plot.regAbcrf {abcrf} | R Documentation |
Plot of a reg-ABC-RF object
Description
plot.regAbcrf
provides a variable importance plot used to construct the reg-ABC-RF object, as measured by ranger
with the argument importance='impurity'.
Usage
## S3 method for class 'regAbcrf'
plot(x, n.var=min(30, length(x$model.rf$variable.importance)), xlim=NULL, main=NULL, ...)
Arguments
x |
a |
n.var |
number of variables in the variable importance representation. The default value is equal to the minimum between 30 and the number of summary statistics. |
xlim |
range of the abscissa for the variable importance plot. |
main |
an overall title for the variable importance plot. |
... |
not used. |
References
Raynal L., Marin J.-M. Pudlo P., Ribatet M., Robert C. P. and Estoup, A. (2019) ABC random forests for Bayesian parameter inference Bioinformatics doi:bioinformatics/bty867
See Also
regAbcrf
,
predict.regAbcrf
,
err.regAbcrf
,
covRegAbcrf
,
ranger
,
densityPlot
Examples
data(snp)
modindex <- snp$modindex
sumsta <- snp$sumsta[modindex == "3",]
r <- snp$param$r[modindex == "3"]
r <- r[1:500]
sumsta <- sumsta[1:500,]
data2 <- data.frame(r, sumsta)
model.rf.r <- regAbcrf(r~., data2, ntree=100)
plot(model.rf.r)
[Package abcrf version 1.9 Index]