AggregatePenalty {GeneSelector} | R Documentation

## Aggregation of repeated rankings using a variance penalty approach

### Description

The idea behind this form of aggregation is to find a compromise between quality on the one hand, represented by the list position/rank, and variability on the other hand. The latter is assessed by calling the function dispersion.

### Usage

    AggregatePenalty(RR, dispersion = c("sd", "mad", "iqr"), center = NULL, gamma = 0.05,...)

### Arguments

`RR` | An object of class `RepeatedRanking`.
`dispersion` | The dispersion measure to be used (s. dispersion): "sd" standard deviation, "mad" median absolute deviation, "iqr" interquartile range.
`center` | Optional numeric vector specifying for each gene the rank serving as center/location parameter for `dispersion`. If `center = NULL`, the reference ranking `RR@original@ranking` is used.
`gamma` | As basis of the aggregated ranking, the quantity `(1-gamma)*center + gamma * dispersion` is used, i.e. the variability aspect dominates as `gamma` tends to one.
`...` | Further arguments passed to dispersion.

### Value

An object of class AggregatedRanking.

### Author(s)

Martin Slawski
Anne-Laure Boulesteix

### See Also

RepeatRanking, AggregateSimple, AggregateSVD, AggregateMC

### Examples

    ## Load toy gene expression data
    data(toydata)
    ### class labels
    yy <- toydata[1,]
    ### gene expression
    xx <- toydata[-1,]
    ### run RankingTstat
    ordT <- RankingTstat(xx, yy, type="unpaired")
    ### Generate Leave-one-out Foldmatrix
    loo <- GenerateFoldMatrix(y = yy, k=1)
    ### Get all rankings
    loor_ordT <- RepeatRanking(ordT, loo)
    ### aggregate rankings
    agg_pen_ordT <- AggregatePenalty(loor_ordT, dispersion = "iqr", gamma = 0.3)
    toplist(agg_pen_ordT)

[Package GeneSelector version 2.30.0 Index]