Blog Archives

Di Cook is moving to Monash

December 23, 2014
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Di Cook is moving to Monash

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 Econometrics and Business Statistics in the

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New R package for electricity forecasting

December 17, 2014
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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 other people can easily use it.

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A time series classification contest

December 14, 2014
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A time series classification contest

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 pre-classified training data is

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Am I a data scientist?

December 8, 2014
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Am I a data scientist?

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 regular periods of existential crisis as

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New Australian data on the HMD

November 26, 2014
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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 the care taken to maintain

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Visualization of probabilistic forecasts

November 21, 2014
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Visualization of probabilistic forecasts

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 “Visualizing Uncertainty About the Future”. Both are

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Seasonal periods

November 6, 2014
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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 forecasting the data. I’d

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Jobs at Amazon

October 28, 2014
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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 the data sciences, and we

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Prediction intervals too narrow

October 21, 2014
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Prediction intervals too narrow

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 hold-out samples. We found

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hts with regressors

October 19, 2014
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hts with regressors

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 and grouped time series is

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