Description Usage Arguments Value Author(s) Examples
The function nkpartitions
lists all possible partitions of n objects in to k clusters. The function nkpar
only gives the number of such partitions.
1 2 | nkpartitions(n, k, exact = TRUE, print = FALSE)
nkpar(n, k)
|
n |
Number of units/objects |
k |
Number of clusters/groups |
exact |
Search for partitions with exactly k or at most k clusters |
print |
print results as they are found? |
The matrix or number of possible partitions.
Chris Andrews
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | n <- 8 #if larger, the number of partitions increases dramaticaly,
#as does if we increase the number of clusters
net <- matrix(NA, ncol = n, nrow = n)
clu <- rep(1:2, times = c(3, 5))
tclu <- table(clu)
net[clu == 1, clu == 1] <- rnorm(n = tclu[1] * tclu[1], mean = 0, sd = 1)
net[clu == 1, clu == 2] <- rnorm(n = tclu[1] * tclu[2], mean = 4, sd = 1)
net[clu == 2, clu == 1] <- rnorm(n = tclu[2] * tclu[1], mean = 0, sd = 1)
net[clu == 2, clu == 2] <- rnorm(n = tclu[2] * tclu[2], mean = 0, sd = 1)
#computation of criterion function with the correct partition
nkpar(n = n, k = length(tclu)) #computing the number of partitions
all.par <- nkpartitions(n = n, k = length(tclu)) #forming the partitions
all.par <- lapply(apply(all.par, 1, list), function(x) x[[1]])
# to make a list out of the matrix
res <- critFunC(M = net, clu = clu, approaches = "val",
blocks = c("nul", "com"), preSpecM = 4)
plot(res) #we get the original partition
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