Nothing
Isoqqstat <- function (x, y, fudge, niter)
{
xiter.index <- t(sapply(1:niter, function(i) sample(x)))
to1 <- to2 <- to3 <- to4 <- to5 <- matrix(0, nrow(y), niter)
fudge.factor <- switch(fudge, pooled = Isofudge(x, y), none = c(rep(0,
5)))
total <- niter
pb <- tkProgressBar(title = "progress bar", min = 0, max = total,
width = 300)
for (i in 1:niter) {
yyy0 <- IsoGenemSAM(xiter.index[i, ], as.matrix(y), fudge.factor)
to1[, i] <- sort(yyy0[[1]])
to2[, i] <- sort(yyy0[[2]])
to3[, i] <- sort(yyy0[[3]])
to4[, i] <- sort(yyy0[[4]])
to5[, i] <- sort(yyy0[[5]])
setTkProgressBar(pb, i, title = paste(round(i/total *
100, 0), "% done"))
}
close(pb)
L <- IsoGenemSAM(x, as.matrix(y), fudge.factor)
d <- L[[1]]
d.sort.list <- sort.list(d)
d.sort <- d[d.sort.list]
perm.mean <- rowMeans(to1)
aa1 = cbind(d.sort, perm.mean, d.sort - perm.mean, d.sort.list)
row.names(aa1) <- row.names(y)[d.sort.list]
d <- L[[2]]
d.sort.list <- sort.list(d)
d.sort <- d[d.sort.list]
perm.mean <- rowMeans(to2)
aa2 = cbind(d.sort, perm.mean, d.sort - perm.mean, d.sort.list)
row.names(aa2) <- row.names(y)[d.sort.list]
d <- L[[3]]
d.sort.list <- sort.list(d)
d.sort <- d[d.sort.list]
perm.mean <- rowMeans(to3)
aa3 = cbind(d.sort, perm.mean, d.sort - perm.mean, d.sort.list)
row.names(aa3) <- row.names(y)[d.sort.list]
d <- L[[4]]
d.sort.list <- sort.list(d)
d.sort <- d[d.sort.list]
perm.mean <- rowMeans(to4)
aa4 = cbind(d.sort, perm.mean, d.sort - perm.mean, d.sort.list)
row.names(aa4) <- row.names(y)[d.sort.list]
d <- L[[5]]
d.sort.list <- sort.list(d)
d.sort <- d[d.sort.list]
perm.mean <- rowMeans(to5)
aa5 <- cbind(d.sort, perm.mean, d.sort - perm.mean, d.sort.list)
row.names(aa5) <- row.names(y)[d.sort.list]
res <- list(aa1 = aa1, to1 = to1, aa2 = aa2, to2 = to2, aa3 = aa3,
to3 = to3, aa4 = aa4, to4 = to4, aa5 = aa5, to5 = to5)
return(res)
}
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