Hi! Thanks for visiting my web site. If you find anything useful, please tell me. If you would suggest improvements, please make an issue on the github repo. The bio below and photo can be used for media releases without additional permission.
Dianne Cook is Professor of Business Analytics at Monash University in
Melbourne, Australia. Her research is in the area of data visualisation, especially the visualisation of high-dimensional data using tours with low-dimensional projections, and projection pursuit. A current focus is on bridging the gap between exploratory graphics and statistical inference. Technology plays an important role in data visualisation for evaluating effectiveness and for public consumption. Di utilises technology such as virtual environments, Amazon’s Mechanical Turk, and eye-tracking in her work, and makes an effort to share her work with open source software. Di is a Fellow of the American Statistical Association, elected member of the International Statistical Institute, past-editor of the Journal of Computational and Graphical Statistics, elected Member of the R Foundation, and current editor of the R Journal. Education is an important part of her contributions, and mentoring graduate research is a significant activity. Several of her students have won the prestigious American Statistical Association John Chambers Software Award, including Hadley Wickham, Yihui Xie, Carson Sievert, and most recently, Monash student Earo Wang.
Note: Di was a professor at Iowa State University from 1993-2015. She is listed as emeritus on that faculty web site and on wikipedia. This status was only requested because this made it possible to continue to supervise her graduate students after the move to Monash. She is not retired! Iowa State University has an amazingly long history of statistics research, and the department is broadly connected to other departments on campus, with an active and supported consulting mission, in parallel to core research. This rich environment led to successfully fostering statistical graphics research, which continues to have a very active group of faculty and students.
Interests
Interactive data visualisation
Exploratory data analysis
High-dimensional spaces
Statistical graphics
Statistical computing
Bioinformatics
Sports
Ecology
Environment
Open source
Open data
Education
PhD in Statistics, 1993
Rutgers University
MS in Statistics, 1991
Rutgers University
BSc/Dip Ed in Mathematics, Statistics and Biochemistry, 1982
In 1997, I wrote a paper that was accepted for the newly fledged Journal of Statistical Software. That article is still available at https://www.jstatsoft.org/article/view/v002i06. It looks nothing like the original published paper. Papers today are only published in pdf format, unlike the original which were delivered as html, with pdf being a secondary format o help readers who preferred a printed copy.
My paper was titled “Calibrate your to Recognise High-Dimensional Shapes from their Low-Dimensional Projections”.
Multicollinearity This was one of the comments from a recent review of a paper:
As you note in the paper, it seems likely that there are still issues with multi-collinearity
Multicollinearity means that the observations are co-linear in some combination of the variables. This has been relaxed in practice to mean substantial association between explanatory variables. When your explanatory variables have substantial association between them, it means that you don’t have a stable base on which to build a model.
useR! 2018 was held for the first time in the southern hemisphere, and the feedback from participants has been very positive. I have been asked to write about the organisation and this is a good way to get some of the planning and decisions and operations into print, so that it might be useful for others charged with conference organisation. There are a lot of people who made the conference a success, and their contributions need to be acknowledged.
Goal I just gave a short talk at ISCB-ASC 2018 about visualising high-dimensional data, which involves showing dynamic graphics. In the past, I have run the tour, captured the window and saved to a movie, and embedded this into the Rmarkdown xaringan slides. It seems a bit discombobulated to make the slides this way, and a better way to work would be to make a tour animation using plotly. This turned out to take me two days to get it working, through little mistakes that were not easy to debug by googling the problem.
Download your data You can get access to your own electricity and gas usage data from https://www.citipower.com.au/our-services/myenergy. You will need a copy of your power bill, which has your smart meter number and meter id, to register for an account.
Reading the data The data structure is described here.
The data is not especially nicely formatted (surprise). The main components are:
The time resolution is half-hourly. And values for each day are spread across the columns.
Non-Uniform Monash Business Analytics Team: This is a research working group consisting of facutly, post-docs and students in Econometrics and Business Statistics at Monash University. The group meets regularly to discuss current research and host visitors talking to the group. If you would like to visit and present your work to the group, send email numbats@googlegroups.com.
The conference useR! 2018 will be held in Australia July 10-13, at the Brisbane Convention and Exhibition Centre. This is the first time that it has been held outside Europe or North America.
