AggregatePenalty {GeneSelector} | R Documentation |
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.
AggregatePenalty(RR, dispersion = c("sd", "mad", "iqr"), center = NULL, gamma = 0.05,...)
RR |
An object of class |
dispersion |
The dispersion measure to be used (s. dispersion):
|
center |
Optional numeric vector specifying for each gene the rank serving as center/location parameter for |
gamma |
As basis of the aggregated ranking, the quantity |
... |
Further arguments passed to dispersion. |
An object of class AggregatedRanking.
Martin Slawski
Anne-Laure Boulesteix
RepeatRanking, AggregateSimple, AggregateSVD, AggregateMC
## 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)