Hi,
Has anyone attempted to compile R on QNX 4.x or 6.x ? It would be
particularly cool if there is a precompiled version somewhere on the QNX
software archives.
Thank you very much !!
Suresh
ps. Please cc replies to my address if possible...
__
Hi,
I am trying to fit a function of the form:
y = A0 + A1 * exp( -0.5* ( (X - Mu1) / Sigma1 )^2 ) - A2 * exp ( -0.5*
( (X-Mu2)/Sigma2 )^2 )
i.e. a mean term (A0) + a difference between two gaussians.
The constraints are A1,A2 >0, Sigma1,Sigma2>0, and usually Sigma2>Sigma1.
The plot looks
Sorry, I wrote too soon. I thought you meant rdcom. My fault... I dont
know of anything wrong with rcom 1.2.2, it works for me.
Suresh
On Tue, 08 Nov 2005 08:29:12 -0500, Suresh Krishna <[EMAIL PROTECTED]>
wrote:
>
> You need the 2.0 beta package available
You need the 2.0 beta package available at:
http://sunsite.univie.ac.at/rcom/download/RSrv200beta.exe
Also, there is a rcom mailing list at
http://mailman.csd.univie.ac.at/mailman/listinfo/rcom-l for more help.
Suresh
On Tue, 08 Nov 2005 06:42:37 -0500, Julia Ivanova <[EMAIL PROTECTED]> wrot
I am very much a naive and interested beginner, so I am not at all sure
if you will find this reference
http://snipurl.com/hq2j
interesting
S.
Uwe Ligges wrote:
> Sebastian Leuzinger wrote:
>
>
>>the null hypothesis would be: one particular frequency peak is not
>>significantly differe
i dont use gmail, but this method *may* run into problems if people are
replying to a message and "r-help" is on the cc: line.
thunderbird has a "to: or cc:" option for this... is gmail's to: field a
default for "to: or cc:" ?
-s.
Deepayan Sarkar wrote:
> On 6/30/05, Douglas Bates <[EMAIL PRO
From:
?cor.test
Arguments:
x, y: numeric vectors of data values. 'x' and 'y' must have the
same length.
-s.
Michael Grant wrote:
Using Windows System, R 2.1.0
d is a data frame, 48 rows, 10 columns
cor(d) works properly providing all pairwise Pearson correlation
coefficients
it is the first link if you type "making packages" into the google
search box here:
http://maths.newcastle.edu.au/~rking/R/
-s.
Laura Holt wrote:
Hi R People:
A few weeks ago, someone put a link to a website for "how to" for
building R packages. It was very nice.
But of course, I have
http://snipurl.com/f0xh
(leads you to packages 'ade4' and 'MASS')
-s.
Navarre Sabine wrote:
I would like to donc an AFC (factoriel correspondance analysis) and I know that
on Splus, the function to do that is afc(data). But on R??? is it acm?
That a lot!
Sabine
-
Sonya Ku wrote:
Hi
I am just beginning to learn R and have fitted several GAM to my
species presense/absence data.
I have used plot(x,y) using fitted.values as a y variable against
predictors. However, it is hard to see general relationships where
there is wide spread in predicted values for any
oops, my fault. i missed typing the key '*' character in the second version.
apologies !!!
suresh
Suresh Krishna wrote:
Is that the entire story ? I tried this with yesterday's patched version
(windows xp) and found:
> list.files(getwd(),"*.txt",full=T)
Error
Is that the entire story ? I tried this with yesterday's patched version
(windows xp) and found:
> list.files(getwd(),"*.txt",full=T)
Error in list.files(path, pattern, all.files, full.names, recursive) :
invalid 'pattern' regular expression
> list.files(getwd(),'.txt',full=T)
[1] "C:/Doc
oops, i meant something more like:
TestValues <- c(0,1,2,4,9) #should be in increasing order
TestResults <- c(.95, .85, .7, NaN,0)
if (InternalMean==0) IntResult=1 else
IntResult=TestResults[TestValues==max(TestValues[TestValues<=InternalMean])]
-s.
Suresh Krishna wrote:
are you lo
are you looking for something like:
InternalMean <- mean(data1[,3])
TestValues <- c(0,1,2,4,9) #should be in increasing order
TestResults <- c(.95, .85, .7, NaN,0)
if (InternalMean==0) IntResult=1 else
IntResult=TestResults[which(TestValues==max(TestValues[TestValues
-s.
Jones, Glen R wrote:
Hell
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/20509.html
-s.
Hui Han wrote:
Thank you very much, Professor Ripley.
If possible, could you point me to other packages that you think I
should look at for estimating a derivative?
Best regards,
Hui
Prof Brian Ripley wrote:
On Tue, 10 May 2005, Hui H
oh, this too...
http://finzi.psych.upenn.edu/R/library/stats/html/anova.mlm.html
and these threads:
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/48210.html
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/46714.html
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/16662.html
Suresh Krishna wrote
see these threads:
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/46512.html
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/15653.html
-suresh
Darren Weber wrote:
Is there a function in R for doing Greenhouse-Geiser correction in ANOVA
models?
Is it already available in the aov function? How do
Oops, I corrected some errors in the first paragraph; sorry for the
repeated posting.
Suresh
~~
Hi,
I am analyzing a data set with greater than 1000 independent cases
(collected in an unrestricted manner), where each case has 3 varia
Hi,
I am analyzing a data set with greater than 1000 independent cases
(collected in an unrestricted manner), where each case has 3 variables
associated with it: one, a factor variable with 0/1 levels (called XX),
another factor variable with 8 levels (X) and a third response variable
with two
-existent directory), Emacs will freeze as soon as
one toggles from the Emacs window to another application and back to Emacs.
And of course, I should have written FSF Emacs in my original post, not FSG.
Hope this helps!
Le 26 Février 2005 00:06, Suresh Krishna a écrit :
Prof. Goulet,
I apologize in
work on it, I might develop some way to simulate a
process that seemed to describe what I thought generated these numbers
and compare simulated results with actual, under a variety of
hypotheses, obtaining various kinds of p-values, etc.
hope this helps. spencer graves
Suresh Krishna
Hi,
I have a question that I have not been succesful in finding a definitive
answer to; and I was hoping someone here could give me some pointers to
the right place in the literature.
A. We have 4 sets of data, A(t), B(t), C(t), and D(t). Each of these
consists of a series of counts obtained in
hi,
after
m=locfit(y~x,..., family=binomial)
plot(m,band="local") gives me a plot of locfit's result with a confidence
interval around it. i would like to get the actual values that are being
used to plot the lines in this figure.
i tried using predict, but the standard error it returns
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