similar to: memory problem in exporting data frame

Hi, I'm using R to collect data for a number of exchanges through a socket connection and constantly running into memory problems even though task I believe is not that memory consuming. I guess there is a miscommunication between R and WinXP about freeing up memory. So this is the code: for (x in 1:length(exchanges.to.get)) { tickers<-sqlQuery(channel,paste("SELECT Symbol

Hi there, I run the following code in R and got the warning like that, how can I change the memory.size? Or anything else? Thanks a lot! Faye temp<-apply(Idd4.perms$permstats[-stratum1,], + 2,sort) Error: cannot allocate vector of size 47.5 Mb In addition: Warning messages: 1: In apply(Idd4.perms$permstats[-stratum1, ], 2, sort) : Reached total allocation of 1023Mb: see help(memory.size)

I just have a simple question. I'm using the predict function, and I get about 1000 values. Now, how would I make it into a data frame or a list so that I can easily use Excel to graph the data? Right now, it's in horizontal lines, and it would be a pain to copy and paste and make it into a vertical column. Thanks! -- View this message in context:

I have been searching all day & most of last night, but can't find any benchmarking or recommendations regarding R system requirements for very large (2-5GB) data sets to help guide our hardware configuration. If anybody has experience with this they're willing to share or could anybody point me in a direction that might be productive to research, it would be much appreciated.

Dear list members I would like to apply a vector of labels v=c("lab1","lab2","lab3") to a dataframe df=data.frame(1:3,1:3,1:3) using some kind of loop or apply function. Any ideas? Thanks Steve Powell Checked by AVG Free Edition. 17:03 [[alternative HTML version deleted]]

hello, i have something like: out<-list() for(i in 1:n){ data<-gen(...) #fixed size data out[[i]]<- fun(data) } > object.size(out[[1]]) 6824 In principle 1 GB should allow n = 1024^3/6824 = 157347? i have about 2GB are not taken by other processes. however, I can see the memory shrinking quite rapidly on my system monitor and have to stop the simulation after only n=300. why

could someone explain what is happening below ? I was trying to solve a related question on the list and then , as I was solving it, I was getting strange answers and then I noticed below. It's obviously not a bug but I don't get it. Thanks. m <- data.frame(class = c("birds", "planes"), feather = c(1,3), jet = c(2,4)) d1 <- data.frame(jet = c(10), feather =

could someone explain what is happening below ? I was trying to solve a related question on the list and then , as I was solving it, I was getting strange answers and then I noticed below. It's obviously not a bug but I don't get it. Thanks. m <- data.frame(class = c("birds", "planes"), feather = c(1,3), jet = c(2,4)) d1 <- data.frame(jet = c(10), feather =

There's a new page on the Burns Statistics website http://www.burns-stat.com/pages/Tutor/spreadsheet_addiction.html that looks at spreadsheets from a quality assurance perspective. It presents R as a suitable alternative to spreadsheets. Also there are several specific problems with Excel that are highlighted, including the status of statistical functionality in Excel. Patrick Burns Burns

Hi all, I am using RODB to export multiple data.frames into one excel file with multiple sheets. One thing I can't seem to unserdatand is way the command adds the character: ' To the beginning of each of my (non numeric) values. Here is an example code: library(RODBC) library(MASS) data(anorexia) save2excel <- function(x, t.name) sqlSave(xlsFile, x, tablename = t.name, rownames =

I believe that I have a basic understanding of zoo and how to use read.zoo on a text file, What I have not seen in the zoo help files and vignettes is how to convert a data frame to a zoo matrix for irregular time series analyses. An example data frame is structured like this: str(burns.cast) 'data.frame': 256 obs. of 47 variables: $ site : Factor w/ 143 levels

Dear list, I am leaving my old position and now need to convert my R data frames into a format that can be used by an SPSS user replacing me, without running into conversion problems. The data set consists of strings in UTF8 encoding and values in double precision floats. The data set is not terribly large, but I had bit problems getting it into R due to the large number of unfortunate characters

"The R Inferno" is now on the Burns Statistics website at http://www.burns-stat.com/pages/Tutor/R_inferno.pdf Abstract: If you are using R and you think you're in hell, this is a map for you. Also, I've expanded the outline concerning R on the Burns Statistics 'Links' page. Suggestions (off-list) for additional items are encouraged. Patrick Burns patrick at

I'm interested in using a data frame as if it were a hash table. For instance if I had the following, > (d <- data.frame(key=seq(0.5, 3, 0.5), value=rnorm(6))) key value 1 0.5 -1.118665122 2 1.0 0.465122921 3 1.5 -0.529239211 4 2.0 -0.147324638 5 2.5 -1.531503795 6 3.0 -0.002720434 Then I'd like to be able to quickly retrieve the "value" of "key" 1.5

Hi all, why doesn't something like this does not work? speedy <- (sdata$VaR < sdata$DdtdAbs) && sdata$DdtdDuration >= qpois(pct,lambda) && sdata$Ddtd > MinDD or sdata$Ddtd[sdata$Ddtd > 0 && sdata$VaR < sdata$DdtdAbs] sdata looks like this: dataId date value Ddtd VaR DdtdAbs DdtdDuration 18948 79637 2004-07-27 10085.10

'assign' does not give a warning if 'x' has length greater than 1 -- it just uses the first element: assign(c('a1', 'a2'), 1:2) One way of thinking about this is that people using 'assign' get what they deserve. The other is that it is used seldom enough that adding a warning isn't going to slow things down appreciably. Patrick Burns patrick at

Hi R-users Can the users let me know how to do MGARCH estimate (Bivariate GARCH) and volatility forecast for 2 variables in R. thanks and regards snvk

Is there a wildcard value for vector values in r? For instance: > M <- *wildcard > (M==1) TRUE >(M=="peanut butter") TRUE >is.na(M) FALSE thanks, Francis -- Francis Smart (406) 223-8108 cell

You may recall that there was a discussion of a technical report from the statistical consulting group at UCLA. I have a draft of a comment on that report, which you can get from http://www.burns-stat.com/pages/Flotsam/uclaRcomment_draft1.pdf I'm interested in comments: corrections, additions, deletions. Patrick Burns patrick at burns-stat.com +44 (0)20 8525 0696 http://www.burns-stat.com

Hi Is it possible to subset an n-dimensional array by a vector of n dimensions? E.g. assume I have > x <- array(1:24, dim=2:4) > x[1,1,2] [1] 7 > dims <- c(1,1,2) I would like a function that I can supply x and dims as parameters to, and have it return 7. Also, I would like to do something like: > x[1,1,] [1] 1 7 13 19 > dims2<- c(1,1,NA) And have a function of x and