impute.pa2 {DAPAR} | R Documentation

## Missing values imputation from a `MSnSet` object

### Description

This method is a variation to the function `impute.pa` from the package `imp4p`.

### Usage

    impute.pa2(
      tab,
      conditions,
      q.min = 0,
      q.norm = 3,
      eps = 0,
      distribution = "unif"
    )

### Arguments

`tab` | An object of class `MSnSet`.
`conditions` | A vector of conditions in the dataset
`q.min` | A quantile value of the observed values allowing defining the maximal value which can be generated. This maximal value is defined by the quantile q.min of the observed values distribution minus eps. Default is 0 (the maximal value is the minimum of observed values minus eps).
`q.norm` | A quantile value of a normal distribution allowing defining the minimal value which can be generated. Default is 3 (the minimal value is the maximal value minus qn*median(sd(observed values)) where sd is the standard deviation of a row in a condition).
`eps` | A value allowing defining the maximal value which can be generated. This maximal value is defined by the quantile q.min of the observed values distribution minus eps. Default is 0.
`distribution` | The type of distribution used. Values are unif or beta.

### Value

The object `obj` which has been imputed

### Author(s)

Thomas Burger, Samuel Wieczorek

### Examples

    utils::data(Exp1_R25_pept, package='DAPARdata')
    obj.imp <- wrapper.impute.pa2(Exp1_R25_pept[1:100], distribution="beta")

[Package DAPAR version 1.24.8 Index]