Nothing
test.Simes <- function() {
m <- matrix(0,nr=4,nc=4)
m[1,3] <- m[2,4] <- m[3,2] <- m[4,1] <- 1
w <- c(1/2, 1/2, 0, 0)
p1 <- c(0.01, 0.005, 0.01, 0.5)
p2 <- c(0.01, 0.005, 0.015, 0.022)
a <- 0.05
g <- matrix2graph(m, w)
result1 <- gMCP(g, pvalues=p1, test="Simes", alpha=a)
result2 <- gMCP(g, pvalues=p2, test="Simes", alpha=a)
checkEquals(unname(result1@rejected), c(TRUE, TRUE, TRUE, FALSE))
checkEquals(unname(result2@rejected), c(TRUE, TRUE, TRUE, TRUE))
}
checkWeights <- function(graph, pvalues) {
# Compares the weights of the gMCP-R-code, gMCP-C-code, power-C-code and parametric-R-code
result <- gMCP(graph, pvalues, keepWeights=FALSE)
rejected <- getRejected(result)
weights <- getWeights(result)
result2 <- gMCP(graph, pvalues, useC=TRUE, keepWeights=FALSE)
rejected2 <- getRejected(result2)
weights2 <- getWeights(result2)
checkEquals(rejected, rejected2)
checkEquals(weights, weights2)
result <- gMCP(graph, pvalues, keepWeights=TRUE)
rejected <- getRejected(result)
weights <- getWeights(result)
result3 <- graphTest(pvalues=pvalues, alpha=0.05, graph=substituteEps(graph))
m3 <- attr(result, "last.G")
weights3 <- attr(result3, "last.alphas") / 0.05
rejected3 <- result3!=0
checkEquals(unname(rejected), unname(rejected3)) # TODO fix naming
#checkEquals(unname(weights), weights3) TODO check why NaNs occur
}
test.checkWeights <- function() {
graphs <- list(BonferroniHolm(5),
parallelGatekeeping(),
improvedParallelGatekeeping(),
BretzEtAl2011(),
#HungEtWang2010(),
#HuqueAloshEtBhore2011(),
HommelEtAl2007(),
HommelEtAl2007Simple(),
MaurerEtAl1995(),
improvedFallbackI(weights=rep(1/3, 3)),
improvedFallbackII(weights=rep(1/3, 3)),
cycleGraph(nodes=paste("H",1:4,sep=""), weights=rep(1/4, 4)),
fixedSequence(5),
fallback(weights=rep(1/4, 4)),
#generalSuccessive(weights = c(1/2, 1/2)),
simpleSuccessiveI(),
simpleSuccessiveII(),
#truncatedHolm(),
BauerEtAl2001(),
BretzEtAl2009a(),
BretzEtAl2009b(),
BretzEtAl2009c()#,
#FerberTimeDose2011(times=5, doses=3, w=1/2),
#Ferber2011(),
#Entangled1Maurer2012(),
#Entangled2Maurer2012(),
)
for (graph in graphs) {
p <- gMCP:::permutations(length(getNodes(graph)))
for (i in 1:(dim(p)[1])) {
pvalues <- p[i,]
pvalues[pvalues==0] <- 0.00001
checkWeights(graph, pvalues)
}
}
}
test.upscale <- function() {
g <- BonferroniHolm(5)
r1 <- gMCP(g, pvalues=c(0.01, 0.02, 0.04, 0.04, 0.7))
# Simple Bonferroni with empty graph:
g2 <- matrix2graph(matrix(0, nrow=5, ncol=5))
r2 <- gMCP(g2, pvalues=c(0.01, 0.02, 0.04, 0.04, 0.7))
# With 'upscale=TRUE' equal to BonferroniHolm:
r3 <- gMCP(g2, pvalues=c(0.01, 0.02, 0.04, 0.04, 0.7), upscale=TRUE)
checkEquals(r1@rejected, r3@rejected)
checkTrue(all(r1@rejected>=r2@rejected)) # FALSE<TRUE
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.