[R] Dynamic clustering?

[Ralf B]

Are there R packages that allow for dynamic clustering, i.e. where the
number of clusters are not predefined? I have a list of numbers that
falls in either 2 or just 1 cluster. Here an example of one that
should be clustered into two clusters:

two <- c(1,2,3,2,3,1,2,3,400,300,400)

and here one that only contains one cluster and would therefore not
need to be clustered at all.

one <- c(400,402,405, 401,410,415, 407,412)

Given a sufficiently large amount of data, a statistical test or an
effect size should be able to determined if a data set makes sense to
be divided i.e. if there are two groups that differ well enough. I am
not familiar with the underlying techniques in kmeans, but I know that
it blindly divides both data sets based on the predefined number of
clusters. Are there any more sophisticated methods that allow me to
determine the number of clusters in a data set based on statistical
tests or effect sizes ?

Is it possible that this is not a clustering problem but a
classification problem?

Ralf