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...]

R has great support for Holt-Winter filtering and forecasting. I sometimes use this functionality, HoltWinter & predict.HoltWinter, to forecast demand figures based on historical data. Using the HoltWinter functions in R is pretty straightforward. Let's say our dataset looks as follows; demand [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...]

I finally got around to publishing my time series cross-validation package to github, and I plan to push it out to CRAN  shortly. You can clone the repo using github for mac, for windows, or linux, and then run the following script to... [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 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...]

Lately I've been using Rob J Hyndman's excellent forecast package. The package comes with some built in plotting functions but I found I wanted to customize and make my own plots in ggplot. In order to do that, I need a generalizable function that will... [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...]

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

I was recently asked how to implement time series cross-validation in R. Time series people would normally call this “forecast evaluation with a rolling origin” or something similar, but it is the natural and obvious analogue to leave-one-out cross-validation for cross-sectional data, so I prefer to call it “time series ... [Read more...]

The forecast package for R has undergone a major upgrade, and I’ve given it version number 3 as a result. Some of these changes were suggestions from the forecasting workshop I ran in Switzerland a couple of months ago, and some have been on the drawing board for a long ... [Read more...]

I’ll be giving a talk on Forecasting time series using R for the Melbourne Users of R Network (MelbURN) on Thursday 27 October 2011 at 6pm. I will look at the various facilities for time series forecasting available in R, concentrating on the forecast package. This package implements several automatic methods ... [Read more...]

I received an email today with the following comment: I’m using ARIMA with Intervention detection and was planning to use your package to identify my initial ARIMA model for later iteration, however I found that sometimes the auto.arima function returns a model where AR/MA coefficients are not ... [Read more...]

I don’t normally post job ads except when they are within my own research group. But this one is close to my research interests, and I’d like to help the institution find someone good for the role, so I’m making an exception. It is a position for ... [Read more...]

There are six places left for the forecasting workshop I am giving in Switzerland in June. If you were thinking of going, book in fast! [Read more...]