similar to: Not all files synched - hard link problems???

Someone can help me? I tried several things and always don't converge # Model library(sem) dados40.cov <- cov(dados40,method="spearman") model.dados40 <- specify.model() F1 -> Item11, lam11, NA F1 -> Item31, lam31, NA F1 -> Item36, lam36, NA F1 -> Item54, lam54, NA F1 -> Item63, lam63, NA F1 -> Item65, lam55, NA F1 -> Item67, lam67, NA F1 ->

Hi, Here's the data we have: > rs[1:5,] probe_id f1 f2 f3 f4 M A f 1 A_68_P20002076 2 58 0 0 1.51778114 6.344453 59 2 A_68_P20002775 22 8 15 0 0.43419304 5.488819 59 3 A_68_P20005791 43 3 0 0 0.05698666 9.830594 59 4 A_68_P20005805 11 34 0 0 1.71076835 6.624038 59 5 A_68_P20006729 16 44 0 0 0.85498261 6.044229 59 I want rs$f be the max of f1, f2, f3,

Hello, FYI, this is a bug http://llvm.org/bugs/show_bug.cgi?id=13324 When compiling the following code for sm_20, func params are by some reason given with .align 0, which is invalid. Problem does not occur if compiled for sm_10. > cat test.ll ; ModuleID = '__kernelgen_main_module' target datalayout = "e-p:64:64-i64:64:64-f64:64:64-n1:8:16:32:64" target triple =

Hi, I have the following table data: f1, f2, f3, f4. I want to compute the counts of unique combinations of f1-f4. In SQL I would just write: SELECT COUNT(*) FROM <table> GROUP BY f1, f2, ..,f4. How to do this in R? Thanks, Nick -- View this message in context: http://www.nabble.com/Group-by-in-R-tp23020587p23020587.html Sent from the R help mailing list archive at Nabble.com.

Dear all, In the following code, I was trying to compute each row of the "param" iteratively based on the first row. This likely is not the best way. Can anyone suggest a simpler way to improve the code. Thanks a lot! Hannah param <- matrix(0, 11, 5) colnames(param) <- c("p", "q", "r", "2s", "t") param[1,]

Hello all - I have an example column in a dataFrame id.name 123.45 123.45 123.45 123.45 234.56 234.56 234.56 234.56 234.56 234.56 234.56 345.67 345.67 345.67 456.78 456.78 456.78 456.78 456.78 456.78 456.78 456.78 456.78 ... [truncated] And I'd like to create a second vector of sequential values (i.e., 1:N) for each unique id.name value. In other words, I need id.name x 123.45 1 123.45

For some time I have been using rsync to backup data between different machines and my NAS drive. But within the last 2 days I have found out that rsync is not removing old files from destination - directories renamed or removed from source. In this example I want to sync files on my Debian Linux server to a NAS drive. NAS drive is mounted using smbmount. Using "-avhzn" dry-run it

I am trying to add a constant to the previous value of a variable based on certain conditions. Maybe there is a simple way to do this that I am missing completely. I have given an example below: df <- data.frame(x = c(1,2,3,4,5), y = c(10,20,30,NA,NA)) > df x y 1 1 10 2 2 20 3 3 30 4 4 NA 5 5 NA I want to add 2 to the previous value of y, if x exceeds 3 (also will have to handle NAs in

Dear all, I am trying to repeat an example from Sokal and Rohlfs "Biometry" -- Box 11.4, example of a randomized-complete-blocks experiment. The data is fairly simple: series genotype weight 1 pp 0.958 1 pb 0.985 1 bb 0.925 2 pp 0.971 2 pb 1.051 2 bb 0.952 3 pp 0.927 3 pb 0.891 3 bb 0.892 4

Hi, I have a data frame where one column is a list of lists. I would like to subset the data frame based on membership of the lists in that column and be able to 'denormalise' the data frame so that a row is duplicated for each of its list elements. Example code follows: # The data is read in in this form with the c2 list values in single strings which I then split to give lists: > f1

Dear R-helpers, To get curves for a pseudo cohort other than the one centered at the mean of the covariates, I have been trying to use the newdata argument to survfit with no success. Here is my model statement, the newdata and the ensuing error. What am I doing wrong? > summary(fit) Call: coxph(formula = Surv(Start, Stop, Event, type = "counting") ~ Week + LagAOO + Prior.f +

Hi, I need to extract the second largest element from each row of a matrix. Below is my solution, but I think there should be a more efficient way to accomplish the same, or not? set.seed(1) a <- matrix(rnorm(9), 3 ,3) sec.large <- as.vector(apply(a, 1, order, decreasing=T)[2,]) ans <- sapply(1:length(sec.large), function(i) a[i, sec.large[i]]) ans Thanks in advance for your

> -----Original Message----- > From: Rotem, Nadav [mailto:nadav.rotem at intel.com] > Sent: Saturday, July 30, 2011 6:51 AM > To: Gregory Junker > Subject: RE: [LLVMdev] "Cannot select" error in 2.9 > > Can you reduce the test with bug-point ? Does it work on ToT ? Hi Nadav I'm not sure what those are -- can you clarify? Thanks Greg

Hi, I have big .csv file. I would like to filter that file into a new table. For example, I have .csv file as below: f1 f2 f3 f4 f5 f6 f7 f9 f10 f11 t1 1 0 1 0 1 0 0 0 0 1 t2 1 0 0 0 0 1 1 1 1 1 t3 0 0 0 0 0 0 0 0 0 0 t4 1 0 0 0 1 0 0 0 0 0 t5 0 0 0 0 0 0 0 0 0 0 t6 0 0 0 0 0 0 0 0 0 0

This might be a trivial question, but I would appreciate if anybody could suggest an elegant way of plotting a function such as the following (a simple distribution function): F(x) = 0 if x<=0 =(x^2)/2 if 0<x<=1 =2x-((x^2)/2)-1 if 1<x<=2 =1 if x>2 This is just an example. In this case it is a continuous function. But how to do it in general in an elegant way.

Hi r-users,   I have the following code to solve 4 simultaneous eqns with 4 unknowns using newton iteration method.  But I got the error message:   pars <- c(1.15, 40, 50, 0.78) newton.input2 <- function(pars) {  ## parameters to estimate      alp <- pars[1]    b1  <- pars[2]     b2  <- pars[3]    rho <- pars[4]   f1 <- pars[1]*pars[2] f2 <-

That's very nice, Hadley. Simple and clean. Never would have thought of it myself. As usual, however, in the course of my churnings, I have a further complication to add. But first ... **TO ALL**: Feel free to ignore the following, as I'm just fooling around here and don't want to waste your time with my stupid stuff. Anyway, the complication is motivated by the use of formals() or

Hi I'm trying to set up a simulation problem without resorting to (m)any loops. I want to set entries in a data frame of zeros ('starts' in the code below) to 1 at certain points and the points have been randomly generated and stored in a separate data.frame ('sl'), which has the same number of columns. An example of the procedure is as follows: ml <-

Exec. Summary: step() basically ``fails'' whereas MASS' stepAIC() does work This may not be a bug in the strictest sense, but at least something for the wish list. Unfortunately I have no time currently to investigate further myself but want to be sure this won't be forgotten: The example is using a real data set with 216 observations on 9 variables -- where we have

Hello, I am dealing with numeric vectors 10^5 to 10^6 elements long. The values are sorted (with duplicates) in the vector (v). I am obtaining the length of vectors such as (v < c) or (v > c1 & v < c2), where c, c1, c2 are some scalar variables. What is the most efficient way to do this? I am using sum(v < c) since TRUE's are 1's and FALSE's are 0's. This