AggregatePenalty {GeneSelector} | R Documentation |
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.
AggregatePenalty(RR, lambda = NULL, k=5, theta = 50, estimator = c("var", "mad", "iqr", "residuals"), ...)
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:
|
... |
Further arguments passed to variance,RepeatRanking-method. |
An object of class AggregatedRanking.
Martin Slawski martin.slawski@campus.lmu.de
Anne-Laure Boulesteix http://www.slcmsr.net/boulesteix
AggregateSimple, AggregateBayes, AggregatePenalty, AggregatePCA