plot.abcrf: Plot of an ABC-RF object

In abcrf: Approximate Bayesian Computation via Random Forests

Plot of an ABC-RF object

Description

plot.abcrf provides both a variable importance plot of a model choice ABC-RF object and the projection of the reference table on the LDA axes.

Usage

## S3 method for class 'abcrf'
plot(x, training, obs=NULL, n.var=20, pdf=FALSE, xlim=NULL, ...)

Arguments

x	an abcrf object.
training	the data frame containing the reference table used to train the abcrf object.
obs	a vector containing the summary statistics of an observed dataset that will be added to the graph of the projected reference table (black star or vertical line).
n.var	number of variables in the variable importance representation.
pdf	a boolean that indicates if a pdf version of the graph(s) should be saved in the current directory.
xlim	range of the abscissa for the variable importance plot.
...	not used.

Note

The graph of the reference table projected on the LD axes is shown only if LD axes has been added to the set of summary statistics in the call of abcrf.

References

Pudlo P., Marin J.-M., Estoup A., Cornuet J.-M., Gautier M. and Robert, C. P. (2016) Reliable ABC model choice via random forests Bioinformatics doi: 10.1093/bioinformatics/btv684

See Also

abcrf, predict.abcrf, err.abcrf, variableImpPlot

Examples

data(snp)
modindex <- snp$modindex[1:500]
sumsta <- snp$sumsta[1:500,]
data1 <- data.frame(modindex, sumsta)
model.rf <- abcrf(modindex~., data1, ntree=100)
plot(model.rf, data1)
data(snp.obs)
plot(model.rf, data1, obs=snp.obs[1,])

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