Hi Harold:
Yes, this was the R code that I tried, and got different result from SAS.
Is that mean I cannot actually use R to run unstructured covariance matrix?
How can I solve this problem if I need an unstructured covariance matrix
method?
Thanks for the help.
--
View this message in
Belle:
Before I provide any more help, you'll need to follow some posting guide rules
and describe what you have done with some R code, describe what the problem is,
and describe what you are hoping to accomplish.
The fact that the results you get from R and SAS are different doesn't mean
Hello,
I've drawn a black rectangle over the plotting area, and when I add an image()
heatmap, it doesn't take up all the area, but is set inward from the black
rectangle. Can anyone suggest how to make it stretch out to the entire area ?
Minimal example :
y - matrix(runif(2000*20), nrow =
Hello,
Yes, that's right, it is a values matrix. Not a dissimilarity matrix.
i.e.
str(iMatrix)
num [1:23371, 1:56] -0.407 0.198 NA -0.133 NA ...
- attr(*, dimnames)=List of 2
..$ : NULL
..$ : chr [1:56] -8100 -7900 -7700 -7500 ...
For the snippet of checking for NAs, I get all TRUEs, so
May be this problem is OS specific (mac OS or windows...) i use ubuntu and
have no problem with this function
R packageVersion(base)
[1] ‘2.12.1’
R packageVersion('lme4')
[1] ‘0.999375.37’
R sessionInfo()
R version 2.12.1 (2010-12-16)
Platform: x86_64-pc-linux-gnu (64-bit)
locale:
[1]
Hello,
I want to create a flexible code for the following example: In stead of
using a different code for each n (as in my example below), I want to
write a general code for every n (n from 1 to 10).
I tried a lot of things, but I always got stuck with the number of
subloops or witch closing
Hi,
I have this data.frame with two variables in it,
z
V1 V2
1 10 8
2 NA 18
3 9 7
4 3 NA
5 NA 10
6 11 12
7 13 9
8 12 11
and a vector of means,
means - apply(z, 2, function (col) mean(na.omit(col)))
means
V1V2
9.67 10.714286
My intention was substracting means
Hi Harold:
I know the outputs are different between SAS and R, but the results that I
got have big difference.
Here is part of the result based on the SAS code I provided earlier:
Cov Parm SubjectEstimate Error
Value Pr Z
sapply(z, function(row) ...) does not actually grab a row at a time out of
'z'. It grabs a column (because 'z' is a data.frame)
You may want:
t(apply(z, 1, function(row) row - means))
or:
t(t(z) - means)
Hope that helps,
-David Johnston
--
View this message in context:
The empirical statement on the proc mixed line gives you robust
standard errors, I don't think you get them in R.
In SAS you specify that the predictors are to be dummy coded using the
class . Are they factors in R? I can't tell from the SAS output,
because the formatting has been lost.
On Jan 27, 2011, at 7:16 PM, Ernest Adrogué i Calveras wrote:
Hi,
I have this data.frame with two variables in it,
z
V1 V2
1 10 8
2 NA 18
3 9 7
4 3 NA
5 NA 10
6 11 12
7 13 9
8 12 11
and a vector of means,
means - apply(z, 2, function (col) mean(na.omit(col)))
means
V1
It looks like the text didn't show assigning the results of factanal
to an object. Try:
pgdata-read.table(pgfull.txt,header=T)
names(pgdata)
pgd-pgdata[,1:54]
#missing line
model - factanal(pgd,8)
par(mfrow=c(2,2))
plot(loadings(model)[,1],loadings(model)[,2],pch=16,xlab=Factor
1,ylab=Factor 2)
In addition to what has already been suggested you could use ..
mapply(function(x,y) x-y, z,means)
which returns
V1 V2
[1,] 0.333 -2.7142857
[2,] NA 7.2857143
[3,] -0.667 -3.7142857
[4,] -6.667 NA
[5,] NA -0.7142857
[6,]
You could use the survey package to run the bootstrapping, if you mean
the Rao Wu bootstrap that samples n-1 of n PSUs in each replicate.
Set up a survey design object with bootstrap replicate weights: use
svrepdesign() if you already have replicate weights, use svydesign()
and then
R works by going down the columns. If you make the rows into columns, it then
does what you want. You just have to make the columns back into rows to get the
original shape of your matrix.
So the code in one line is :
t(t(z) - means)
Original message
Date: Fri, 28 Jan 2011 01:16:45
Newbie and trying to learn the right way of doing things in R. in this case,
I just have that feeling that my convoluted line of code is way more
complicated than it needs to be. Please help me in seeing the easier way.
I want to do something pretty simple. I have a dataframe called x that is
On Thu, Jan 27, 2011 at 11:56 AM, John E. Kaprich jkapr...@gmail.com wrote:
When I try to convert the zoo object to a timeSeries object, which would
allow me to utilize Rmetrics packages, I get an error message.
Data-read.zoo(c:\\DOWUBSPRICING.txt,na.strings=NA,sep=\t,header=T)
is(Data)
David Winsemius dwinsem...@comcast.net [Thu, Jan 27, 2011 at 10:08:00PM CET]:
You got a perfectly sensible reply from Thereau, the author of the
package, a day after your posting and then failed to respond to his
questions. I'm not sure what more you are expecting.
My apologies. Next time
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of eric
Sent: Thursday, January 27, 2011 7:07 PM
To: r-help@r-project.org
Subject: [R] There must be a smarter way
Newbie and trying to learn the right way of doing things in
On Jan 28, 2011, at 12:37 AM, Johannes Huesing wrote:
David Winsemius dwinsem...@comcast.net [Thu, Jan 27, 2011 at
10:08:00PM CET]:
You got a perfectly sensible reply from Thereau, the author of the
package, a day after your posting and then failed to respond to his
questions. I'm not sure
On Jan 27, 2011, at 6:29 PM, Peter Jaksons wrote:
Hello,
I want to create a flexible code for the following example: In stead
of
using a different code for each n (as in my example below), I want to
write a general code for every n (n from 1 to 10).
Have you done any thinking about the
Hi,
I am trying to work with the ape package, and there is one thing I am
struggling with. When calling the *read.GenBank()* function, I can get it
to work with an object created like this:
*x - c(AY395554,AY611035, ...)*
*read.GenBank(x)*
However, I am trying to use the function to fetch
Could someone please help me with instructions on running a principal
coordinate analysis using R?
Julie Smith
Sent from my iPod
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R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
Hi,
I am trying to convert a 2D correlation matrix to 3 columns for graphical
representation:
rdata = replicate(100, rnorm(15)) #construct a 2D matrix
c1 = cor(rdata) #outputs a correlation matrix
Now I want to convert the 2D c1 to
(row#, col#, correlation)
1 1 cor1
1 2 cor2
1 3 cor3
...
2 1
I need to import a large number of simple, space-delimited text files with a
few columns of data each. The one quirk is that some rows are missing data and
some contain junk text at the end of each line. A typical file might look like:
a b c d
1 2 3 x
4 5 6
7 8 9 x
1 2 3 x c c
4 5 6 x
7 8 9 x
Hi,
I have 25 normal and 25 tumor samples and generated 50 boxplots one for
each
Is there a possibility to alternate the colors for the boxplots
Green Red Green Red.
Example:
A B C D
10 23 23 34
20 24 24 30
20 2434 34
this would generate 4 boxplot one for each. I want the boxplot
On Thu, 27 Jan 2011, Julie Smith wrote:
Could someone please help me with instructions on running a
principal coordinate analysis using R?
?cmdscale
Julie Smith
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
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