Articles by R on Rob J Hyndman

A forecast ensemble benchmark

June 23, 2018 | R on Rob J Hyndman

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 naï...
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Upcoming talks: May-July 2018

April 22, 2018 | R on Rob J Hyndman

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 ... [Read more...]

Forecasting in NYC: 25-27 June 2018

April 22, 2018 | R on Rob J Hyndman

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 ... [Read more...]

forecast v8.3 now on CRAN

April 13, 2018 | R on Rob J Hyndman

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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M4 Forecasting Competition update

December 21, 2017 | R on Rob J Hyndman

The official guidelines for the M4 competition have now been published, and there have been several developments since my last post on this. There is now a prize for prediction interval accuracy using a scaled version of the Mean Interval Score. If...
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Some new time series packages

November 28, 2017 | R on Rob J Hyndman

This week I have finished preliminary versions of two new R packages for time series analysis. The first (tscompdata) contains several large collections of time series that have been used in forecasting competitions; the second (tsfeatures) is designed to compute features from univariate time series data. For now, both are ...
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M4 Forecasting Competition

November 18, 2017 | R on Rob J Hyndman

The “M” competitions organized by Spyros Makridakis have had an enormous influence on the field of forecasting. They focused attention on what models produced good forecasts, rather than on the mathematical properties of those models. For that, Spyros deserves congratulations for changing the landscape of forecasting research through this series ...
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Come and work with me

November 13, 2017 | R on Rob J Hyndman

I have funding for a new post-doctoral research fellow, on a 2-year contract, to work with me and Professor Kate Smith-Miles on analysing large collections of time series data. We are particularly seeking someone with a PhD in computational statistics or statistical machine learning. Desirable characteristics: Experience with time series ... [Read more...]

2017 Beijing Workshop on Forecasting

October 31, 2017 | R on Rob J Hyndman

Later this month I’m speaking at the 2017 Beijing Workshop on Forecasting, to be held on Saturday 18 November at the Central University of Finance and Economics. I’m giving four talks as part of the workshop. Other speakers are Junni Zhang, Lei Song, Hui Bu, Feng Li and Yanfei Kang. ... [Read more...]

Looking for a new research assistant

September 7, 2017 | R on Rob J Hyndman

I’m currently looking for a new research assistant to help (primarily) with some modelling and R coding as part of a project on forecasting mobile phone sales. The position is likely to last for about 6–9 months, and will be casual. Requirements Based in Melbourne. I’d rather not communicate ... [Read more...]

rOpenSci OzUnconference coming to Melbourne

September 6, 2017 | R on Rob J Hyndman

For a second year running, there will be another rOpenSci OzUnconference in Australia. This one will be held in Melbourne, on 26-27 October 2017. Unlike regular conferences, there are no talks and there is no pre-determined agenda. It brings together scientists, developers, and open data enthusiasts from academia, industry, government, and ... [Read more...]

Finding distinct rows of a tibble

August 30, 2017 | R on Rob J Hyndman

I’ve been using R or its predecessors for about 30 years, so I tend to I know a lot about R, but I don’t necessarily know how to use modern R tools. Lately, I’ve been teaching my students the tidyverse approach to data analysis, which means that I ... [Read more...]

Forecasting workshop in Perth

July 29, 2017 | R on Rob J Hyndman

On 26-28 September 2017, I will be running my 3-day workshop in Perth on “Forecasting: principles and practice” based on my book of the same name. Topics to be covered include seasonality and trends, exponential smoothing, ARIMA modelling, dynamic regression and state space models, as well as forecast accuracy methods and ... [Read more...]

Prediction intervals for NNETAR models

May 24, 2017 | R on Rob J Hyndman

The nnetar function in the forecast package for R fits a neural network model to a time series with lagged values of the time series as inputs (and possibly some other exogenous inputs). So it is a nonlinear autogressive model, and it is not possible to analytically derive prediction intervals. ...
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Monthly seasonality

May 2, 2017 | R on Rob J Hyndman

I regularly get asked why I don’t consider monthly seasonality in my models for daily or sub-daily time series. For example, this recent comment on my post on seasonal periods, or this comment on my post on daily data. The fact is, I’ve never seen a time series ... [Read more...]
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