Standardize VIMP? For regression families, VIMP is
standardized by dividing by the variance and then multipled by 100.
For all other families, VIMP is scaled by 100.
normal
Use parametric normal confidence regions or
nonparametric regions? Generally, parametric regions perform better.
jknife
Use the delete-d jackknife variance estimator?
target
For classification families, an integer or
character value specifying the class VIMP will be conditioned on
(default is to use unconditional VIMP).
For competing risk families, an integer value between
1 and J indicating the event VIMP is requested, where J is
the number of event types. The default is to use the first event.
m.target
Character value for multivariate families
specifying the target outcome to be used. If left unspecified, the
algorithm will choose a default target.
pmax
Trims the data to this number of variables (sorted by VIMP).
main
Title used for plot.
cex
Character expansion used for variable names.
...
Further arguments that can be passed to bxp.
References
Ishwaran H. and Lu M. (2017). Standard errors and confidence
intervals for variable importance in random forest regression,
classification, and survival.
Politis, D.N. and Romano, J.P. (1994). Large sample confidence
regions based on subsamples under minimal assumptions. The
Annals of Statistics, 22(4):2031-2050.
Shao, J. and Wu, C.J. (1989). A general theory for jackknife variance
estimation. The Annals of Statistics, 17(3):1176-1197.