dI | R Documentation |
Calculates 1-\alpha
lower confidence bound for the set-wise of false null hypotheses.
dI(ix, cv, pvalues, iterative, approx, ncomb, ...)
ix |
Numeric vector: set-wise hypotheses considered. |
cv |
Numeric vector: critical vector computed by |
pvalues |
If |
iterative |
Boolean value. If |
approx |
Boolean value. Default to |
ncomb |
Numeric value. If |
... |
Further arguments for the iterative approach, i.e., |
Numeric value: the lower confidence bound for the number of true discoveries concerning the cluster ix
specified.
Angela Andreella
Andreella, A., Hemerik, J., Finos, L., Weeda, W., & Goeman, J. (2023). Permutation-based true discovery proportions for functional magnetic resonance imaging cluster analysis. Statistics in Medicine, 42(14), 2311-2340.
db <- simulateData(pi0 = 0.7, m = 100, n = 20, rho = 0)
out <- signTest(X = db)
pv <- cbind(out$pv, out$pv_H0)
cv <- criticalVector(pvalues = pv, family = "simes", lambda = 0.1, alpha = 0.1)
dI(ix = c(1:100), cv = cv, pvalues = pv)
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