Displaying 5 results from an estimated 5 matches similar to: "problem creating an array"
2005 Jan 13
1
(no subject)
Good morning,
I wrote a little code in R which has to show two graphs but I can get
only one. How can I adress the graphs in two files?
Second, I'd like, always in the same code, to add a legend to a graph.
Better, I'd like to put in such a legend a new item whose color
could remind the colour ol the columns it refers to in the plot. I wrote:
leg.txt<-c("control
2008 Dec 15
2
cannot allocate vector of size... restructuring suggestion please...
Dear R Users,
I was running some data analysis scripts and ran into this error:
Error: cannot allocate vector of size 27.6 Mb
Doing a "memory.size(max=TRUE)" will give me:
[1] 1506.812
The current situation is:
I'm working on a Windows Vista 32bit laptop with 4GB RAM (effectively
3GB I assume...)
I have a data file of 450Mb loaded into R and have around 1500
data.frames floating
2005 Jan 13
0
(no subject)
Good morning,
I wrote a little code in R which has to show two graphs but I can get
only one. How can I adress the graphs in two files?
Second, I'd like, always in the same code, to add a legend to a graph.
Better, I'd like to put in such a legend a new item whose color
could remind the colour ol the columns it refers to in the plot. I wrote:
leg.txt<-c("control
2010 Sep 03
1
Fourteen patches to speed up R
I've continued to work on speeding up R, and now have a collection of
fourteen patches, some of which speed up particular functions, and
some of which reduce general interpretive overhead. The total speed
improvement from these patches is substantial. It varies a lot from
one R program to the next, of course, and probably from one machine to
the next, but speedups of 25% can be expected in
2007 Nov 12
4
a repetition of simulation
Hello,
I have a simple (?) simulation problem.
I'm doing a simulation with logistic model and I want to reapet it 600
times.
The simulation looks like this:
z <- 0
x <- 0
y <- 0
aps <- 0
tiss <- 0
for (i in 1:500){
z[i] <- rbinom(1, 1, .6)
x[i] <- rbinom(1, 1, .95)
y[i] <- z[i]*x[i]
if (y[i]==1) aps[i] <- rnorm(1,mean=13.4, sd=7.09) else aps[i] <-