similar to: Handling masked methods

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'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()

Hi, Again I'm doing logistic regression using lrm from Harrell's Design package, but on wide matrices (28 observations, 1891 variables) so L2 penalisation is used. I get the following error, although I've tried different penalties and different tolerances. The X matrix is scaled and centred. > library(Design) >

Hi, I have an RData file containing a GeneSetCollection object (Bioconductor), http://www.cs.mu.oz.au/~gabraham/c2.RData. I think it uses lazy loading because packages are only loaded when I access the object (see below) in the R console. When I try the same with Rscript, it segfaults. This happens on 2.9.0 both on Linux and Mac: Rscript -e 'load("c2.RData"); c2[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 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'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'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, Say x.train is a matrix of covariates that I want to do PCA on, so I can do regression on its principal components, and x.test is a test set of the same covariates on which I want to evaluate the regression fit. I would like the covariates to be centred and scaled: p <- prcomp(x.train, center=TRUE, scale=TRUE) x.train.pc <- predict(p) Now I want to get the PCs from the test set.

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) +

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, 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, 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 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 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, 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 latex() from Frank Harrell's Hmisc library to produce LaTeX files. By default, it calls xdvi and displays the dvi. How can I make xdvi not show? I couldn't find a clue in the extensive documentation. Thanks, Gad ps: Hmisc 3.3-1 on R 2.5.0 for Linux. -- Gad Abraham Department of Mathematics and Statistics The University of Melbourne Parkville 3010, Victoria,

Hi, I'm performing (blocked) 10-fold cross-validation of a several time series forecasting methods, measuring their mean squared error (MSE). I know that the MSE_cv is the average over the 10 MSEs. Is there a way to calculate the standard error as well? The usual SD/sqrt(n) formula probably doesn't apply here as the 10 observations aren't independent. Thanks, Gad -- Gad