similar to: How to match vector with a list ?

Hi, is there any way to keep a sub matrix dimension? exemple : i1<-1; i2<-1 j1<-2; j2<-3; ret <-matrix(1,4,4)[i1:i2,j1:j2] ; dim(ret) is NULL because the submatrix single col or single row is coerce to a vector automaticaly. How can i bypass this cast : submatrix->vector ??????? Thank you. --------------------------------- [[alternative HTML version

Hi, Having 3 dataframes with different row numbers, but equal column names (see below) I want to merge them by Var1 so I've tried: merge(j1,j2,j3,by="Var1") merge(j,j1,j2,by=names("Var1")) But always got the same message: Erro en fix.by(by.x, x) : 'by' must specify column(s) as numbers, names or logical What I'm doing wrong? Thanks, Antonio j1

I am hoping someone can help translate some WinBUGS code into R code. I would like to use R to create the C[] matrix required for a car.proper model in WinBUGS, but I am having a difficult time negotiating the coding. The C matrix provides normalized weights for each pair of spatial areas. So the WinBUGS example is as follows: # of the weight matrix with elements Cij. The first J1 elements

#I have a data set that looks like this. A bit more complicated actually with # three factor levels but these calculations need to be done on one factor at a #I then have a set of different rates that are applied #to it. #dataset cata <- c( 1,1,6,1,1,2) catb <- c( 1,2,3,4,5,6) doga <- c(3,5,3,6,4, 0) data1 <- data.frame(cata, catb, doga) rm(cata,catb,doga) data1 # start rates #

Dear R People: Here is an interesting question(I think) Suppose I want to calculate Centered Moving Averages; i.e. x[1] <- ( sum(y[1:12]) )/12 x[2] <- ( sum(y[2:13]) )/12 and so on. Of course, this is easily done through loops. However, I have been trying to do this more elegantly, but have failed. I have tried things like j1 <- 1:109 j2 <- 12:120 x[1:109] <- ( sum( y[j1:j2])

hello: I have 3 data.frame objects. First df object: Of dim (149,31). Columns 2:31 are marked as T1..T14 and N1..N16. Name T1 T2 N1 T3 N2 N3 N4 T4 mu1 10 10 9 10 9 9 8 10 mu2 11 11 9 11 9 9 9 11 ... muN 12 12 9 11 9 9 8 12 Second df object: of Dim (50000,31). Columns 2:31 are maked as T1...T14 and N1..N16.

Hi James/Chris, You guys have done this before, so I'm guessing you can help me understand what's going on. If my buildbot config is: jobs=2, nt_flags=['--cflag', '-mcpu=cortex-a15', '--use-perf', '--threads=1', '--build-threads=4'] It uses -j4 for build, -j2 for running the tests:

Hi all, This is covered by (struct-path aware) TBAA, but BasicAA disagrees. See the attached testcase, where it prevents us from removing the redundant load. For arbitrary GEPs, we can't decide based on constant indices (because of e.g., &A[0][1] and &A[1][0], with *A a one-element array). BasicAA has some logic to "try to distinguish something like &A[i][1] against

Dear List: I have a data manipulation problem that I was unable to solve in R. I did it in SQL, and it may be that the solution in R is to do it in SQL, but I wondered if people could imagine a vector-based solution. Imagine a list A[i] of observers who observe some set of events B[j]. Each observer i may observe one or more events, and each event j may have been observed by one or more

Here is an alternative approach using apply(). Note that with apply() you are reversing rows or columns not indices of rows or columns so apply(junk, 2, rev) reverses the values in each column not the column indices. We actually need to use rev() on everything but the index we are interested in reversing: f2 <- function(a, wh) { dims <- seq_len(length(dim(a))) dims <-

I have some data 'myData' in wide form (attached at the end), and would like to convert it to long form. I wish to have five variables in the result: 1) Subj: factor 2) Group: between-subjects factor (2 levels: s / w) 3) Reference: within-subject factor (2 levels: Me / She) 4) F: within-subject factor (2 levels: F1 / F2) 5) J: within-subject factor (2 levels: J1 / J2) As this is the

?? > z <- array(1:24,dim=2:4) > all.equal(f(z,3),f2(z,3)) [1] "Attributes: < Component ?dim?: Mean relative difference: 0.4444444 >" [2] "Mean relative difference: 0.6109091" In fact, > dim(f(z,3)) [1] 2 3 4 > dim(f2(z,3)) [1] 3 4 2 Have I made some sort of stupid error here? Or have I misunderstood what was wanted? Cheers, Bert Bert Gunter

Dear R users, I have a few hundred .csv files which I need to put together (full outer joins on a common variable) to do a factor analysis. Each file may contain anywhere from a few hundred to a few thousand rows. What would be the most efficient way to do this in R? Please include some sample code if applicable. Thank you, b.

Greetings All! As is often the case on this list, the answer may well be under my nose but I can't see it! I am looking for a "smart" way to do the following. Say I have a vector of values, X. I set up bins" for X, say with breaks at B = c(b1,b2,...,b11) covering the range of X, i.e. bins numbered 1:10. The value x is in bin i if B[i] < x <= B[i+1] What I seek is a

I've noticed that LLVM does a bad job of optimizing array indexing code for FORTRAN arrays declared using the ALLOCATABLE keyword. For example if you have something like the following: DOUBLE PRECISION,ALLOCATABLE,DIMENSION(:,:,:,:) :: QAV ... ALLOCATE( QAV( -2:IMAX+2,-2:JMAX+2,-2:KMAX+2,ND) ) ... DO L = 1, 5 DO K = K1, K2 DO J = J1, J2 DO I = I1, I2 II = I +

Hi Jonas, > here is a patch to add Thumb call relocation to the dynamic linker. I would be happy if you could commit it to the SVN. Thanks very much for working on this. It looks like a good starting-point, but there are a couple of issues with the patch at the moment. First, it only handles RelValue up to 22 bits (depending on how you count) in size. But on ARMv6T2 onwards the J1 and J2

Hi all, general query here --- I'm about to set up an asterisk box for use in Japan but can't figureout if it's all ISDN there or what? I have gathered so far that the two major providers, NTT and KVH both offer ISDN lines with .......INS1500 and maybe INS64 protocols? Not sure... But I'm seeing stuff about J1 vs. T1/E1 .... so does that mean I can't use a Digium card it

My error. Clearly I did not do enough testing. z <- array(1:24,dim=2:4) > all.equal(f(z,1),f2(z,1)) [1] TRUE > all.equal(f(z,2),f2(z,2)) [1] TRUE > all.equal(f(z,3),f2(z,3)) [1] "Attributes: < Component ?dim?: Mean relative difference: 0.4444444 >" [2] "Mean relative difference: 0.6109091" # Your earlier example > z <- array(1:120, dim=2:5) >

Hello, These are implementations of strverscmp, scandir, alphasort and versionsort, and some test cases for them. I know these aren't in POSIX, but they're useful, nonetheless, and someone else might be interested in them. Regards, Luciano Rocha -- lfr 0/0 -------------- next part -------------- /* ----------------------------------------------------------------------- * * *

Hi all, I am struggling to work out how to use the rownames from an edited dataframe rather than the row names from the original dataframe. In my data set i'm trying to extract several rows of data on particular individuals, i don't doubt i'm using the long way round but what i have in the way of a script is this: ##selecting the IDs from the dataframe individually