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...gth(svd(x)$d) [1] 3 > dim(svd(x, nv=5)$v) [1] 5 5 > length(svd(x, nv=5)$d) [1] 3 > Is there a way of getting more PCs and eigenvalues than rows? Is the eigen-decomposition of the covariance matrix really that numerically bad? (i.e., eigen(cov(x)) ) Thanks, Gad -- Gad Abraham Dept. CSSE and NICTA The University of Melbourne Parkville 3010, Victoria, Australia email: gabraham at csse.unimelb.edu.au web: http://www.csse.unimelb.edu.au/~gabraham

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() 6: .Call("La_chol2inv", x, size, PACKAGE = "base") 5: chol2inv(fit$qr$qr) 4: ols(y ~ x1 * x2, data = x) 3: eval.with.vis(e...

...; does not have the correct number of columns > dim(x2) [1] 5 20 > dim(p$rotation) [1] 20 5 All predict.prcomp really does is x2 %*% p$rotation, which is a perfectly legal operation that should yield a 5x5 matrix: > dim(x2 %*% p$rotation) [1] 5 5 Thanks, Gad -- Gad Abraham Dept. CSSE and NICTA The University of Melbourne Parkville 3010, Victoria, Australia email: gabraham at csse.unimelb.edu.au web: http://www.csse.unimelb.edu.au/~gabraham

...sn't work: M <- new("dsyMatrix", uplo="U", x=0, Dim=as.integer(c(100, 100))) Error in validObject(.Object) : invalid class "dsyMatrix" object: length of x slot != prod(Dim) Is there an easier way of doing this? Thanks, Gad -- Gad Abraham PhD Student, Dept. CSSE and NICTA The University of Melbourne Parkville 3010, Victoria, Australia email: gabraham at csse.unimelb.edu.au web: http://www.csse.unimelb.edu.au/~gabraham

...v libfftw3-dev libhdf5-serial-dev liblapack-dev Suggested packages: libhdf5-doc The following packages will be REMOVED: r-base-dev refblas3-dev The following NEW packages will be installed: libblas-dev libfftw3-dev libhdf5-serial-dev liblapack-dev octave3.0-headers -- Gad Abraham Dept. CSSE and NICTA The University of Melbourne Parkville 3010, Victoria, Australia email: gabraham at csse.unimelb.edu.au web: http://www.csse.unimelb.edu.au/~gabraham

...B] Fetched 1B in 3s (0B/s) W: Failed to fetch http://debian.cran.r-project.org/cran2deb/debian-amd64/testing/Packages.bz2 Hash Sum mismatch My /etc/apt/sources contains: deb http://debian.cran.r-project.org/cran2deb/debian-amd64 testing/ Any idea? Thanks, Gad -- Gad Abraham PhD Student, Dept. CSSE and NICTA The University of Melbourne Parkville 3010, Victoria, Australia email: gabraham at csse.unimelb.edu.au web: http://www.csse.unimelb.edu.au/~gabraham

...sessionInfo() R version 2.8.1 (2008-12-22) i386-apple-darwin8.11.1 locale: en_AU.UTF-8/en_AU.UTF-8/C/C/en_AU.UTF-8/en_AU.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] test2_0.1 -- Gad Abraham MEng Student, Dept. CSSE and NICTA The University of Melbourne Parkville 3010, Victoria, Australia email: gabraham at csse.unimelb.edu.au web: http://www.csse.unimelb.edu.au/~gabraham

...PATH from file bin/exec/R) trying path=/usr/local/apps/libiconv-1.11/lib/libiconv.so.2 libiconv.so.2 => /usr/local/apps/libiconv-1.11/lib/ libiconv.so.2 [snip] I don't know what else to try. Anyone? Regards, -- Lucas Barbuto E: lucasjb at csse.unimelb.edu.au System Administrator T: +613 8344 1270 Department of CSSE The University of Melbourne http://www.csse.unimelb.edu.au/

...ll'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) > load(url("http://www.csse.unimelb.edu.au/~gabraham/data2.Rdata")) > l <- lrm(y ~ X, penalty=100, tol=1e-13) Error in solvet(info.matrix, tol = tol) : apparently singular matrix > traceback() 4: stop("apparently singular matrix") 3: solvet(info.matrix, tol = tol) 2: fitter(X, Y, initial = f$coef, m...

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

...al distribution. Given that Flac is much more advanced in other respects, i wonder if you are interested in using bonk's encoding scheme? The relevant file is utility.h in http://yoyo.cc.monash.edu.au/~pfh/bonk/bonk-0.6.tar.gz. I've put a draft description of the encoder here: http://www.csse.monash.edu.au/~pfh/random/encoder.pdf regards, Paul Email: pfh@csse.monash.edu.au one ring, no rulers, thecircle.org.au

...ing together and what is needed. Cheers, Ryan. -- Ryan McConigley - Systems Administrator _.-, Computer Science University of Western Australia .--' '-._ Tel: (+61 8) 6488 7082 - Fax: (+61 8) 6488 1089 _/`- _ '. Ryan[@]csse.uwa.edu.au - http://www.csse.uwa.edu.au/~ryan '----'._`.----. \ ` \; "You're just jealous because the voices are talking to me" ;_\

...use the same center and scale vectors from the training set: x.test.pc <- predict(p, newdata=x.test, center=p$center, scale=p$center) or use the training set's own centers and scales: x.test.pc <- predict(p, newdata=x.test, center=TRUE, scale=TRUE) Thanks, Gad -- Gad Abraham Dept. CSSE and NICTA The University of Melbourne Parkville 3010, Victoria, Australia email: gabraham at csse.unimelb.edu.au web: http://www.csse.unimelb.edu.au/~gabraham

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]]

Hi, We're using stats4 for a logistic regression. The code is chdreg.logit2 <- glm(chd ~ age + sex, family = binomial) summary(chdreg.logit2) oddsratios <- coef(chdreg.logit2) exp(oddsratios) # Calculate model predicted values pred <- predict(chdreg.logit2,type="response") The glm part runs fine, and up to now so has the predict function. However, now we're

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

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

...ase packages: [1] splines stats graphics grDevices utils datasets methods [8] base other attached packages: [1] Design_2.1-1 survival_2.34 Hmisc_3.4-3 loaded via a namespace (and not attached): [1] cluster_1.11.9 grid_2.6.2 lattice_0.17-4 rcompgen_0.1-17 -- Gad Abraham Dept. CSSE and NICTA The University of Melbourne Parkville 3010, Victoria, Australia email: gabraham at csse.unimelb.edu.au web: http://www.csse.unimelb.edu.au/~gabraham

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