A few days ago I released version 4.0 of the forecast package for R. There were quite a few changes and new features, so I thought it deserved a new version number. I keep a list of changes in the Changelog for the package, but I doubt that many people look ... [Read more...]

I gave this talk last night to the Melbourne Users of R Network. Examples [Read more...]

Updated: 21 November 2012 Make is a marvellous tool used by programmers to build software, but it can be used for much more than that. I use make whenever I have a large project involving R files and LaTeX files, which means I use it for almost all of the papers I ... [Read more...]

Forecasters are often met with skepticism. Almost every time I tell someone that I work in forecasting, they say something about forecasting the stock market, or forecasting the weather, usually suggesting that such forecasts are hopelessly inaccurate. In fact, forecasts of the weather are amazingly accurate given the complexity of ... [Read more...]

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 ... [Read more...]

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 ... [Read more...]

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... [Read more...]

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 ... [Read more...]

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 ... [Read more...]

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 ... [Read more...]

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 ... [Read more...]

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 ... [Read more...]

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 ... [Read more...]

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 ... [Read more...]

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 ... [Read more...]

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, ... [Read more...]

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 ... [Read more...]

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 ... [Read more...]

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 ... [Read more...]

It is good to see forecasting algorithms getting some mainstream exposure on ABC Catalyst. [Read more...]