Keywords: Model visualisation, model exploration, structure visualisation, grammar of model visualisation
The
ggplot2 (Wickham 2009) package changed the way how we approach to data visualisation. Instead of looking for suitable type of a plot out of dozens of predefined templates now we express the relation among variables with a well defined grammar based on the excellent book
The Grammar of Graphics (Wilkinson 2006).
Similar revolution is happening with tools for visualisation of statistical models. In the
CRAN repository, one may find a lot of great packages that graphically explain a structure or diagnostic for some family of statistical models. Just to mention few known and powerful packages:
rms,
forestmodel and
regtools (regression models),
survminer (survival models),
ggRandomForests (random forest based models),
factoextra (multivariate structure exploration),
factorMerger (one-way ANOVA) and many, many others. They are great, but they do not share same logic nor structure.
New packages from the
tidyverse, like
broom (Robinson 2017), creates an opportunity to build an unified interface for model exploration and visualisation for large collection of statistical models. And there is more and more articles that set theoretical foundations for unified grammar of model visualization (see for example Wickham, Cook, and Hofmann 2015).
In this talk I am going to present various approaches to the model visualisation, give an overview of selected existing packages for visualisation of statistical models and discuss proposition for a unified grammar of model visualisation.
References Robinson, David. 2017.
Broom: Convert Statistical Analysis Objects into Tidy Data Frames.
https://CRAN.R-project.org/package=broom.
Wickham, Hadley. 2009.
Ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York.
http://ggplot2.org.
Wickham, Hadley, Dianne Cook, and Heike Hofmann. 2015.
Visualizing Statistical Models: Removing the Blindfold. Statistical Analysis; Data Mining 8(4).
Wilkinson, Leland. 2006.
The Grammar of Graphics. Springer Science & Business Media.
