Blog Archives

Software for honours students

April 4, 2017
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I spoke to our new crop of honours students this morning. Here are my slides, example files and links.   Managing References Mendeley Zotero Paperpile Data analysis and computation Download R Download Rstudio Online R tutorial R packages for time series R packages for econometrics R packages for finance Writing your thesis LaTeX Windows: Download MikTeX

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Follow-up forecasting forum in Eindhoven

March 7, 2017
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Last October I gave a 3-day masterclass on “Forecasting with R” in Eindhoven, Netherlands. There is a follow-up event planned for Tuesday 18 April 2017. It is particularly designed for people who attended the 3-day class, but if anyone else wants to attend they would be welcome. Please register here if you want to attend. The preliminary

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forecast 8.0

February 28, 2017
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forecast 8.0

In what is now a roughly annual event, the forecast package has been updated on CRAN with a new version, this time 8.0. A few of the more important new features are described below. Check residuals A common task when building forecasting models is to check that the residuals satisfy some assumptions (that they are

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Simulating from a specified seasonal ARIMA model

January 26, 2017
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From my email today You use an illustration of a seasonal arima model: ARIMA(1,1,1)(1,1,1)4 I would like to simulate data from this process then fit a model… but I am unable to find any information as to how this can be conducted… if I set phi1, Phi1, theta1, and Theta1 it would be reassuring that

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Cross-validation for time series

December 5, 2016
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Cross-validation for time series

I’ve added a couple of new functions to the forecast package for R which implement two types of cross-validation for time series. K-fold cross-validation for autoregression The first is regular k-fold cross-validation for autoregressive models. Although cross-validation is sometimes not valid for time series models, it does work for autoregressions, which includes many machine learning

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Q&A time

October 23, 2016
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Someone sent me some questions by email, and I decided to answer some of them here. How important is it that I know and understand the underlying mathematical framework to forecasting methods? I understand conceptually how most of them work, but I feel as if I may benefit from truly understanding the math. The main benefit

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Tourism forecasting competition data as an R package

October 22, 2016
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The data used in the tourism forecasting competition, discussed in Athanasopoulos et al (2011), have been made available in the Tcomp package for R. The objects are of the same format as for Mcomp package containing data from the M1 and M3 competitions. Thanks to Peter Ellis for putting the package together. He has also

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Hadley Wickham Master R Developer course coming to Melbourne

October 5, 2016
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Hadley Wickham’s popular R developer course is coming to Melbourne on 12-13 December 2016. Bookings can be made via Eventbrite. Hadley, of course, is the developer of the wonderful tidyverse set of R packages including ggplot2, dplyr, tidyr, readr, purrr, tibble, and many more. He is the author of several books including the new “R for

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RStudio just keeps getting better

December 10, 2015
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RStudio has been a life-changer for the way I work, and for how I teach data analysis. I still have a couple of minor frustrations with it, but they are slowly disappearing as RStudio adds features. I use dual monitors and I like to code on one monitor and have the console and plots on

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Who’s downloading the forecast package?

December 9, 2015
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Who’s downloading the forecast package?

The github page for the forecast package currently shows the following information Note the downloads figure: 264K/month. I know the package is popular, but that seems crazy. Also, the downloads figure on github only counts the downloads from the RStudio mirror, and ignores downloads from the other 125 mirrors around the world. Here are the

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