Articles by Rob J Hyndman

North American seminars: June 2015

June 15, 2015 | Rob J Hyndman

For the next few weeks I am travelling in North America and will be giving the following talks. 19 June: Southern California Edison, Rosemead CA. “Probabilistic forecasting of peak electricity demand”. 23 June: International Symposium on Forecasting, Riverside CA. “MEFM: An R package for long-term probabilistic forecasting of electricity demand”. 25 June: Google, ... [Read more...]

R vs Autobox vs ForecastPro vs …

June 2, 2015 | Rob J Hyndman

Every now and then a commercial software vendor makes claims on social media about how their software is so much better than the forecast package for R, but no details are provided. There are lots of reasons why you might select a particular software solution, and R isn’t for ... [Read more...]

A new R package for detecting unusual time series

May 30, 2015 | Rob J Hyndman

The anomalous package provides some tools to detect unusual time series in a large collection of time series. This is joint work with Earo Wang (an honours student at Monash) and Nikolay Laptev (from Yahoo Labs). Yahoo is interested in detecting unusual patterns in server metrics. The basic idea is ... [Read more...]

New in forecast 6.0

May 14, 2015 | Rob J Hyndman

This week I uploaded a new version of the forecast package to CRAN. As there were a lot of changes, I decided to increase the version number to 6.0. The changes are all outlined in the ChangeLog file as usual. I will highlight some of the more important changes since v5.0 ... [Read more...]

Feeling the FPP love

April 9, 2015 | Rob J Hyndman

It is now exactly 12 months since the print version of my forecasting textbook with George Athanasopoulos was released on Although the book is freely available online, it seems that a lot of people still like to buy print books. It’s nice to see that it has been ... [Read more...]

A new open source data set for anomaly detection

March 31, 2015 | Rob J Hyndman

Yahoo Labs has just released an interesting new data set useful for research on detecting anomalies (or outliers) in time series data. There are many contexts in which anomaly detection is important. For Yahoo, the main use case is in detecting unusual traffic on Yahoo servers. The data set comprises ... [Read more...]

Dark themes for writing

March 17, 2015 | Rob J Hyndman

I spend much of my day sitting in front of a screen, coding or writing. To limit the strain on my eyes, I use a dark theme as much as possible. That is, I write with light colored text on a dark background. I don’t know why this is ... [Read more...]

RSS feeds for statistics and related journals

January 23, 2015 | Rob J Hyndman

I’ve now resurrected the collection of research journals that I follow, and set it up as a shared collection in feedly. So anyone can easily subscribe to all of the same journals, or select a subset of them, to follow on feedly. There are about 90 journals on the list, ... [Read more...]

Seminars in Taiwan

January 5, 2015 | Rob J Hyndman

I’m currently visiting Taiwan and I’m giving two seminars while I’m here — one at the National Tsing Hua University in Hsinchu, and the other at Academia Sinica in Taipei. Details are below for those who might be nearby. Automatic Time Series Forecasting College of Technology Management, Institute ... [Read more...]

Di Cook is moving to Monash

December 23, 2014 | Rob J Hyndman

I’m delighted that Professor Dianne Cook will be joining Monash University in July 2015 as a Professor of Business Analytics. Di is an Australian who has worked in the US for the past 25 years, mostly at Iowa State University. She is moving back to Australia and joining the Department of ... [Read more...]

New R package for electricity forecasting

December 17, 2014 | Rob J Hyndman

Shu Fan and I have developed a model for electricity demand forecasting that is now widely used in Australia for long-term forecasting of peak electricity demand. It has become known as the “Monash Electricity Forecasting Model”. We have decided to release an R package that implements our model so that ... [Read more...]

A time series classification contest

December 14, 2014 | Rob J Hyndman

Amongst today’s email was one from someone running a private competition to classify time series. Here are the essential details. The data are measurements from a medical diagnostic machine which takes 1 measurement every second, and after 32–1000 seconds, the time series must be classified into one of two classes. Some ... [Read more...]

Am I a data scientist?

December 8, 2014 | Rob J Hyndman

Last night I gave a very short talk (less than 5 minutes) at the Melbourne Analytics Charity Christmas Gala, a combined event of the Statistical Society of Australia, Data Science Melbourne, Big Data Analytics and Melbourne Users of R Network. This is (roughly) what I said. Statisticians seem to go through ... [Read more...]

New Australian data on the HMD

November 26, 2014 | Rob J Hyndman

The Human Mortality Database is a wonderful resource for anyone interested in demographic data. It is a carefully curated collection of high quality deaths and population data from 37 countries, all in a consistent format with consistent definitions. I have used it many times and never cease to be amazed at ... [Read more...]

Visualization of probabilistic forecasts

November 21, 2014 | Rob J Hyndman

This week my research group discussed Adrian Raftery’s recent paper on “Use and Communication of Probabilistic Forecasts” which provides a fascinating but brief survey of some of his work on modelling and communicating uncertain futures. Coincidentally, today I was also sent a copy of David Spiegelhalter’s paper on “... [Read more...]

Seasonal periods

November 6, 2014 | Rob J Hyndman

I get questions about this almost every week. Here is an example from a recent comment on this blog: I have two large time series data. One is separated by seconds intervals and the other by minutes. The length of each time series is 180 days. I’m using R (3.1.1) for ... [Read more...]

Jobs at Amazon

October 28, 2014 | Rob J Hyndman

I do not normally post job adverts, but this was very specifically targeted to “applied time series candidates” so I thought it might be of sufficient interest to readers of this blog. Here is an excerpt from an email I received from someone at Amazon: Amazon is aggressively recruiting in ... [Read more...]

Prediction intervals too narrow

October 21, 2014 | Rob J Hyndman

Almost all prediction intervals from time series models are too narrow. This is a well-known phenomenon and arises because they do not account for all sources of uncertainty. In my 2002 IJF paper, we measured the size of the problem by computing the actual coverage percentage of the prediction intervals on ... [Read more...]

hts with regressors

October 19, 2014 | Rob J Hyndman

The hts package for R allows for forecasting hierarchical and grouped time series data. The idea is to generate forecasts for all series at all levels of aggregation without imposing the aggregation constraints, and then to reconcile the forecasts so they satisfy the aggregation constraints. (An introduction to reconciling hierarchical ... [Read more...]
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