divergence.Renyi: Renyi divergence

In MEET: MEET: Motif Elements Estimation Toolkit

Description

This function calculates parametric divergence (Renyi Order different 1)

Usage

divergence.Renyi(training.set, pmX, pmXY, q, correction)

Arguments

training.set	A set of aligned nucleotide sequences
pmX	Relative frequency of a nucleotide at a motif position (position independency model) as an estimation of the probability of this fact.
pmXY	To extend to pmX to include of correlated positions (position dependency model)
q	Renyi Order
correction	Correction of the Finite Sample Size Effect

Author(s)

Joan Maynou <[e-mail]>

See Also

divergence.Shannon, PredictDivergence

Examples

data(TranscriptionFactor)
data(BackgroundOrganism)
data(RenyiOrder)
data(iicc)
q<-0.5
training.set<-TranscriptionFactor
correction<-correction.entropy(q,p=nrow(training.set),long=1,iicc)
HXmax<-iicc$HXmax
pmX<-probability(training.set,Prob,missing.fun=TRUE)
prob_parella<-probability.couple(Prob)
pmXY<-joint.probability(training.set, Prob, prob_parella)
HXY<-entropy.joint(pmXY,q,iicc)
divergence.Renyi(training.set,pmX,pmXY,q,correction)

MEET documentation built on May 2, 2019, 5:52 p.m.