wrapper.dapar.impute.mi {DAPAR} | R Documentation

## Missing values imputation using the LSimpute algorithm.

### Description

This method is a wrapper to the function `impute.mi` of the package `imp4p` adapted to an object of class `MSnSet`.

### Usage

    wrapper.dapar.impute.mi(obj, nb.iter = 3, nknn = 15, selec = 600,
      siz = 500, weight = 1, ind.comp = 1, progress.bar = TRUE,
      x.step.mod = 300, x.step.pi = 300, nb.rei = 100, method = 4,
      gridsize = 300, q = 0.95, q.min = 0, q.norm = 3, eps = 0,
      methodi = "slsa", lapala = TRUE, distribution = "unif")

### Arguments

`obj` | An object of class `MSnSet`.
`nb.iter` | Same as the function `mi.mix` in the package `imp4p`
`nknn` | Same as the function `mi.mix` in the package `imp4p`
`selec` | Same as the function `mi.mix` in the package `imp4p`
`siz` | Same as the function `mi.mix` in the package `imp4p`
`weight` | Same as the function `mi.mix` in the package `imp4p`
`ind.comp` | Same as the function `mi.mix` in the package `imp4p`
`progress.bar` | Same as the function `mi.mix` in the package `imp4p`
`x.step.mod` | Same as the function `estim.mix` in the package `imp4p`
`x.step.pi` | Same as the function `estim.mix` in the package `imp4p`
`nb.rei` | Same as the function `estim.mix` in the package `imp4p`
`method` | Same as the function `estim.mix` in the package `imp4p`
`gridsize` | Same as the function `estim.mix` in the package `imp4p`
`q` | Same as the function `mi.mix` in the package `imp4p`
`q.min` | Same as the function `impute.pa` in the package `imp4p`
`q.norm` | Same as the function `impute.pa` in the package `imp4p`
`eps` | Same as the function `impute.pa` in the package `imp4p`
`methodi` | Same as the function `mi.mix` in the package `imp4p`
`lapala` | xxxxxxxxxxx
`distribution` | The type of distribution used. Values are `unif` (default) or `beta`.

### Value

The `exprs(obj)` matrix with imputed values instead of missing values.

### Author(s)

Samuel Wieczorek

### Examples

    require(DAPARdata)
    data(Exp1_R25_pept)
    dat <- mvFilter(Exp1_R25_pept[1:1000], type="allCond", th = 1)
    dat <- wrapper.dapar.impute.mi(dat, nb.iter=1)

[Package DAPAR version 1.16.11 Index]