Rmarkdown templates for staff and students in my department are now available on github. For a thesis, fork the repository MonashThesis.
For other templates, install the R package MonashEBSTemplates R package. This provides templates for
- beamer slides
- working papers
This is only directly relevant to my Monash students and colleagues, but the same idea might be useful for adapting to other institutions.
Some recent changes in the rmarkdown and bookdown packages mean that it is now possible to produce working papers in exactly the same format as we previously used with LaTeX.Just install the MonashEBSTemplates package from github. You also need a recent version of LaTeX.
Then from within RStudio, create a new document by selecting “Rmarkdown”, “From Template”, and select “Monash EBS Working Paper”.
I’ve been having discussions with colleagues and university administration about the best way for universities to manage home-grown software.
The traditional business model for software is that we build software and sell it to everyone willing to pay. Very often, that leads to a software company spin-off that has little or nothing to do with the university that nurtured the development. Think MATLAB, S-Plus, Minitab, SAS and SPSS, all of which grew out of universities or research institutions.
One of my PhD students, Thilaksha Tharanganie, has been very successful in getting travel funding to attend conferences. She was the subject of a write-up in today’s Monash News.
We encourage students to attend conferences, and provide funding for them to attend one international conference and one local conference during their PhD candidature. Thilaksha was previously funded to attend last year’s COMPSTAT in Geneva, Switzerland and IMS conference in Sydney. Having exhausted local funding, she has now convinced several other organizations to support her conference habit.
One of the first things I tell my new research students is to use a reference management system to help them keep track of the papers they read, and to assist in creating bib files for their bibliography. Most of them use Mendeley, one or two use Zotero. Both do a good job and both are free.
I use neither. I did use Mendeley for several years, but it became slower and slower to sync as my reference collection grew.
I’m delighted that Professor Dianne Cook will be joining Monash University in July 2015 as a Professor of Business Analytics. Di is an Australian who has worked in the US for the past 25 years, mostly at Iowa State University. She is moving back to Australia and joining the Department of Econometrics and Business Statistics in the Monash Business School, as part of our initiative in Business Analytics.
Di is a world leader in data visualization, and is well-known for her work on interactive graphics.
Souhaib Ben Taieb has been awarded his doctorate at the Université libre de Bruxelles and so he is now officially Dr Ben Taieb! Although Souhaib lives in Brussels, and was a student at the Université libre de Bruxelles, I co-supervised his doctorate (along with Professor Gianluca Bontempi). Souhaib is the 19th PhD student of mine to graduate.
His thesis was on “Machine learning strategies for multi-step-ahead time series forecasting” and is now available online.
Next week, Professor Di Cook from Iowa State University is visiting my research group at Monash University. Di is a world leader in data visualization, and is especially well-known for her work on interactive graphics and the XGobi and GGobi software. See her book with Deb Swayne for details.
For those wanting to hear her speak, read on.Research seminar She will be giving a seminar at 2pm on Monday 18 August at the Monash Clayton campus (Rm E457, Menzies Building 11).
Last week my research group discussed Hal Varian’s interesting new paper on “Big data: new tricks for econometrics”, Journal of Economic Perspectives, 28(2): 3-28.
It’s a nice introduction to trees, bagging and forests, plus a very brief entree to the LASSO and the elastic net, and to slab and spike regression. Not enough to be able to use them, but ok if you’ve no idea what they are. It was more disappointing on boosting (completely ignoring the fact that boosting can be applied in a regression context as well as a classification context), and his comments on causality seemed curiously naive.
Last week, my research group discussed Galit Shmueli’s paper “To explain or to predict?”, Statistical Science, 25(3), 289-310. (See her website for further materials.) This is a paper everyone doing statistics and econometrics should read as it helps to clarify a distinction that is often blurred. In the discussion, the following issues were covered amongst other things.
The AIC is better suited to model selection for prediction as it is asymptotically equivalent to leave-one-out cross-validation in regression, or one-step-cross-validation in time series.