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]