Hi Thomas,
Thanks for the reply.
1. In the first pick, I draw 'A' genes from N, without replacement.
2. Similarly, in the second pick, I draw 'B' genes from N, without replacement
(and 'C' genes from 'N' etc.)
3. Order does not matter - so the two cases you cited are equivalent.
I would like to
Hi All,
My apologies if this is a totally newbie question.
I want to calculate the probability that a particular set of genes is picked
repeatedly for 3 samplings. For example, if from a total of 'N' genes, I pick
'A' number of genes in the first pick, 'B' number of genes in the second pick,
Hi,
I was trying to install R in my home directory on a Mac OS X Server running
Darwin. How do I go about installing it? How can I install from the binary
provided (R-2.11.1.pkg) from command line?
Is there any other information that I can provide?
thanks
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Hi,
I looked at the help documentation, but couldn't find the algorithm for
calculating the modified jaccard index for separate sets of biclusters. Is
there
a link to some documentation on this?
many thanks!
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From: Ben Bolker
To: r-h...@stat.math.ethz.ch
Sent: Thu, September 2, 2010 2:06:47 PM
Subject: Re: [R] Linear models (lme4) - basic question
James Nead yahoo.com> writes:
>
> Sorry, forgot to mention that the processed data will be used as input for a
> classification alg
Sorry, forgot to mention that the processed data will be used as input for a
classification algorithm. So, I need to adjust for known effects before I can
use the data.
thanks
From: Bert Gunter
Cc: r-help@r-project.org
Sent: Thu, September 2, 2010 12:46:13
Hi Bert,
Thanks for the reply.
Height, was just as an example. Perhaps, I should have said 'x' instead of
height.
Essentially, what I want to do is adjust the data for known effects. After I've
done this, I can conduct further analysis on the data (for example, if another
variable 'z' has an
Hi,
Sorry for a basic questions on linear models.
I am trying to adjust raw data for both fixed and mixed effects. The data that
I
output should account for these effects, so that I can use the adjusted data
for
further analysis.
For example, if I have the blood sugar levels for 30 patients,
Hi,
I wanted to compare the quality of biclusters obtained from the various
biclustering algorithms. Is there a function/metric in biclust (or some other
package) that will enable me to do this?
thanks!
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