plot.regAbcrf: Plot of a reg-ABC-RF object

In abcrf: Approximate Bayesian Computation via Random Forests

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 regAbcrf object.
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)

abcrf documentation built on Aug. 9, 2022, 5:07 p.m.