# dI: Lower bound for the number of true discoveries In angeella/ARIpermutation: Permutation-Based All-Resolutions Inference Method

## Description

Calculates (1-alpha) lower confidence bounds for the set-wise of false null hypotheses.

## Usage

 1 dI(ix, cv, pvalues, iterative, approx, ncomb, ...)

## Arguments

 ix numeric vector. It refers to the set-wise hypotheses considered. cv numeric vector. It refers to the critical vector computed by criticalVector. pvalues matrix of pvalues with dimensions m \times B. iterative Boolean value. If iterative = TRUE, the iterative method for improvement of confidence envelopes is applied. Default @FALSE. approx Boolean value. Default @TRUE. If you are treating high dimensional data, we suggest to put approx = TRUE to speed up the computation time. Default @TRUE ncomb Numeric value. If approx = TRUE, you must decide how many random subcollections (level of approximation) considered. Default 100. ... further arguments for the iterative approach, i.e., iterative = TRUE.

## Value

numeric value: the lower confidence bound for the number of true discoveries concerning the cluster ix specified.

Angela Andreella

## Examples

 1 2 3 4 5 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)

angeella/ARIpermutation documentation built on Nov. 25, 2021, 9:23 a.m.