similar to: ARIMA standard error

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'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 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

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, 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'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 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 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 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 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 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, 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

Hello, I have an elementary question (for which I couldn't find the answer on the web or the help): how can I extract the mode (modal score) of a vector? Thanks in advance for your help. [[alternative HTML version deleted]]

Hi R helpers, I'm fitting large number of single factor logistic regression models as a way to immediatly discard factor which are insignificant. Everything works fine expect that for some factors I get error message "Singular information matrix in lrm.fit" which breaks whole execution loop... how to make LRM not to throw this error and simply skip factors with singularity

Hi R-users I have two conditions. For each condition, 100 sets of 10 random numbers from N(0,1) need to be generated. Here is my question. At the begining I specify a seed number. I want to make the 100th set of the first condition and 1st set of the second conditon the same. What do I need to do ? After generating 99th set of 10 random numbers and then saving .Random.seed then using

Hi all, I have some residuals from regression, and i suspect they have correlations in them... I am willing to cast the correlation into a ARMA(p, q) framework, what's the best way to identify the most suitable p, and q, and fit ARMA(p, q) model and then correct for the correlations in regression? I know there are functions in R, I have used them before, but I just want to see if I can do