similar to: CUPS and virtual interfaces

Hi, I'm trying to use Frank Harrell's Design:::ols function to do regression of y (numeric) on the interaction of two factors (x1 and x2), but Lapack throws an error: > library(Design) ... > load(url("http://www.csse.unimelb.edu.au/~gabraham/x")) > ols(y ~ x1 * x2, data=x) Error in chol2inv(fit$qr$qr) : 'size' cannot exceed nrow(x) = 20 > traceback()

I have Samba PDC and use tdbsam backend. I use the version 3.0.11, but recently I have exchanged it for the version 3.0.23c. Now I have a number of problem. Here is one of then. I wish to move one user "gad" from Domain Users (RID 513) to Domain Guests (RID 514). Now Primary group of user "gad" is "Domain Users": pdbedit -Lv gad -d0 Unix username: gad NT

I manage a bunch of workstations at the Wendell Free Library. They are all diskless, boot via PXE and mount all of their file systems via NFS from a server. All of the machines are 32-bit and run CentOS (fully up-to-date running 5.10). There are two printers with queues managed on the server. The server 'shares' these printers on the local LAN (eg with all of the workstations).

Hello Everyone,   I've been learning to use R in my spare time over the past several months. I've read about 7-8 books on the subject. Lately I've been testing what I've learned by trying to replicate the analyses from some of my SAS books. This helps me make sure I know how to use R properly and also helps me to understand how the two programs are similar and different.   Below is

Hi, Can anyone explain how the standard error in arima() is calculated? Also, how can I extract it from the Arima object? I don't see it in there. > x <- rnorm(1000) > a <- arima(x, order = c(4, 0, 0)) > a Call: arima(x = x, order = c(4, 0, 0)) Coefficients: ar1 ar2 ar3 ar4 intercept -0.0451 0.0448 0.0139 -0.0688 0.0010 s.e.

Hi, Is this a bug in truehist()? > library(MASS) > x <- rep(1, 10) > truehist(x) Error in pretty(data, nbins) : invalid 'n' value Thanks, Gad > R.version platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 4.1 year 2006 month 12 day 18 svn

Hi, Is this a bug in truehist()? > library(MASS) > x <- rep(1, 10) > truehist(x) Error in pretty(data, nbins) : invalid 'n' value Thanks, Gad > R.version platform i486-pc-linux-gnu arch i486 os linux-gnu system i486, linux-gnu status major 2 minor 4.1 year 2006 month 12 day 18 svn

Hi, I'm using survreg() from the survival package for parametric survival regression (modelling inter-arrival times of patients to a waiting list as exponentially distributed, with various regressors such as queue size and season). Does anyone know which algorithm survreg() uses for this? Thanks, Gad -- Gad Abraham Department of Mathematics and Statistics The University of Melbourne

Hi, I'm trying to plot several lag.plots on a page, however the second plot replaces the first one (although it only takes up the upper half as it should): par(mfrow=c(2,1)) a<-sin(1:100) b<-cos(1:100) lag.plot(a) lag.plot(b) What's the trick to this? I'm using R 2.2.1 (2005-12-20 r36812) on Ubuntu Linux. Thanks, Gad -- Gad Abraham Department of Mathematics and

Hi, I'm using zoo because it can automatically label the months of a time series composed of daily observations. This works well for certain time series lengths, but not for others, e.g.: While: > library(zoo) > plot(zoo(runif(10), as.Date("2005-06-01") + 0:50)) Shows up the months and day of month, > plot(zoo(runif(10), as.Date("2005-06-01") + 0:380))

Hi, I'm using Ubuntu Hardy i386, and the R 2.7.1 Ubuntu packages from CRAN. The CRAN r-base-dev package depends on refblas3-dev or atlas3-base-dev, but octave3.0-headers depends on libblas-dev. The two blas packages seem to conflict, so r-base-dev and octave3.0-headers can't be installed together. Is this a known issue? Thanks, Gad $ sudo apt-get install octave3.0-headers Reading

Hi, I'd like to store large covariance matrices using Matrix classes. dsyMatrix seems like the right one, but I want to specify just the upper/lower triangle and diagonal and not have to instantiate a huge n^2 vector just for the sake of having half of it ignored: Dumb example: M <- new("dsyMatrix", uplo="U", x=rnorm(1e4), Dim=as.integer(c(100, 100))) diag(M) <- 1

Hi, I'm doing PCA on wide matrices and I don't understand why calling predict.prcomp on it throws an error: > x1 <- matrix(rnorm(100), 5, 20) > x2 <- matrix(rnorm(100), 5, 20) > p <- prcomp(x1) > predict(p, x2) Error in predict.prcomp(p, x2) : 'newdata' does not have the correct number of columns > dim(x2) [1] 5 20 > dim(p$rotation) [1] 20 5

Hi, I'm trying to do PCA on a n by p wide matrix (n < p), and I'd like to get more principal components than there are rows. However, svd() only returns a V matrix of with n columns (instead of p) unless the argument nv=p is set (prcomp calls svd without setting it). Moreover, the eigenvalues returned are always min(n, p) instead of p, even if nv is set: > x <-

Hi, I'm using Ubuntu 9.10 amd64 with cran2deb packages (I know it's meant for Debian, it's worked fine for me for many months). Recently apt-get update has to started to complain: ... Hit http://debian.cran.r-project.org testing/ Release Get:1 http://debian.cran.r-project.org testing/ Packages [515kB] Fetched 1B in 3s (0B/s) W: Failed to fetch

Hi, I have two example packages, test1 and test2, where the only code in them is: setGeneric("predict", function(object, ...) standardGeneric("predict")) (get them from http://www.cs.mu.oz.au/~gabraham/test1.tar and http://www.cs.mu.oz.au/~gabraham/test2.tar) The difference between them is that first does not have a namespace, and loads fine. The second has a namespace

hi. I am trying to get print working and have a hard time indeed... My goal is to replace our nt4 print server with a linux/samba one as we have problems serving printers and drivers to win2000 workstations (and I don't want to set up a win2000 server for printing, and have the same problem _again_ when switching to XP ;-) The situation so far : - Debian woody - Samba 2.2.4-1 - Winbind

Hi, I'm using natural cubic splines from splines::ns() in survival regression (regressing inter-arrival times of patients to a queue on queue size). The queue size fluctuates between 3600 and 3900. I would like to be able to run predict.survreg() for sizes <3600 and >3900 by assuming that the rate for <3600 is the same as for 3600 and that for >4000 it's the same as for

Hi, In the boot package, the original statistic is simply the statistic function evaluated on the original data (called t0). However, in Harrell et al 1996 "Multivariable prognostic models..." Stats Med vol 15, pp. 361--387, it is different (p. 372): The statistic function evaluated on the original data is called "D_app" (apparent statistic), whereas "D_orig"

Hi, Design isn't strictly an R base package, but maybe someone can explain the following. When lrm is called within a function, it can't find the dataset dd: > library(Design) > age <- rnorm(30, 50, 10) > cholesterol <- rnorm(30, 200, 25) > ch <- cut2(cholesterol, g=5, levels.mean=TRUE) > fit <- function(ch, age) + { + d <- data.frame(ch, age) +