David,
Using the ?count.fields revealed that I only have 2410 columns. That fixed
the problem I had. I used, data_tmp[,842:2410] and that gave me the solution
I was looking for. This, ironically, also solved the other problem I had.
As for:
>
> You also say file.remove( fileout) , then you try
Hi Meir,
It's part of Prof. Ripley's package tree, but is not exported.
library(tree)
ls(asNamespace("tree"))
RSiteSearch("tree.matrix")
Regards, Mark.
Meir Preiszler wrote:
>
>
> Hi,
>
> Does anyone know where such a function can be found?
>
> Thanks
> Meir
>
>
>
> **
Hi Rodrigo,
[apropos of Ward's method]
>> ... we saw something like "You must use it with Euclidean Distance..."
Strictly speaking this is probably correct, as Ward's method does an
analysis of variance type of decomposition and so doesn't really make much
sense (I think) unless Euclidean dist
Hi,
Does anyone know where such a function can be found?
Thanks
Meir
Meir Preiszler - Research Engineer
I t a m a r M e d i c a l Ltd.
Caesarea, Israel:
Tel: +(972) 4 617 7000 ext 232
Fax: +(972) 4 627 5598
Cell: +(972) 54 699 9630
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Neil Shephard wrote:
Jinsong Zhao wrote:
Hi there,
I hope to draw a plot like this:
http://www.sg-chem.net/swizard/Ru-bqdi-spectra.gif
is it possible to draw it using R?
thanks for any suggestions.
My intuition would say yes it is possible as R graphics are highly flexible.
I'm afraid I
I think the function split.screen() in 'graphics' package is enough
for this task. For example,
##
fig.loc = matrix(c(0, 1, 0, 1, 0.1, 0.6, 0.5, 0.9),
2, byrow = T)
x = split.screen(fig.loc)
par(mar = c(3, 3, 1, 1))
screen(1)
plot(rnorm(100))
screen(2)
plot(rnorm(20), type = "h")
Yihui
On Mo
Jinsong Zhao wrote:
Hi there,
I hope to draw a plot like this:
http://www.sg-chem.net/swizard/Ru-bqdi-spectra.gif
is it possible to draw it using R?
Hi Jinsong,
Look at the subplot function in the TeachingDemos package.
Jim
__
R-help@r-project.
Solved! Something must have gone wrong when I set up the system. I reinstalled
Mandriva, updated the packages and VOILA: R finally installed without any
problems!
Thanks Joanne
[[alternative HTML version deleted]]
__
R-help@r-project.org m
Jinsong Zhao wrote:
>
> Hi there,
>
> I hope to draw a plot like this:
> http://www.sg-chem.net/swizard/Ru-bqdi-spectra.gif
>
> is it possible to draw it using R?
>
> thanks for any suggestions.
>
My intuition would say yes it is possible as R graphics are highly flexible.
I'm afraid I don
Hi Roberto,
The other thing you can do --- if you don't wish to step across to lmer(),
where you will be able to exactly replicate the crossed-factor error
structure --- is stay with aov(... + Error()), but fit the factor you are
interested in last. Assume it is Sex. Then fit your model as
aov.m
lme4
On Mon, Sep 15, 2008 at 12:35 PM, Wensui Liu <[EMAIL PROTECTED]> wrote:
> I checked GlmmML package. However, it can only do binomial and poisson
> distribution. How about others such as gamma or neg binomial?
> Thank you so much!
> wensui
>
--
Yihui Xie <[EMAIL PROTECTED]>
Phone: +86-(0)10
Felipe wrote:
i calculated the density and wanna do something like this
separate in 0-19-29-39-49-59-69-79-99
and put in these spaces 8 densities .. 0.something
i have the frequency in % and divided already in 20 or 10 to get the density
i tried and tried..made breaks vector to separate but cou
Hi, guys,
I am trying to sample from a truncated normal/gamma distribution.
But only the far end of the distribution (where the probability is very low)
is left. e.g.
mu = - 4;
sigma = 0.1;
The distribution is Normal(mu,sigma^2) truncated on [0,+Inf];
How can I get a sample? I tried to use inver
Thierry,
Thanks so much. Your solution works perfectly.
Tony
-Original Message-
From: ONKELINX, Thierry [mailto:[EMAIL PROTECTED]
Sent: Monday, September 15, 2008 2:56 AM
To: Brown, Tony Nicholas; r-help@r-project.org
Subject: RE: [R] randomly sample within clustered data?
Something li
Gundala Viswanath wrote:
Hi,
I have a density plot in which the x axis
ranged from 0 to 2000.
How can I scale the data so that the x-axis
is scaled in -1 to 1 form?
Hi Gundala,
If your data is named "mydata":
mynewdata<-rescale(mydata,c(-1,1))
This will linearly transform "mydata" into t
Something like this?
do.call("rbind",
lapply(
split(Dataf, Dataf$id),
function(x){
x[sample(seq_len(nrow(x)), size=2), ]
}
)
)
HTH,
Thierry
Dear useRs,
What is an efficient way to randomly sample from clustered data such
that I get equal representation from each cluster? For example, let's
say I want to randomly sample two cases from each cluster created by the
"id" variable in the following data frame:
> id<-c(rep("100", 4),re
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