like a good starting
procedure.
Thanks,kbrownk
On Dec 22, 3:32 pm, Duncan Murdoch wrote:
> On 21/12/2011 3:37 PM, kbrownk wrote:
>
> > > From library(diptest):
>
> > Shouldn't the following almost always be non-significant for
> > Hartigan's dip test?
>
nyone familiar with Hartigan's dip test and what I may not be
understanding?
Thanks,
kbrownk
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I ended up just using a vba macro for Excel. Hopefully I can start
transitioning to R for some of these tasks soon.
Thanks,
kbrownk
On Dec 20, 6:14 pm, Sarah Goslee wrote:
> > bindata <- 1:5
> > nobs <- c(2, 3, 1, 4, 3)
> > rep(bindata, times=nobs)
>
> [1] 1 1 2 2
Thanks for the heads up. I don't have a #. My data is as you suggest.
I tried to generalize my example because I'm open to reformatting for
the solution to my problem.
Thanks,
kbrownk
On Dec 20, 6:14 pm, Sarah Goslee wrote:
> > bindata <- 1:5
> > nobs <- c(2, 3, 1,
file actually looks like this:
Bin: 1,2,3, ... ,10 #Observations: 23,42,1,... 56
Bin: 1,2,3, ... ,10 #Observations: 13,33,32,...98
.
.
.
Bin: 1,2,3, ... ,10 #Observations: 11,76,55,...46
I want to automate the process.
Thanks for any advice,
kbrownk
_
ing on the advice you provided,
which may provide some answers.
Thanks,
kbrownk
On Dec 12, 1:38 am, Peter Langfelder
wrote:
> On Sun, Dec 11, 2011 at 8:43 PM,kbrownk wrote:
> > The R function hclust is used to do cluster analysis, but based on R
> > help I see no way to print the actu
Never mind on my reply post (hasn't posted yet, but assuming it does).
I found a way to use the merge and height values with Excel to
subtract out the lower level distance. Thanks for the help!
kbrownk
On Dec 12, 1:38 am, Peter Langfelder
wrote:
> On Sun, Dec 11, 2011 at 8:43 PM,kbrow
m
the mean fusion distance (i.e. The Best Cut Test).
To perform a cluster analysis I'm using:
x <- dist(mydata, method = "euclidean") # distance matrix
y <- hclust(x, method="ward") #clustering (i.e. fusion) method
plot(y)
. across
cluster similarities (i.e. distances).
If I'm way off please let me know, otherwise thanks for taking the time to
read my question.
kbrownk
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