R: Imputing missing values using Random Forest.

impute.RF {imp4p} | R Documentation

## Imputing missing values using Random Forest.

### Description

Imputing missing values using the algorithm proposed by Stekhoven and Buehlmann (2012). The function is based on the missForest function of the R package missForest.

### Usage

    impute.RF(tab, conditions,
                        maxiter = 10, ntree = 100, variablewise = FALSE,
                        decreasing = FALSE, verbose = FALSE,
                        mtry = floor(sqrt(ncol(tab))), replace = TRUE,
                        classwt = NULL, cutoff = NULL, strata = NULL,
                        sampsize = NULL, nodesize = NULL, maxnodes = NULL,
                        xtrue = NA, parallelize = c('no', 'variables', 'forests'))

### Arguments

`tab` | A data matrix containing numeric and missing values. Each column of this matrix is assumed to correspond to an experimental sample, and each row to an identified peptide.
`conditions` | A vector of factors indicating the biological condition to which each sample belongs.
`maxiter` | parameter of the `missForest` function (missForest R package).
`ntree` | parameter of the `missForest` function (missForest R package).
`variablewise` | parameter of the `missForest` function (missForest R package).
`decreasing` | parameter of the `missForest` function (missForest R package).
`verbose` | parameter of the `missForest` function (missForest R package).
`mtry` | parameter of the `missForest` function (missForest R package).
`replace` | parameter of the `missForest` function (missForest R package).
`classwt` | parameter of the `missForest` function (missForest R package).
`cutoff` | parameter of the `missForest` function (missForest R package).
`strata` | parameter of the `missForest` function (missForest R package).
`sampsize` | parameter of the `missForest` function (missForest R package).
`nodesize` | parameter of the `missForest` function (missForest R package).
`maxnodes` | parameter of the `missForest` function (missForest R package).
`xtrue` | parameter of the `missForest` function (missForest R package).
`parallelize` | parameter of the `missForest` function (missForest R package).

### Details

See Stekhoven and Buehlmann (2012) for the theory. It is built from functions proposed in the R package missForest.

### Value

The input matrix `tab` with imputed values instead of missing values.

### Author(s)

Quentin Giai Gianetto <quentin2g@yahoo.fr>

### 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

    #Simulating data
    res.sim=sim.data(nb.pept=2000,nb.miss=600,nb.cond=2);

    #Imputation of missing values with Random Forest
    dat.rf=impute.RF(tab=res.sim$dat.obs,conditions=res.sim$condition);

[Package imp4p version 1.2 Index]