Wagner Bonat wbo...@gmail.com
on Wed, 23 Apr 2014 12:12:17 +0200 writes:
Hi all !
I am look for some efficient method to compute the derivative of
exponential matrix function in R. For example, I have a simple matrix like
log.Sigma - matrix(c(par1, rho, rho, par2),2,2)
EL == Eberhard Lisse nos...@lisse.na
on Thu, 24 Apr 2014 01:21:37 +0100 writes:
EL In MySQL
EL SELECT INET_ATON('127.0.0.1')
EL returns the integer 2130706433
EL Is there a function in R to reverse that, ie so that something like
EL ip - inet_ntoa(2130706433)
EL
Dear R users;
I have a question about Cramer Rao upper/lower bounds
Is it possible to compute Crammer Rao upper/lower bounds from residuals
and corresponding covariance matrices ?
Any suggestions will be appreciated, thanks in advance.
M.O
__
On 23/04/2014, 9:02 PM, Alex Reynolds wrote:
Unfortunately, that doesn't help as it removes axis lines. It looks like
I can't use segments3d() without knowing what the bounds are of the
current axes and I don't know what to call to expose those.
Thanks again for your help, though, I appreciate
Sir I have this problem,
res -
maxLik(logLik=loglik1,start=c(a=1.5,b=1.5,c=1.5,dee=2),method=BFGS)
There were 50 or more warnings (use warnings() to see the first 50)
summary(res)
Maximum Likelihood estimation
BFGS maximisation, 0 iterations
Return code 100: Initial value out of
On 04/24/2014 08:52 PM, mark wrote:
On 04/23/14 23:22, William Dunlap wrote:
Aren't those files support for named semaphores (made with sem_open())?
Packages like BH and RSQLite contain calls to sem_open. Is your
long-running
R process using such a package?
I don't think you would want to
On 24/04/2014, 7:42 AM, Jim Lemon wrote:
On 04/24/2014 08:52 PM, mark wrote:
On 04/23/14 23:22, William Dunlap wrote:
Aren't those files support for named semaphores (made with sem_open())?
Packages like BH and RSQLite contain calls to sem_open. Is your
long-running
R process using such a
At 11:56 22/04/2014, Dipl. Kfm Dominik Wagner MSc; MSc wrote:
Dear all,
I am quite new to R. Now my following easy question.
I use metafor and performed an outlier test with rstudent(res).
This is resulting in 1000 rows of 1578 and 578 omitted rows (starting with
row 598).
1. How can I
Hi,
I want to implement CHAID in R, but at this point am not sure how to go
about it.
Would be glad if someone please helps me out with it. I am attaching the
data set for your perusal.
The variable in the 1st column is the dependent variable.
Thanks,
Preetam
--
Preetam Pal
(+91)-9432212774
On 24/04/2014 9:56 AM, m.r...@5-cent.us wrote:
Duncan Murdoch wrote:
On 24/04/2014, 7:42 AM, Jim Lemon wrote:
On 04/24/2014 08:52 PM, mark wrote:
On 04/23/14 23:22, William Dunlap wrote:
snip
deleting those files. I'm sure that my user's long-running job is
creating them. What I'm asking is
I need to generate a sparse matrix. Currently I have the data held in two
regular matrices. One 'targets' holds the column subscripts while the other
'scores' holds the values. I have written a 'toy' sample below. Using this
approach takes about 90 seconds to populate a 3 x 3 element
Hi Marta,
If your first dataset field2 is greater than the number of rows for a
particular field1 in second dataset, this error could happen.
e.g. using modified dat1:
dat1 - structure(list(field1 = 1:3, field2 = c(3L, 20L, 4L)), .Names =
c(field1,
field2), class = data.frame, row.names =
âlibrary(mvpart)
The r code I used:
mvpart(ept~cond+phlab+doc+episub+embed+woodtot+shade+Q+stgrad+veldpth,
data=mydata, method=anova, xv=1se, xval=5, xvmult=1000)â
Part of the tabular output of the tree:
*1) root 295 3905.9860 4.806780 *
* 2) cond=194.15 77 491.2468 2.493506 *
Or perhaps the documentation could be updated to clear up what works and what
doesn't. It seems pretty confusing to put options in the docs that do not work
as described.
-Alex
On Apr 24, 2014, at 4:05 AM, Duncan Murdoch murdoch.dun...@gmail.com wrote:
On 23/04/2014, 9:02 PM, Alex Reynolds
Hi all;
I have a data set that I want to remove the top values above 90th
percentile from it. Any suggestions?
Thank you;
--
*Nasrin Pak, MSc*
Air Quality Scientist
[[alternative HTML version deleted]]
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R-help@r-project.org mailing list
Duncan Murdoch wrote:
On 24/04/2014, 7:42 AM, Jim Lemon wrote:
On 04/24/2014 08:52 PM, mark wrote:
On 04/23/14 23:22, William Dunlap wrote:
snip
deleting those files. I'm sure that my user's long-running job is
creating them. What I'm asking is if ANYONE HERE knows if there is some
On 04/23/14 23:22, William Dunlap wrote:
Aren't those files support for named semaphores (made with sem_open())?
Packages like BH and RSQLite contain calls to sem_open. Is your long-running
R process using such a package?
