Better variable importance indices

[bonStats]

Could potentially use Sobol indices: https://arxiv.org/abs/2005.13622

There is an implementation of this method here: https://bitbucket.org/mpratola/openbt/src/master/

https://bitbucket.org/mpratola/openbt/src/master/src/sobol.cpp

This method does not require refitting the BART mdoels

[bonStats]

bartMachine currently has built in covariate and interaction importance: https://github.com/kapelner/bartMachine/blob/master/bartMachine/R/bart_package_variable_selection.R based on https://arxiv.org/abs/1310.4887

[bonStats]

https://arxiv.org/abs/2108.04310 interaction visualisations

[bonStats]

https://arxiv.org/abs/2210.11391 more variable importance work

[schelhorn]

See also Alan's new {bartMan} package (especially the variable importance section a the the end of the vignette) as well as the 2021 paper from the same author "Visualizations for Bayesian Additive Regression Trees" that also covers variable importance metrics.