similar to: help with predict in stats4

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 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, 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 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, 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 want to use R to do user-submitted jobs in a (java-based) webapp. Specifically, I want * users to upload R scripts * run the R job on user data * save the results to database I'm concerned about sandbox issues. * Is it possible to disable file read/write capability? * Can I prevent the user from loading packages (e.g. the database package). * Can I have users work on separate data

I am new to 'R' and also new to the concept of a 'Hessian' with non-linear optimization. I would like to avoid going through all of the reference articles given with ?optim as access to a library is not handy. Would someone be able to elighten me on what is in the Hessian matrix if 'hessian = TRUE' with optim? The documentation indicates that this is a numerically

Hi! Is there any package or function on R to ARMA models (Box & Jenkins, without sazonality and trend) with resources to automatic identification for p and q ? Regards, Raphael Saldanha Brazil [[alternative HTML version deleted]]

Hello List, My question is an elementary one. I have run a fuzzy kmeans cluster using FANNY to group freshwater fish assemblages. I then went in the field to validate that classification and have retrieved new assemblage data for a new suite of streams. Therefore I would like to use Predict to determine how well the original clustering fits the new data. However I have not figured out a

Hi, I have been running the ccf() function to find cross-correlations of time series across various lags. When I give the option of plot=TRUE, I get a plot that gives me 95% confidence interval cut-offs (based on sample covariances) for my cross-correlations at each lag. This gives me a sense of whether my cross-correlations are statistically significant or not. However, I am unable to get R to

Hi everyone, This is not so much of an R question as a statistics question. I currently work for the largest pre employment screening company in Canada. Upper management has noticed that noticed that usually a month or so before any big kind of economic shock happens, that our incoming files (requests for a background check) jump up or down. As the company statistician, they've asked me

After doing a PCA using princomp, how do you view how much each component contributes to variance in the dataset. I'm still quite new to the theory of PCA - I have a little idea about eigenvectors and eigenvalues (these determine the variance explained?). Are the eigenvalues related to loadings in R? Thanks, Paul -- View this message in context:

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

Dear all, I have a few questions regarding the 64 bit version of R and the cache memory R uses. ----------------------------------- Computer & software info: OS: kUbuntu Feasty Fawn 7.04 (64-bit) Processor: AMD Opteron 64-bit R: version 2.7.0 (64-bit) Cache memory: currently 16 GB (was 2 GB) Outcome of 'limit' command in shell: cputime unlimited, filesize unlimited, datasize

Hello R-help list, I have a piece of code written by a grad student here at BU which will segfault when using one data set, but complete just fine using another. Both sets are just text files full of real numbers. It seems like a bug within R. It could be a bug within her data, but again, her data is just a bunch of floats, so her data could be triggering a bug within R. I have tried this

Hi all, I have just found out that the machine learning group in our Faculty has a lot of spare capacity on their FreeNX servers. I do not know a lot about these beasts but I understand that they are a free version of something produced by a firm called "NoMachine". They are designed for executing parallel algorithms and I thought that they might be of use in a project of mine

I'm curious if there are users of RPy on this list. I've recently created a gui front end using Tkinter for some python scripts I've written for some of our internal operations and I am quite pleased with how this program works. I wonder if it is possible to also get this gui to run R functions through the use of RPy. Going even a step further, I wonder if it is possible to get this