Nothing
corr.sim <-
function(n.grp, # Vector with number of subjects per group
rdist, # rdist matrix
dist.param1, # dist.param1
dist.param2, # dist.param2
slope,
test.specs,
ebp.def,
keep.res, # names of result items to keep
nreps=10)
{
# Initialize result list
res<-vector("list",6+length(keep.res))
names(res)<-c("test.specs","ebp.def","slope","rdist","dist.param1","dist.param2",keep.res)
res$test.specs<-test.specs
res$ebp.def<-ebp.def
res$rdist<-rdist
res$dist.param1<-dist.param1
res$dist.param2<-dist.param2
res$slope<-slope
ngenes<-max(dim(rdist)[1],dim(dist.param1)[1],dim(dist.param2)[1])
for (i in 6+1:length(keep.res)) res[[i]]<-matrix(NA,ngenes,nreps)
# Now perform simulation
for (i in 1:nreps) # Loop over sim reps
{
ex.set<-generate.corr.data(n.grp,rdist,dist.param1,dist.param2,slope) # Generate a data set
sim.res<-hybrid.test(ex.set,test.specs,ebp.def) # Apply the method
for (j in 1:length(keep.res)) # Store results in result list object
{
res[[keep.res[j]]][,i]<-sim.res[,keep.res[j]]
}
}
return(res) # Return results
}
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