impute.randomForest,proFIAset-method {proFIA}R Documentation

Fill missing values in the peak table using random forest.

Description

Impute the missing values in an FIA experiment using a random forest implemented in the missForest package.

Usage

## S4 method for signature 'proFIAset'
impute.randomForest(object, parallel = FALSE, ...)

Arguments

object

A proFIAset object.

parallel

Shall parallelism be used.

...

supplementary arguements to be passed to missForest function.

Value

A proFIAset object with the missing values imputated.

References

Stekhoven, D.J. and Buehlmann, P. (2012), 'MissForest - nonparametric missing value imputation for mixed-type data', Bioinformatics, 28(1) 2012, 112-118, doi: 10.1093/bioinformatics/btr597

Examples

if(require(plasFIA)){
    data(plasSet)
    ###Reinitializing the data matrix
    plasSet<-makeDataMatrix(plasSet,maxo=FALSE)
    plasSet<-impute.randomForest(plasSet)
}

[Package proFIA version 1.6.0 Index]