Description Usage Arguments Value Author(s) References See Also Examples
This function inputs the estimated quantities obtained from
errDisc
(EFD, EMD, EFDR, EMDR) and outputs
the non-overlapping sets (atoms) in the Bayes estimator.
1 2 3 |
EFD.EMD |
Matrix with estimated EFD, EMD, EFDR, EMDR for each of the
non-overlapping sets (atoms) in the Bayes estimator
(output of the |
w |
Value of threshold used to determine whether or not an atom is in the Bayes estimator. |
type |
Either |
pen.for.feats |
Penalty for the number of features in the Bayes estimator. |
pen.for.atoms |
Penalty for the number of atoms in the Bayes estimator. |
atom.sizes |
Vector of the number of genes in each atom. |
ilim |
Number of iterations performs to obtain Bayes estimator in ratio case. |
verbose |
If |
Vector of the atoms in the Bayes estimator.
Hector Corrada Bravo, Simina M. Boca, Jeffrey T. Leek
Boca S.M., H. Corrada Bravo, B. Caffo, J.T. Leek, and G. Parmigiani (2010): A decision-theory approach to interpretable set analysis for high-dimensional data, JHU Biostat Working Paper 211, http://www.bepress.com/jhubiostat/paper211/
postProb, errDisc
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 | ##first obtain estimates of the gene-level posterior probabilities
data(GenderStats)
data(ChromSets)
gene.stat <- (gene.stat - mean(gene.stat))/sd(gene.stat)
set.seed(70790707)
post.prob.genes <- postProb(gene.stat, null = rnorm(20 * length(gene.stat),
+ 0, 1), K = length(gene.stat))
##now run errDisc function
EFD.EMD.res <- errDisc(sets, post.prob.genes)
head(EFD.EMD.res)
##now get Bayes estimator in various cases
bayesEst(EFD.EMD.res, w = 0.75, type = "count", atom.sizes =
sapply(sets, length))
bayesEst(EFD.EMD.res, w = 0.97, type = "count", atom.sizes =
sapply(sets, length))
bayesEst(EFD.EMD.res, w = 0.75, type = "count", atom.sizes =
sapply(sets, length), pen.for.feats = 0.2)
bayesEst(EFD.EMD.res, w = 0.97, type = "count", atom.sizes =
sapply(sets, length), pen.for.feats = 0.2)
bayesEst(EFD.EMD.res, w = 0.75, type = "count", atom.sizes =
sapply(sets, length), pen.for.atoms = 5)
bayesEst(EFD.EMD.res, w = 0.97, type = "count", atom.sizes =
sapply(sets, length), pen.for.atoms = 5)
bayesEst(EFD.EMD.res, w = 0.75, type = "ratio", atom.sizes =
sapply(sets, length))
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