similar to: split the data

I want to sample from the ID. For each ID, i want to have 2 set of data. I try the sample() function but it didn't work. > x<-data.frame(id=c(1,1,1,2,2,2,2,3,3,3,4,4), v1=c(1:12), V2=c(12:23)) > x id v1 V2 1 1 1 12 2 1 2 13 3 1 3 14 4 2 4 15 5 2 5 16 6 2 6 17 7 2 7 18 8 3 8 19 9 3 9 20 10 3 10 21 11 4 11 22 12 4 12 23 -- View this message in

i am trying to convert sas file into csv. I used write.csv(a, file="cool.csv") but nothing come out. i don't know why. Thanks. library(Hmisc) a<- sasxport.get("C:\\Users\.....") write.csv(a, file="cool.csv") -- View this message in context: http://r.789695.n4.nabble.com/convert-the-sas-file-into-csv-in-R-tp3311769p3311769.html Sent from the R help mailing

Hello, If I want to see how, say, apply function is written, how would I be able to do that? Just typing "apply" at the prompt does not work. Thank you for help! Sergey

As part of my work, I am trying to append matrices onto data frames. Naively I assumed that when rbinding a data.frame and matrix, the matrix would be coerced and appended, keeping the names from the data frame. Clearly, I am not fully understanding the process by which rbind works. Example code: > A<-data.frame(1,1,1); names(A)=letters[1:3] ; B<-matrix(0,2,3) > rbind(A,B)

Hi! Consider d <- data.frame(x=1:10,y=5+1:10, yf=rnorm(10,5+1:10)) x y yf 1 1 6 5.268621 2 2 7 8.623896 3 3 8 8.114830 4 4 9 10.125955 5 5 10 9.977261 ... I plot y and yf against x with xyplot(y+yf~x,data=d,col=c('red','green'),pch=c("a","b")) BUT - I would like that the plot of y against x is with type='l' and the

Hi, I have a data frame that I want to split into two based on the values of a variable in it. The variable Y has numeric values ranging between 0 through 70. I want to plot the frequencies of another variable X in two different cases: - When Y = 0 and - When Y > 0 How does one go about doing this? In general, I want to do several analyses with this data frame that are a variation of the

I would like to use lattice graphics to plot multiple functions (or groups or subpopulations) on the same plot region, using different line types "lty" or colors "col" to distinguish the functions (or groups). In traditional graphics, this seems straightforward: First plot all the data using 'type="n"', and subsequently execute a series of "points"

https://bugzilla.mindrot.org/show_bug.cgi?id=2699 Bug ID: 2699 Summary: PKCS#8 private keys with AES-128-CBC stopped working Product: Portable OpenSSH Version: 7.5p1 Hardware: amd64 OS: Linux Status: NEW Severity: normal Priority: P5 Component: ssh-keygen Assignee:

I'm having trouble creating a looping variable and i can't see wher ethe problem arises from any hep gratfully appreciated First create a table x<-table(SURVEY$n_0,exposed) > x exposed False True Under 16 24 1 16-19 68 9 20-24 190 37 25-34 555 204 35-44 330 87 45-54 198 65 55-64 67 35 65+

Before re-inventing the wheel I would like to ask: does anyone know about an optimizer in R which can reliably identify which value of X (Xopt) leads to Y (Yopt) closest to Ytarget in Y <- MonotoneStepFun(X) optionally with the restriction that Yopt <= Ytarget (at least if any Y <= Ytarget, otherwise any Yopt > Ytarget would be the preferred answer) If none is known, I will write

Dear R-List, I?m new in R, so I hope my question is not to primitive, but I haven?t found a solution in the R-help. I?ve got a datatframe with 3 factors, called xf (9 levels), yf (9 levels), zf (3 levels) and one variable (rt): > xf yf zf rt > 1 1 1 67 > 1 1 1 56 > 1 1 1 60 [...] > 1 1 2 58 > 1 1 2 61 [...] > 9 1

Hi all, I am running R version 2.4.0 (2006-10-03) on an i686 pc with Mandrake 10.2 Linux. I was given a binary data file containing single precision numbers that I would like to read into R. In a previous posting, someone suggested reading in such data as double(), which is what I've tried: > zz <- file(file, "rb") > h1 <- readBin(con = zz, what = double(), n = 1, size

I believe there is a memory leak in isoreg in the current version of R, as I believe the following shows > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 120405 3.3 350000 9.4 350000 9.4 Vcells 78639 0.6 786432 6.0 392463 3.0 > for(k in 1:100) { + + y <- runif(10000) + isoreg(x,y) + } > rm(x) > rm(y) > gc() used (Mb) gc

Dear R folks: I wonder anyone has a elegent way of doing what I need to do. I have a data frame called with four columns: V1, V2, A1 and A2: V1 V2 A1 A2 A B 1.2 2.0 A D 1.2 4.0 A C 2.4 2.2 What I need to do is to convert it into the following data frame with a new column x, where x is just the stacked up of A1 and A2 placed with respective V1 and V2 in the first two

Thank you for your hint. I really mean I am planning to store millions of files on the file system. Then may I ask that what is the maximum number of files which could be stored in one directory without affecting the performance of web server? At 2018-11-03 16:03:56, "Walter H." <Walter.H at mathemainzel.info> wrote: >On 03.11.2018 08:44, yf chu wrote: >> I have

Full_Name: Petr Klasterecky Version: 1.8.1 OS: Windows XP, Linux Submission from: (NULL) (195.113.27.212) The isoreg() function causes R to crash when called repeatedly. Consider the following simple script: { library(modreg) N <- 10 x <- rnorm(N) print("Original x values:") print(x) for(n in (1:N)){print(y <- isoreg(x[1:n])$yf)} } I am able to run (call) it several

How can I pass an array to a define? It''s not documented in the puppet language guide. I''ve got: define lvm::create_vg ( $pvdisks ) { exec { ''pvcreate'': command => "/sbin/pvcreate -yf $pvdisks", unless => "/sbin/pvdisplay $pvdisks", ... } } class someclass { lvm::create_vg {

Hi, when I apply a glm() model in two ways, first with the response in a two column matrix specification with successes and failures y <- matrix(c( 5, 1, 3, 3, 2, 2, 0, 4), ncol=2, byrow=TRUE) X <- data.frame(x1 = factor(c(1,1,0,0)), x2 = factor(c(0,1,0,1))) glm(y ~ x1 + x2, data = X, family="binomial") second with a model matrix that

Hi, That sounds simple but I cannot think of a really fast way of getting the following: c(1,1,2,2,3,3,4,4) would give c(1,3,5,7) i.e., a function that returns the indexes of the first occurrences of numbers. Note that numbers may have any order e.g., c(3,4,1,2,1,1,2,3,5), can be very large, and the vectors are also very large (which prohibits any loop). The best I could think of is: tmp =

I am running the following nls equation. I tried it with data that excel was fitting and got the error: singular gradient matrix at initial parameter estimates I thought it was due to a low number of points (6), but when I create a dataset, I get the same problem. If I remove the parameter "a," then it can find a solution. Does anyone know what I can do to fit this model?