similar to: Multiple lag.plots per page

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, 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 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 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'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 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, 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 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 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'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, 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 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, 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, Say I have two packages, test1 and test2, that both define the generic method train (identical definition), and each has a specific train method for a different S4 object (foo and bar, resp.) I want to be able to call train(foo, x, y) and train(bar, x, y), which doesn't work since test2 masks test1, as seen below. The two solutions I can think of are to a) prefix train,

Hi Could anybody give me a bit of advice on some code I'm having trouble with? I've been trying to calculate the loglikelihood of a function iterated over a data of time values and I seem to be experiencing difficulty when I use the function expm(). Here's an example of what I am trying to do y<-c(5,10) #vector of 2 survival times p<-Matrix(c(1,0),1,2) #1x2 matrix

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"

Dear all, The standard call to ARIMA in the base package such as arima(y,c(5,0,0),include.mean=FALSE) gives a full 5th order lag polynomial model with for example coeffs Coefficients: ar1 ar2 ar3 ar4 ar5 0.4715 0.067 -0.1772 0.0256 -0.2550 s.e. 0.1421 0.158 0.1569 0.1602 0.1469 Is it possible (I doubt it but am

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 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,