Description Usage Arguments Details Author(s) See Also Examples
This function calculates Mutual Information (Renyi Order equal 1) by means of Kullback-Leibler divergence
1 | divergence.Shannon(training.set, H, HXY,correction)
|
training.set |
A set of aligned nucleotide sequences |
H |
Entropy |
HXY |
Joint Entropy |
correction |
Correction of the Finite Sample Size Effect |
Renyi Order has to be equal 1.
Joan Maynou <joan.maynouatupc.edu>
divergence.Renyi, PredictDivergence, kfold.divergence
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | require("MEET")
data(TranscriptionFactor)
data(BackgroundOrganism)
data(iicc)
q<-1
training.set<-TranscriptionFactor
correction<-correction.entropy(q,p=nrow(training.set),long=1,iicc)
HXmax<-entropy.Shannon(as.matrix(Prob))
pmX<-probability(training.set,Prob)
Probtrans<-probability.couple(Prob)
H<-entropy.Shannon(pmX)
pmXY<-joint.probability(training.set, Prob, Probtrans)
HXY<-entropy.joint(pmXY,q,iicc)
divergence.Shannon(training.set,H,HXY,correction)
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