similar to: indexing an array using an index-array, but one entry being ', '

Hi. Can anyone suggest a simple way to obtain in R a list of vector coordinates of the following form? The code below is Mathematica. In[5]:= Flatten[Table[{i,j,k},{i,3},{j,4},{k,5}], 2] Out[5]= {{1,1,1},{1,1,2},{1,1,3},{1,1,4},{1,1,5},{1,2,1},{1,2,2},{1,2,3},{1 ,2,4},{1,2, 5},{1,3,1},{1,3,2},{1,3,3},{1,3,4},{1,3,5},{1,4,1},{1,4,2},{1,4,3}, {1,4,

Hi, I am running samba and lprng for 4 hp laserjets. Sometimes a samba print job goes to the wrong printer. Normally everything works just fine. Shown below is the lprng acct log file enries for the concerned print job. Please notice that the print job was supposed to go to hp4050-mail, but ended up in hp8100. Any suggestions are much appreciated. Thanks Balagopal jobstart

What is the best way to back up a zfs pool for recovery? Recover entire pool or files from a pool... Would you use snapshots and clones? I would like to move the "backup" to a different disk and not use tapes. suggestions?? TIA --Kenny -- This message posted from opensolaris.org

Hi everyone, I'm not exactly sure how to ask this question most clearly, but I hope that giving the context in which it occurs for me will help: I'm trying to compare the brain images of two patient populations; each image is composed of voxels (the 3D analogue of pixels), and I have two images per patient, one reflecting grey matter concentration at each voxel, and the other reflecting

After many months, I am now banging my head against the wall because I can't find a solution to this seemingly trivial problem.  Any help would be appreciated: I am trying to apply a nonlinear fitting routine to a 3D MR image on a voxel-by-voxel basis.  I've tested the routine using simulated data and things went well.  As for the real data, the fitting routine

I want to eufi boot this image: http://cdn-fastly.deb.debian.org/debian/dists/testing/main/installer-amd64/current/images/hd-media/boot.img.gz there is a bug against it: https://bugs.debian.org/cgi-bin/bugreport.cgi?bug=913523 I'd like to fix the resulting usb stick for my use, and also fix it in a way that can be used to fix the upstream bug. I'm trying to follow the guids

I would like to know which rows are duplicates of each other, not simply that a row is duplicate of another row. In the following example rows 1 and 3 are duplicates. > x <- c(1,3,1) > y <- c(2,4,2) > z <- c(3,4,3) > data <- data.frame(x,y,z) x y z 1 1 2 3 2 3 4 4 3 1 2 3 I can't figure out how to get R to tell me that observation 1 and 3 are the same.

I would like to know which rows are duplicates of each other, not simply that a row is duplicate of another row. In the following example rows 1 and 3 are duplicates. > x <- c(1,3,1) > y <- c(2,4,2) > z <- c(3,4,3) > data <- data.frame(x,y,z) x y z 1 1 2 3 2 3 4 4 3 1 2 3 I can't figure out how to get R to tell me that observation 1 and 3 are the same.

Dear "R" users, I have a question about the Package DierckxSpline. I have tried to find the answer by myself but it didn't worked out. I wondered if Dierckxspline can use different sets of y values in one time to fit a line with knot. I have different sets of Y values representing the same thing for different voxels (in an fmri image). I have already fitted the data in different

Hi I need to define the following c("one group" = class.weight[2], "other group" = class.weight[1]) #class.weight = c(1,2) but I don't like the hard-coded way and would like to use my.group <- array(c("one group", "other group")) but now c(my.group[1] = class.weight[2], my.group[2] = class.weight[1]) gives an error how can I solve this

again, under another subject: sorry, maybe an all too trivial question. But we have power data from J frequency spectra and to have the same range for the data of all our subjects, we just transformed them into % values, pseudo-code: power[i,j]=power[i,j]/sum(power[i,1:J]) of course, now we have a perfect linear relationship in our x design-matrix, since all power-values for each subject sum up

Dear R-users How can I get the eigenvalues out of an lda analysis? thanks a lot christoph -- Christoph Lehmann <christoph.lehmann at gmx.ch>

Hi I need to overlay two pixmaps (library (pixmap)). One, a pixmapGrey, is the basis, and on this I need to overlay a pixmapIndexed, BUT: the pixmapIndexed has set only some of its "pixels" to an indexed color, many of its pixels should not cover the basis pixmapGrey pixel, means, for this "in pixmapIndexed not defined pixels" it should be transparent. What would you

Dear R experts I have the follwoing data V1 V2 1 -5.8000000 0 2 -4.8000000 0 3 -2.8666667 0 4 -0.8666667 0 5 -0.7333333 0 6 -1.6666667 0 7 -0.1333333 1 8 1.2000000 1 9 1.3333333 1 and I want to know, whether V1 can predict V2: of course it can, since there is a perfect separation between cases 1..6 and 7..9 How can I test, whether this conclusion (being able to assign an

Based on the examples I've seen in using statistical analysis packages such as lmer, it seems that people usually tabulate all the input data into one file with the first line indicating the variable names (or labels), and then read the file inside R. However, in my case I can't do that because of the huge amount of imaging data. Suppose I have a one-way within-subject ANCOVA with

Hello list, i've got some problems getting a E1 line with a E100P up and running (germany). # cat /proc/zaptel/1 Span 1: WCT1/0 "Digium Wildcard E100P E1/PRA Card 0" HDB3/CCS/CRC4 YELLOW RED "YELLOW RED" sounds not so good. When launching asterisk, enabling pri debug on that span, i see outgoing attempts: ;---------- snip -------- > [00 01 7f ] > Unnumbered

am I right in the assumption, that for calculation of the condition numbers I have to use the correlation matrix of X, and not t(x) %*% x? > e <- eigen(t(x) %*% x) better (x must not have a first column of ones): > e <- eigen(cor(x)) > e$val [1] 6.6653e+07 2.0907e+05 1.0536e+05 1.8040e+04 2.4557e+01 2.0151e+00 > sqrt(e$val[1]/e$val) [1] 1.000 17.855 25.153 60.785 1647.478

Hi Since the 'equal slope' assumption doesn't hold in my data I cannot use a proportional odds model ('Design' library, together with 'Hmisc'). I would like to try therefore a partial proportional odds model Please, could anybody tell me, where to find the code and how to specify such a model ..or any potential alternatives many thanks for your kind help christoph

Hi It seems, I just miss something. I defined treshold <- function(pred) { if (pred < 0.5) pred <- 0 else pred <- 1 return(pred) } and want to use apply it on a vector sapply(mylist[,,3],threshold) but I get: Error in match.fun(FUN) : Object "threshold" not found thanks for help cheers chris -- Christoph Lehmann <christoph.lehmann at gmx.ch>

Hi (1)In polr(), is there any way to calculate a pseudo analogue to the R^2. Just for use as a purely descriptive statistic of the goodness of fit? (2) And: what are the assumptions which must be fulfilled, so that the results of polr() (t-values, etc.) are valid? How can I test these prerequisites most easily: I have a three-level (ordered factor) response and four metric variables. many