Blog Archives

Using ggplot2 for functional time series

December 11, 2018
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Using ggplot2 for functional time series

This week I’ve been attending the Functional Data and Beyond workshop at the Matrix centre in Creswick. I spoke yesterday about using ggplot2 for functional data graphics, rather than the custom-built plotting functionality available in the many functional data packages, including my own rainbow package written with Hanlin Shang. It is a much more powerful and flexible way to work, so...

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M4 Forecasting Conference

October 23, 2018
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M4 Forecasting Conference

Following the highly successful M4 Forecasting Competition, there will be a conference held on 10-11 December at Tribeca Rooftop, New York, to discuss the results. The conference will elaborate on the findings of the M4 Competition, with prominent sp...

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MeDaScIn 2018

August 25, 2018
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The annual Melbourne Data Science Initiative (or MeDaScIn, pronounced medicine) is on again next month (24-27 September) with lots of tutorials, and the annual datathon. This year there will be a “Forecasting with R” workshop (25 September) led my two of my Monash colleagues – George Athanasopoulos and Elena Sanina. Another great tutorial will be led by Steph Kovalchik (from Tennis...

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Saving ts objects as csv files

August 2, 2018
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Occasionally R might not be the tool you want to use (hard to believe, but apparently that happens). Then you may need to export some data from R via a csv file. When the data is stored as a ts object, the time index can easily get lost. So I wrote a little function to make this easier, using...

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Seasonal decomposition of short time series

July 13, 2018
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Seasonal decomposition of short time series

Many users have tried to do a seasonal decomposition with a short time series, and hit the error “Series has less than two periods”. The problem is that the usual methods of decomposition (e.g., decompose and stl) estimate seasonality using at least as many degrees of freedom as there are seasonal periods. So you need at least two observations per...

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A forecast ensemble benchmark

June 23, 2018
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A forecast ensemble benchmark

Forecasting benchmarks are very important when testing new forecasting methods, to see how well they perform against some simple alternatives. Every week I get sent papers proposing new forecasting methods that fail to do better than even the simplest benchmark. They are rejected without review. Typical benchmarks include the naïve method (especially for finance and economic data), the seasonal naïve...

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Upcoming talks: May-July 2018

April 22, 2018
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First semester teaching is nearly finished, and that means conference season for me. Here are some talks I’m giving in the next two months. Click the links for more details. Melbourne, Australia. 28 May: Panel discussion: Forecasting models, the uncertainties and associated risk Boulder, Colorado, USA. 17-20 June: International Symposium on Forecasting. I’ll be talking about “Tidy forecasting in R”. New York,...

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Forecasting in NYC: 25-27 June 2018

April 22, 2018
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In late June, I will be in New York to teach my 3-day workshop on Forecasting using R. Tickets are available at Eventbrite. This is the first time I’ve taught this workshop in the US, having previously run it in the Netherlands and Australia. It will be based on the 2nd edition of my book “Forecasting: Principles and Practice” with...

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forecast v8.3 now on CRAN

April 13, 2018
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forecast v8.3 now on CRAN

The latest version of the forecast package for R is now on CRAN. This is the version used in the 2nd edition of my forecasting textbook with George Athanasopoulos. So readers should now be able to replicate all examples in the book using only CRAN pack...

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A brief history of time series forecasting competitions

April 10, 2018
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Prediction competitions are now so widespread that it is often forgotten how controversial they were when first held, and how influential they have been over the years. To keep this exercise manageable, I will restrict attention to time series forecasting competitions — where only the history of the data is available when producing forecasts. Nottingham studies The earliest non-trivial study of time...

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