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.
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.