abcrf (version 1.9)

plot.regAbcrf: 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 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 tools:::Rd_expr_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)