 deaths in each country are often undercounts due to different reporting practices, or people dying of COVID19 related causes without ever being tested. One way to explore the true mortality effect of the pandemic is to look at “excess deaths” — the difference between death rates this year and the same time in previous years. The Financial Times (and other media outlets) have been collecting data from many countries to try to measure this effect.

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Recent publications

  • Sevvandi Kandanaarachchi, Rob J Hyndman and Kate Smith‑Miles (2020) Early classification of spatio-temporal events using partial information. PLOS ONE, to appear. Abstract  pdf
  • Anastasios Panagiotelis, Puwasala Gamakumara, George Athanasopoulos, Rob J Hyndman (2020) Forecast reconciliation: A geometric view with new insights on bias correction. International J Forecasting, to appear. Abstract  pdf
  • Evangelos Spiliotis, Mahdi Abolghasemi, Rob J Hyndman, Fotios Petropoulos, Vassilios Assimakopoulos (2020) Hierarchical forecast reconciliation with machine learning. Abstract  pdf
  • Yanfei Kang, Rob J Hyndman, Feng Li (2020) GRATIS: GeneRAting TIme Series with diverse and controllable characteristics. Statistical Analysis and Data Mining, 13(4), 354-376. Abstract DOI  pdf
  • Priyanga Dilini Talagala, Rob J Hyndman, Kate Smith-Miles, Sevvandi Kandanaarachchi and Mario A Muñoz (2020) Anomaly detection in streaming nonstationary temporal data. Journal of Computational and Graphical Statistics, 20(1), 13-27. Abstract DOI  pdf

Recent and upcoming seminars

  • Forecasting the Future & the Future of Forecasting. (27 May 2020) More info...
  • Developing good research habits. (31 March 2020) More info...
  • How Rmarkdown changed my life. (30 January 2020) More info...
  • Tidy time series & forecasting in R. (27 January 2020) More info...
  • The journal game. (29 October 2019) More info...