I don't think you would want to delete those files, but perhaps you can
Thank you,
el
on 2014-04-24, 10:33 Martin Maechler said the following:
EL == Eberhard Lisse nos...@lisse.na
on Thu, 24 Apr 2014 01:21:37 +0100 writes:
EL In MySQL
EL SELECT INET_ATON('127.0.0.1')
EL returns the integer 2130706433
EL Is there a function in R to
Is this what you want:
myData - rnorm(1000)
length(myData)
[1] 1000
top90 - quantile(myData, prob = 0.9)
low90 - myData[myData top90]
length(low90)
[1] 900
Jim Holtman
Data Munger Guru
What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to
Hello,
I am unable to install package rqpd. I have also tried to download for source
but not able to do so.
Please help
thank in advance
regards
vishal
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PLEASE do read
Hi,
Someone just asked me to analyze a fairly large data set using something
they called perceptual mapping. I'm not familiar with the term, but a
quick check in Google seems to indicate that it is just another term for
Multidimensional Scaling. However, they insist that it is something
Hello!
I am using the metafor package for my master's thesis as an R-newbie. While
calculating effectsizes from my dataset (mean values and
standarddeviations) using escalc shouldn't be a problem (I hope ;-)), I
wonder how I could at this point integrate additional studies, which only
state
google on perceptual mapping with R
Here is one of the hits:
http://marketing-yogi.blogspot.com/2012/12/session-4-rcode-perceptual-maps.html
It does not look like mds. It appears to be (closely related to?) PCA.
Cheers,
Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
Good evening sir/madam
My name is katleho makatjane. I am currently a B.com statistics student at
North West University Mafikeng campus. I have installed R 3.1.0 on my laptop
but my main problem is to install all necessary packages so that I may be able
to start using it for my analysis. It
Normally on Windows you should install the Windows binary from the
*.zip file, not the source from the *.tar.gz file.
If you look at a CRAN page the available files are labeled that way.
You might also be interested in
?install.packages
There are further instructions available on your local
How did you try to install the package?
What happens when you try?
What operating system are you using?
What version of R are you using?
Did you try Google, and read any of the other discussions of how to
install rqpd?
Did you read the posting guide (linked at bottom of this and every
message)
Many, probably even most (but I have not checked) of the datasets
available in R packages have help files with a references section.
That section should lead you to an original source that may have the
copyright information and is what should be referenced.
My understanding (but I am not a
Convert your 'targets' matrix into a 2 column matrix with the 1st
column representing the row and the 2nd the column where you want your
values, then change the values to a single vector and you can just use
the targets matrix as the subsetting in 1 step without (explicit)
looping, for example:
r1 - totalEffect.all(dsim, simjob)
Error: attempt to apply non-function
traceback()
1: totalEffect.all(dsim, simjob)
class(totalEffect.all)
[1] function
How can I find out where in totalEffect.all the error is arising?
My only theory for the lack of line number was that totaEffect.all was
Thanks Bert,
Not sure how I missed that one.
Best,
On 4/24/14, 11:50 AM, Bert Gunter wrote:
google on perceptual mapping with R
Here is one of the hits:
http://marketing-yogi.blogspot.com/2012/12/session-4-rcode-perceptual-maps.html
It does not look like mds. It appears to be (closely
On 24/04/2014, 6:40 PM, Ross Boylan wrote:
r1 - totalEffect.all(dsim, simjob)
Error: attempt to apply non-function
traceback()
1: totalEffect.all(dsim, simjob)
class(totalEffect.all)
[1] function
How can I find out where in totalEffect.all the error is arising?
My only theory for
On Thu, 2014-04-24 at 19:29 -0400, Duncan Murdoch wrote:
On 24/04/2014, 6:40 PM, Ross Boylan wrote:
r1 - totalEffect.all(dsim, simjob)
Error: attempt to apply non-function
traceback()
1: totalEffect.all(dsim, simjob)
class(totalEffect.all)
[1] function
How can I find
Jeff,
I absolutely agree it is a bad idea to rely on side effects.
I did figure out one way to skin this cat. It relies on an the following
from line 909 of src/main/main.c,
R_LoadProfile(R_OpenSiteFile(), baseEnv);
R_LockBinding(install(.Library.site), R_BaseEnv);
I'm trying to figure out if there is a way in R to get the loglikelihood of
a distribution fit to a set of data where the parameter values are fixed.
For example, I want to simulate data from a given alternate lognormal
distribution and then I will fit it to a lognormal distribution with null
The discussion in the forum solves your issue
http://stackoverflow.com/questions/1474081/how-do-i-install-an-r-package-from-source
Raghu
On Thu 24 Apr 2014 08:26:33 PM CEST, KD Makatjane wrote:
Good evening sir/madam
My name is katleho makatjane. I am currently a B.com statistics student at
Hi,I have been trying to make my axis fonts and axis labels fonts in bold even
when the I write the right command. I writing font.lab=2, font.axis=2 but the
bold fonts don't show up. Any help?
Thanks!
[[alternative HTML version deleted]]
As usual I am too lazy to fight my way through the rather convoluted
code presented, but it seems to me that you just want to calculate a log
likelihood. And that is bog-simple:
The log likelihood for i.i.d. data is just the sum of log f(y_i) where
the y_i are your observed values and f()
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