Likelihoods: Likelihood Indices

In synRNASeqNet: Synthetic RNA-Seq Network Generation and Mutual Information Estimates

Description

The Likelihood Indices accomodate both sensitivity and specificity, but treat them separately.

Usage

Likelihoods(resTable)

Arguments

resTable

the data.frame generated from the performanceNET (or one of the row of the matrix generated from the performanceIndex) function.

Value

The Likelihoods function returns the value of the Likelihood Indices (rho - pos or neg) for a given predicted adjacency matrix.

Author(s)

Luciano Garofano [e-mail], Stefano Maria Pagnotta, Michele Ceccarelli

References

Sokolova M., Japkowicz N., Szpakowicz S. (2006). Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation. Lecture Notes in Computer Science Volume 4304, 2006, pp 1015-1021.

See Also

YoudenIndex, DiscriminantPower

Examples

simData <- simulatedData(p = 10, n = 20, mu = 100, sigma = 0.25,
                        ppower = 0.73, noise = FALSE)
counts <- simData$counts
adjMat <- simData$adjMat

miML <- parMIEstimate(counts, method = "ML", unit = "nat", nchips = 2)
miML <- aracne.a(miML, eps = 0.5)

valML <- performanceNET(miML, adjMat)
LH <- Likelihoods(valML)

synRNASeqNet documentation built on May 2, 2019, 6:01 a.m.