plot.subsample.rfsrc: Plot Subsampled VIMP Confidence Intervals

In randomForestSRC: Fast Unified Random Forests for Survival, Regression, and Classification (RF-SRC)

Plot Subsampled VIMP Confidence Intervals

Description

Plots VIMP (variable importance) confidence regions obtained from subsampling a forest.

Usage

## S3 method for class 'rfsrc'
plot.subsample(x, alpha = .01, xvar.names,
 standardize = TRUE, normal = TRUE, jknife = FALSE, target, m.target = NULL,
 pmax = 75, main = "", sorted = TRUE, show.plots = TRUE, ...)

Arguments

x	An object obtained from calling subample.
alpha	Desired level of significance.
xvar.names	Names of the x-variables to be used. If not specified all variables used.
standardize	Standardize VIMP? For regression families, VIMP is standardized by dividing by the variance. For all other families, VIMP is unaltered.
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.
sorted	Should variables be sorted by importance values?
show.plots	Should plots be displayed? Allows users to produce their own custom plots.
...	Further arguments that can be passed to bxp.

Details

Most of the options used by the R function bxp will work here and can be used for customization of plots. Currently the following parameters will work:

"xaxt", "yaxt", "las", "cex.axis", "col.axis", "cex.main", "col.main", "sub", "cex.sub", "col.sub", "ylab", "cex.lab", "col.lab"

Value

Invisibly, returns the boxplot data that is plotted.

Author(s)

Hemant Ishwaran and Udaya B. Kogalur

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.

See Also

subsample.rfsrc

Examples

o <- rfsrc(Ozone ~ ., airquality)
oo <- subsample(o)
plot.subsample(oo)
plot.subsample(oo, xvar.names = o$xvar.names[1:3])
plot.subsample(oo, jknife = FALSE)
plot.subsample(oo, alpha = .01)
plot(oo,cex.axis=.5)

randomForestSRC documentation built on Sept. 11, 2024, 7:50 p.m.