similar to: using 'apply' to apply princomp to an array of datasets

See if the following helps: > m <- outer(letters[1:5], 1:4, paste, sep="") > m [,1] [,2] [,3] [,4] [1,] "a1" "a2" "a3" "a4" [2,] "b1" "b2" "b3" "b4" [3,] "c1" "c2" "c3" "c4" [4,] "d1" "d2" "d3" "d4" [5,]

Hi folks, Suppose I create the character vector charvec by > charvec<-c("a1.b1","a2.b2") > charvec [1] "a1.b1" "a2.b2" and then I use strsplit on charvec as follows: > splitlist<-strsplit(charvec,split=".",fixed=TRUE) > splitlist [[1]] [1] "a1" "b1" [[2]] [1] "a2" "b2" I was wondering

Hi everyone, I normally include a call to browser() as I'm working out the kinks in my scripts, and I am always able to step through each line by hitting "Return", but for some reason, in the scripts I'm working on now, hitting "Return" seems to cause execution of *all* the lines in my script. I've restarted R several times in case it was stuck in a bad state for

Thanks, Iain. I am willing to hear from other users whether anyone else sees this as a bug before filing it. -- Vincenzo Romano Il giorno ven 2 nov 2018, 20:03 Iain Morgan <imorgan at nas.nasa.gov> ha scritto: > If you truly intend this as a bug report, you should file it at > bugzilla.mindrot.org. > > On Fri, Nov 02, 2018 at 12:25:22 +0100, Vincenzo Romano wrote: > >

How can I select random subsets (rows!) from a data set ? If I generate simple data set > a <- data.frame(x=1:2, y = NaN, z = 2:1) > a x y z 1 1 NaN 2 2 2 NaN 1 I can select random subsets (colums) very easily using sample function: > sample(a, 2) z y 1 2 NaN 2 1 NaN I expected that using transpose of a would do the same for rows, but I am getting rather unexpected

HI. Got a question. When I assign a number of vcpus to a DomU, Are they dedicated to that VM? For example: If I have 16 vcpus available and 8 DomUs, should I assign 2 vcpus for each one? or could I assign more vcpus (i.e. 6) and the hypervisor takes care of it? Thanks -- ---------------------------------------------------------- Luis R. Romano Estudiante de Ingeniería en Computación. FCEFyN -

Vincenzo, thanks for answering !!! As I found out before that this slow down only happens for encrypted transmissions, I've followed your suggestion and tested with a https-based download, from my Nextcloud instance on my VPS. Same slow speed when connecting via IPv6, and as fast as expected when connecting via IPv4. Just to confirm: There's NO dependency/relation between openssh and

Short description: All comands sent to server in batch mode are being echoed back along with prompt. Software Version: "OpenSSH_7.9p1, OpenSSL 1.1.1 11 Sep 2018" (as printed by ssh -V) Server and client systems: ArchLinux x86_64 fully updated as of 2018-11-02. ## How to reproduce Provided that you have proper SSH key authentication in place, from command line run: echo "dir

Il giorno dom 4 nov 2018 alle ore 01:45 Ben Lindstrom <mouring at offwriting.org> ha scritto: > > I don't see it as a bug. Yes, this is why I put a question mark in the subject. > As if I'm writing a batch script I want to see the echo of the command and the output so if there is a failure I know where the failure is. I see: you have a single batch file with no

Hi everyone, I have a data frame one of whose columns is a character vector and the rest are numeric, and in debugging a script, I noticed that an ifelse call seems to be coercing the character column to a numeric column, and producing unintended values as a result. Roughly, here's what I tried to do: df: a data frame with, say, the first column as a character column and the second and

Hi everyone, I ran into the issue below while trying to execute a command of the form apply(list.names,1, function(x) F(favorite.list$x) ) where list.names is a character vector containing the names of the elements of favorite.list and F is some function defined on a list element. Namely, the $ operator doesn't treat the string variable 'x' as the string it represents, so that,

Hi folks - I'm having an issue here. I have my samba server sitting on one subnet, and the rest of the clients sitting on another (due to IP administration reasons). I assign both my clients and the server to the same workgroup, but the winboxen clients can't browse to the samba server. The win clients all have WINS resolution turned on, and I specified all of my WINS servers in

Everyone, I am looking for a utility that I can use to do a mail merge of data to a pdf image file. The image file does not have any active fields, but will be just an image file. I would like to overlay names addresses etc. We currently do this with a pcl file by just overlaying the data with pcl print positions. However, in order to get the pcl file from an original pdf file we have to

R version: 1.7.1 OS: Red Hat Linux 7.2 When "covmat" is supplied in princomp(), the output value "center" is all NA's, even though the input matrix was indeed centered. I haven't read anything about this in the help file for princomp(). See code below for an example: pc2$center is all NA's. Jerome Asselin x <- rnorm(6) y <- rnorm(6) X <- cbind(x,y)

Full_Name: Jerome Asselin Version: 1.7.1 OS: Red Hat Linux 7.2 Submission from: (NULL) (24.77.125.119) Setting the parameter na.action=na.omit should remove incomplete records in princomp. However this does not seem to work as expected. See example below. Sincerely, Jerome Asselin data(USArrests) princomp(USArrests, cor = TRUE) #THIS WORKS USArrests[1,3] <- NA princomp(USArrests, cor =

Some webpage has described prcomp and princomp, but I am still not quite sure what the major difference between them is. Can they be used interchangeably? In help, it says 'princomp' only handles so-called R-mode PCA, that is feature extraction of variables. If a data matrix is supplied (possibly via a formula) it is required that there are at least as many units as

As of R 1.7.0, princomp no longer accept matrices with more coloumns than rows. I'm curious: Why was this decision made? I work a lot with data where more coloumns than rows is more of a rule than an exception (for instance spectroscopic data). To me, princomp have two advantages above prcomp: 1) It has a predict method, and 2) it has a biplot method. A biplot method shouldn't be too

Hi all! I am working with R package cluster and I have a little problem: let's say I have two datasets...first one ("A") is divided into 4 clusters by means of Pam algorythm. Let's say I want to project the second database ("B") onto the Comp.1 X Comp.2 graph, and see where its elements are placed. The two datasets are made of different dim (54x19 and 28x19). I tried

I'm attempting to modify how biplot draws its red vectors (among other things). This is how I've started: Biplot <- function(xx, comps = c(1, 2), cex = c(.6, .4)) { ## Purpose: Makes a biplot with princomp() object to not show arrows ## ---------------------------------------------------------------------- ## Arguments: xx is an object made using princomp() ##

When I look through archives at https://stat.ethz.ch/pipermail/r-help/2003-October/040525.html I see this: Liaw, Andy wrote: >In the `Detail' section of ?princomp: > >princomp only handles so-called Q-mode PCA, that is feature extraction of >variables. If a data matrix is supplied (possibly via a formula) it is >required that there are at least as many units as variables. For