I can't resist being a bit philosophical here. I guess that's one sign of
aging...
You can't form hypotheses and "prove" them with the same data, even if you use
different statistical (or something else) methods for the two steps. That, to
me, is self-fulfilling prophecy.
I get the feeling t
Thank you for both your help saving me a a lot of time searching for
the right technique. I have another question regarding clustering:
My data set occasionally has only one cluster, meaning that clustering
is not required in these occasional cases.
Example:
list <- c(767, 773, 766, 772, 778, 77
On Wed, 5 May 2010, Ralf B wrote:
Hi R friends,
I am posting this question even though I know that the nature of it is
closer to general stats than R. Please let me know if you are aware of
a list for general statistical questions:
I am looking for a simple method to distinguish two groups of
One of many possible approaches is called k-means clustering.
my.data <- c(1,2,3,2,3,2,3,4,3,2,3,4,3,2,400,340,3,2,4,5,6,4,3,6,4,5,3)
split(my.data, kmeans(my.data, 2)$cluster)
$`1`
[1] 400 340
$`2`
[1] 1 2 3 2 3 2 3 4 3 2 3 4 3 2 3 2 4 5 6 4 3 6 4 5 3
Ralf B wrote:
Hi R friends,
I am posti
Hi R friends,
I am posting this question even though I know that the nature of it is
closer to general stats than R. Please let me know if you are aware of
a list for general statistical questions:
I am looking for a simple method to distinguish two groups of data in
a long vector of numbers:
li
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