Hi,
I have found references for the following problem in the list
archives, but no nice solution. So I decided to post one I came up
with.
The problem is that graphs output as eps files, for example using
ps.options(onefile=FALSE, paper=special, width=8, height=8,
horizontal=FALSE,
Dear all
I guess I have a quite simple question
I do not have any problem to plot the data (daily averages)in different
plots as monthly time series (for example with a for loop over the
different months). My problem begin when I want to represent always as a
time serie 1999 data (from june)
From a practical point of view, Carol Alexander's Market Models
might be about as good as it gets.
Patrick Burns
Burns Statistics
[EMAIL PROTECTED]
+44 (0)20 8525 0696
http://www.burns-stat.com
(home of S Poetry and A Guide for the Unwilling S User)
Wayne Jones wrote:
Hi there fellow R-Users,
can i ask you for logiciel R
-
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There is a problem with this scheme that has nothing to do with
syntax. Extending objects dynamically like this is probably the
surest way to run out of memory. If you know the final length an
object will be, then it is best to create the object at its full length
and then subscript into it with
Hi,
I suggest that you read the 'posting guide' - refer the bottom of all
emails on the list.
http://www.R-project.org/posting-guide.html
(il ne faut que d'aller chez http://www.r-project.org/ vous meme).
Sean
karima alem wrote:
can i ask you for logiciel R
The problem is simply that you are using epstopdf incorrectly. This is
not an R issue but the correct solution has been discussed here before
(although my quick searches failed to locate it in the archives).
First, if you want `PDF graphs' you can make them in R with the pdf()
device. I am
Assuming the same Y scale will work for all your data,
the plot statement plots columns 4 through 8 with no marker at
the points so the axes get set up correctly. Then matplot adds to it.
dd - ISOdate( data$year, data$month, data$day )
plot( rep(dd,5), as.matrix(data[,4:8]), type=n )
matplot(
I'm quite sure there're better ways, but this works for me:
dat - data.frame(y=rnorm(30), x1=runif(30), x2=runif(30), x3=runif(30),
+ group=factor(rep(1:3, each=10)))
getCoef - function(dat) {
+ apply(dat[,c(x1,x2,x3)], 2,
+ function(x) lm.fit(cbind(1, x),
Here's one simplistic solution, perhaps there are better ones:
# Make some test data and place in dataframe
x1=rnorm(20)
x2=rnorm(20)
x3=rnorm(20)
x4=as.factor(sample(c(G1,G2,G3),20,replace=T))
y1=2*x1+4*x2+0.5*x3+as.numeric(x4)+rnorm(20)
df=data.frame(y1,x1,x2,x3,x4)
# Now create the ouput
Note that there is a QUESTION at the end regarding
random effects.
Suppose your data frame is df and has components
y, x1, x2, x3 and u where u is a factor.
1. There was a problem posted about doing repeated regressions
(search for Operating on windows of data) last month that
has
The simplest solution for me is to set
setenv GS_OPTIONS -dAutoRotatePages=/None
There was a discussion on this topic a in October, but it was on
R-devel. See here
https://www.stat.math.ethz.ch/pipermail/r-devel/2003-October/027759.html
-roger
Tamas Papp wrote:
Hi,
I have found references
JFRI (Jesper Frickmann) wrote:
I want a list of the number of times some factor levels appear together,
Say a and b are the names of the factors:
table(a,b)
table(a:b)
aggregate(a,list(a=a,b=b),length)
Christophe Pallier
http://www.pallier.org
__
On Sat, 3 Apr 2004, Gabor Grothendieck wrote:
2. Another possibility is to create a giant regression that does
all the usergroup specific regressions at once and then repeat
it without the usergroup variable to get the rest.
df2 is a new data frame that strings out all the x variables into
Could anyone advise me how to allocate 1.5Gbyte memory for R on a Dell
laptop running XP professional with 2G memory?
I have tried
C:\Program Files\R\rw1081\bin\Rgui.exe --max-vsize=1400M
but I only get only 500MB for R actually.
I also tried memory.limit(2^30) in R and got
Yi-Xiong Sean Zhou wrote:
Could anyone advise me how to allocate 1.5Gbyte memory for R on a Dell
laptop running XP professional with 2G memory?
See ?Memory or the the R for Windows FAQ, which tells you:
2.7 There seems to be a limit on the memory it uses!
Indeed there is. It is set by the
After memory.limit(1500), the error message still pop out:
Error: cannot allocate vector of size 11529 Kb
While
memory.size()
[1] 307446696
memory.limit()
[1] 1572864000
And the system is only using 723MB physical memory, while 2G is the total.
Does anyone have a clue of what is going on?
If you check the max memory used, I bet it is the same as your
memory.limit. Try
memory.size(max=TRUE)
to see how much memory was allocated. You also might try
--max-mem-size=2000M. R will not actually be able to get all 2 Gb of
ram, but I think it will be more than 1.5 Gb you are allowing now.
R1.9.0beta solves the problem for now. The memory foot print of R1.9.0 is
way smaller than R1.8.1, with only 400M. It will be interesting to see how
R1.9.0 handles the memory problem when it needs more than 700M.
Thanks for your helps.
Yi-Xiong
-Original Message-
From: Roger D. Peng
In general, this is not an R problem, it is a Windows problem. I find
that these types of memory problems do not appear on Linux, for example.
-roger
Yi-Xiong Sean Zhou wrote:
R1.9.0beta solves the problem for now. The memory foot print of R1.9.0 is
way smaller than R1.8.1, with only 400M. It
That is true, but I don't see that Yi-Xiong Sean Zhou has actually yet
followed the instructions for 1.8.1, which is to set --max-mem-size on the
command line (and this is in the rw-FAQ as people have pointed out).
The issue is that on Windows the memory address space can get fragmented,
and
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