Hierarchical consensus calculation without calibration.
simpleHierarchicalConsensusCalculation(individualData, consensusTree, level = 1)Individual data from which the consensus is to be calculated. It can be either a list or a
multiData structure. Each element in individulData should be a numeric
object (vector, matrix or array).
A list specifying the consensus calculation. See details.
Integer which the user should leave at 1. This serves to keep default set names unique.
A list with a single component consensus, containing the consensus data of the same dimensions as the
individual entries in the input individualData. This perhaps somewhat cumbersome convention is used to
make the output compatible with that of hierarchicalConsensusCalculation.
This function calculates consensus in a hierarchical manner, using a separate (and possibly different) set of
consensus options at each step. The "recipe" for the consensus calculation is supplied in the argument
consensusTree.
The argument consensusTree should have the following components: (1) inputs must be either a
character vector whose components match names(inputData), or consensus trees in the own right.
(2) consensusOptions must be a list of class "ConsensusOptions" that specifies options for
calculating the consensus. A suitable set of options can be obtained by calling
newConsensusOptions. (3) Optionally, the component analysisName can be a single
character string giving the name for the analysis. When intermediate results are returned, they are returned
in a list whose names will be set from analysisName components, if they exist.
Unlike the similar function hierarchicalConsensusCalculation, this function ignores the
calibration settings in the consensusOptions component of consensusTree; no calibration of
input data is performed.
The actual consensus calculation at each level of the consensus tree
is carried out in function simpleConsensusCalculation. The consensus options for each individual
consensus calculation are independent from one another, i.e., the consensus options for different steps can
be different.
simpleConsensusCalculation for a "single-level" consensus calculation;
hierarchicalConsensusCalculation for hierarchical consensus calculation with calibration