kfold.Entropy:
Leave-one-out cross-validation for Renyi entropy (ITEME)
Description
Given a training sequence set, the optimal value for Renyi entropy has been estimated by means of leave-one-out cross-validation from q-value set. For each q-value, the ROC curve has been calculated. From this results, the optimal q-value has been considered according to the area under convex surface maximum.
Usage
kfold.Entropy(iicc, TF)
Arguments
iicc
A set of inicial conditions for the MEET-package (mode, method, background, alignment, threshold, parameters, Transcriptionfactor, nummotif, lenmotif, sentit, position, missing, vector, gapopen, maxiters, gapextend)
TF
A set of nucleotide sequences
Details
This function integrates the Shannon entropy for Renyi Order equal 1. Moreover, it contains a set of function for the detection of transcription factor binding sites:correction.entropy.R, correction.redundancy.R, entropy.Shannon.R,entropy.Renyi.R, entropy.corrected.R, probability.R, CalculRedundancy.R, diff.instructions.R, redundancy.R, ROCmodel.R, detector_1rOrdre_diff.R, pvalue.R.
See Also
kfold.Divergence, kfold.MEME, kfold.MDscan, kfold.MATCH and kfold.PCA