Publications by Rob J Hyndman
Removing white space around R figures
When I want to insert figures generated in R into a LaTeX document, it looks better if I first remove the white space around the figure. Unfortunately, R does not make this easy as the graphs are generated to look good on a screen, not in a document. There are two things that can be done to fix this problem. First, you can reduce the white space ...
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ETS models now in EViews 8
The ETS modelling framework developed in my 2002 IJF paper (with Koehler, Snyder and Grose), and in my 2008 Springer book (with Koehler, Ord and Snyder), is now available in EViews 8. I had no idea they were even working on it, so it was quite a surprise to be told that EViews now includes ETS models. Here is the blurb from the release notes: E...
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My new forecasting book is finally finished
My new online forecasting book (written with George Athanasopoulos) is now completed. I previously described it on this blog nearly a year ago. In reality, an online book is never complete, and we plan to continually update it. But it is now at the point where it is suitable for course work, and contains exercises and references. We hope that use...
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Forecasting annual totals from monthly data
This question was posed on crossvalidated.com: I have a monthly time series (for 2009–2012 non-stationary, with seasonality). I can use ARIMA (or ETS) to obtain point and interval forecasts for each month of 2013, but I am interested in forecasting the total for the whole year, including prediction intervals. Is there an easy way in R to obtain...
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Facts and fallacies of the AIC
Akaike’s Information Criterion (AIC) is a very useful model selection tool, but it is not as well understood as it should be. I frequently read papers, or hear talks, which demonstrate misunderstandings or misuse of this important tool. The following points should clarify some aspects of the AIC, and hopefully reduce its misuse. The AIC is a p...
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Reflections on UseR! 2013
This week I’ve been at the R Users conference in Albacete, Spain. These conferences are a little unusual in that they are not really about research, unlike most conferences I attend. They provide a place for people to discuss and exchange ideas on how R can be used. Here are some thoughts and highlights of the conference, in no particular order...
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Online course on forecasting using R
I am teaming up with Revolution Analytics to teach an online course on forecasting with R. 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 forecast evaluation techniques such as cross-validation. I will talk about some ...
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Forecasting with daily data
I’ve had several emails recently asking how to forecast daily data in R. Unless the time series is very long, the simplest approach is to simply set the frequency attribute to 7. y <- ts(x, frequency=7) Then any of the usual time series forecasting methods should produce reasonable forecasts. For example library(forecast) fit <- ets(y) fc <- fo...
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Forecasting with R
The following video has been produced to advertise my upcoming course on Forecasting with R, run in partnership with Revolution Analytics. The course will run from 21 October to 4 December, for two hours each week. More details are available at http://robjhyndman.com/hyndsight/revolutionr2013/ If you are interested, please register for the cours...
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Questions on my online forecasting course
I’ve been getting emails asking questions about my upcoming course on Forecasting using R. Here are some answers. Do I need to use the Revolution Enterprise version of R, or can I use open-source R? Open source R is fine. Revolution Analytics is organizing the course, but there is no requirement to use their software. I will be using open sourc...
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