Blog Archives

COMPSTAT2012

August 28, 2012
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This week I’m in Cyprus attending the COMPSTAT2012 conference. There’s been the usual interesting collection of talks, and interactions with other researchers. But I was struck by two side comments in talks this morning that I’d like to mention. Stephen Pollock: Don’t imagine your model is the truth Actually, Stephen said something like “economists (or was it econometricians?) have...

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Flat forecasts

August 19, 2012
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About once a week someone will tell me there is a bug in my forecast package for R because it gives forecasts that are the same for all future horizons. To save answering the same question repeatedly, here is my response. A point forecast is (usually) the mean of the distribution of a future observation in the time series,...

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Interviews

August 9, 2012
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I’ve been interviewed twice in the last year: For DecisionStats, 9 August 2012. For Data Mining Research, 21 October 2011. Republished in Amstat News, 1 December 2011. Some readers of this blog might find them interesting. I said a few things in t...

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Forecasting the Olympics

July 30, 2012
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Forecasting sporting events is a growing research area. The International Journal of Forecasting even had a special issue on sports forecasting a couple of years ago. The London 2012 Olympics has attracted a few forecasters trying to predict medal counts, world records, etc. Here are some of the articles I’ve seen. Which Olympic records get shattered?, Nate Silver, New...

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Time Series Data Library now on DataMarket

June 19, 2012
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The Time Series Data Library is a collection of about 800 time series that I have maintained since about 1992, and hosted on my personal website. It includes data from a lot of time series textbooks, as well as many other series that I’ve either collected for student projects or helpful people have sent to me. I’ve now moved...

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Constants and ARIMA models in R

June 5, 2012
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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-stationary ARIMA...

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My new forecasting textbook

May 22, 2012
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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 which is already...

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Blog aggregators

May 15, 2012
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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...

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Measuring time series characteristics

May 2, 2012
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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 clustering for...

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Forecasts and ggplot

March 22, 2012
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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 ...

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