well, are you sure if party() can implement chaid?
i doubt if chaid is being implemented in any R package.
https://r-forge.r-project.org/projects/chaid/
--
Max
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Remove the y=c2 from your histogram plot.
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
On Aug 28, 2009, at 2:50 PM, Mcdonald, Grant wrote:
dear sir,
i am trying to calculate the standard error of my data (x),
The term standard error is generally applied to a parameter estimate
such as a regression coefficient. You may be looking for the function
to retrun the standard
i couldn't find it on CRAN.
On Fri, Aug 28, 2009 at 5:16 PM, Max Kuhn mxk...@gmail.com wrote:
well, are you sure if party() can implement chaid?
i doubt if chaid is being implemented in any R package.
https://r-forge.r-project.org/projects/chaid/
--
Max
--
Dumblauskas, Jerry jerry.dumblauskas at credit-suisse.com writes:
OK
Is your PostGres server on the same Linux box you are running R on?
Sample values
Server = 169.49.30.69 (localhost host means you are on the same
box)
yes, all is local here.
Port= 2700 (make
Sukhbir,
The recommended rsync commands for mirroring the Bioconductor
repositories are given at
http://bioconductor.org/download/mirrors/mirror-howto.html
Cheers,
Patrick
Paul Hiemstra wrote:
Sukhbir Rattan wrote:
Hi,
I have downloaded around 60GB package repositories of bioconductor
Dear list,
I am confused on how to explain the interaction term in the context of
treatment contrast.
for example, I have an data frame as below:
sub group val
1a group1 3.685625
2a group1 3.407445
3a group1 4.040920
4a group1 2.890875
5b group1 3.853280
6b group1
Hi Gavin
I am running on windows and have no problem
R version 2.9.2 (2009-08-24)
i386-pc-mingw32
locale:
LC_COLLATE=English_Australia.1252;LC_CTYPE=English_Australia.1252;LC_MONETARY=English_Australia.1252;LC_NUMERIC=C;LC_TIME=English_Australia.1252
attached base packages:
[1] datasets
Thanks, Prof Spector. Your first solution works well for me.
Phil Spector wrote:
David -
Here's the easiest way I've been able to come up with. I'll provide
some sample data to make things clearer (hint, hint):
dat = data.frame(matrix(rnorm(100),20,5))
dat[3,4] = NA
dat[12,3] = NA
scrs =
The intercept is group=1, sub=a,
The interaction between sub=b and group=2 implies that both sub=b and
group=2 direct effects are included. That is, with the direct effects only
you are now at: intercept+group2+subb, which means the intercept (group1 and
sub=a) + the average difference between
Hi,
How can I generate a random 100x100 correlation matrix, R={r_ij},
where about 10% of r_ij are greater than 0.9
Thanks in advance.
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PLEASE do read the posting guide
R - matrix(runif(1), ncol=100)
hth,
Kingsford Jones
On Fri, Aug 28, 2009 at 7:26 PM, Ning Mapnin...@gmail.com wrote:
Hi,
How can I generate a random 100x100 correlation matrix, R={r_ij},
where about 10% of r_ij are greater than 0.9
Thanks in advance.
Windows Vista
R 2.9.1
When trying to install Rcmdr I get the message shown below. What does it mean,
do I need to do anything?
The downloaded packages are in
C:\Users\John Sorkin\AppData\Local\Temp\RtmpRCLbhe\downloaded_packages
updating HTML package descriptions
Warning message:
In
Ahh -- Mark Leeds just pointed out off-list that it was supposed to be
a correlation matrix.
Perhaps
R - matrix(runif(1), ncol=100)
R - (R * lower.tri(R)) + t(R * lower.tri(R))
diag(R) - 1
These are of course uniformly distributed positive correlations.
Kingsford
On Fri, Aug 28, 2009 at
Hi Kingsford,
There is more structure to a correlation matrix than that meets the eye! Your
method will produce a matrix R that looks like a correlation matrix, but
beware - it is an impostor!
You can obtain a valid correlation matrix, Q, from the impostor R by using the
`nearPD' function in
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