similar to: problem creating an array

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] <-