AggregatePenalty {GeneSelector} | R Documentation

## aggregation of repeated rankings by a variance penalty

### Description

The idea behind this form of aggregation is to find 'reliable' candidate genes, i.e. those ones that are highly ranked and little variable at the same time. Higher variability is stronger penalized.

### Usage

    AggregatePenalty(RR, lambda = NULL, k=5, theta = 50,
                         estimator = c("var", "mad", "iqr", "residuals"), ...)

### Arguments

`RR` | An object of class `RepeatRanking`.
`lambda` | A positive real number, quantifying the amount of variance penalty. Default is `NULL`, an alternative parametrization using `k` and `theta` is used.
`k` | Must be specified combined with `theta`, s.below. Not used if `lambda` is given.
`theta` | A pragmatic way of finding an appropriate value for `lambda` is to define some threshold rank `theta` that is still considered relevant and some `k >= 1` that expresses the impprtance of the first rank as compared to the threshold rank.
`estimator` | The variance estimator to be used: "var" The usual variance estimator. "mad" Squared median absolute deviation. "iqr" Interquartile range. "residuals" Residuals from a multivariate regression, s. StabilityLm
`...` | Further arguments passed to variance,RepeatRanking-method.

### Value

An object of class AggregatedRanking.

### Author(s)

Martin Slawski martin.slawski@campus.lmu.de
Anne-Laure Boulesteix http://www.slcmsr.net/boulesteix

### See Also

AggregateSimple, AggregateBayes, AggregatePenalty, AggregatePCA

[Package GeneSelector version 1.4.0 Index]