Publications by Rob J Hyndman
What you wish you knew before you started a PhD
I asked my research group recently what they wished they had learned before they started work on a PhD. Here are some of the responses. More mathematics. Particular topics they named included real analysis, functional analysis, measure theory, algebra, linear algebra. That would have been my response also. I still wish I knew more mathematics t...
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The art of R programming
This is a gem of a book. It will become the book I give PhD students when they are learning how to write good R code. That is, if I ever see it again. I had hoped to write a review of it, but I haven’t seen it since it arrived in the mail a couple of weeks ago because a research student or research assistant has always had it on loan. I guess t...
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Internet surveys
I received the following email today: I am preparing a thesis … I need to conduct the widest possible poll, and it occurred to me that perhaps you could guide me toward an internet-based way in which this can be done easily. I have a ten-question questionnaire prepared, that I wish to have an random sample of the population respond to. I have n...
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Exponential smoothing and regressors
I have thought quite a lot about including regressors (i.e. covariates) in exponential smoothing (ETS) models, and I have done it a couple of times in my published work. See my 2008 exponential smoothing book (chapter 9) and my 2008 Tourism Management paper. However, there are some theoretical issues with these approaches, which have come to li...
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Data visualization
For those who have not read the seminal works of Tufte and Cleveland, please hang your heads in shame. To salvage some sense of self-worth, you can then head over to Solomon Messing’s blog where he is starting a series on data visualization based on the principles developed by Tufte and Cleveland (with R examples). The classics are also worth r...
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Forecasts and ggplot
The forecast package uses the base R graphics for all plots, but some people may prefer to use the nice graphics available using the ggplot2 package. In the following two posts, Frank Davenport shows how it can be done: Plotting forecast() objects in ggplot part 1: Extracting the Data Plotting forecast() objects in ggplot part 2: Visualize Obser...
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Measuring time series characteristics
A few years ago, I was working on a project where we measured various characteristics of a time series and used the information to determine what forecasting method to apply or how to cluster the time series into meaningful groups. The two main papers to come out of that project were: Wang, Smith and Hyndman (2006) Characteristic-based clu...
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Blog aggregators
A very useful way of keeping up with blogs in a particular area is to subscribe to a blog aggregator. These will syndicate posts from a large number of blogs and provide links back to the original sources. So you only need to subscribe once to get all the good stuff in that area. There are now several blog aggregators available that might be of i...
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My new forecasting textbook
After years of saying that I was going to write a book to replace Makridakis, Wheelwright and Hyndman (1998), I’m finally ready to make an announcement! My new book is Forecasting: principles and practice, co-authored with George Athanasopoulos. It is available online and free-of-charge. We have written about 2/3 of the book so far (all of whic...
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Constants and ARIMA models in R
This post is from my new book Forecasting: principles and practice, available freely online at OTexts.com/fpp/. A non-seasonal ARIMA model can be written as (1) or equivalently as (2) where is the backshift operator, and is the mean of . R uses the parametrization of equation (2). Thus, the inclusion of a constant in a non-stati...
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