search for: softhelp

Dear all, I didn't find any graphical solution in the package "mva" to plot the canonical scores from a CCA (canonical correlation analysis). Does anybody knows how to plot or has anybody already programmed : - the map of the canonical scores, - the graph of the canonical weights, - the correlation circle i.e. the canonical loadings ? Thank you for help ...

A colleague has just passed me this interesting address: http://cc.oulu.fi/~jarioksa/softhelp/vegan.html "Vegan: R functions for vegetation ecologists" "Vegan package is intended to help vegetation ecologists and other community ecologists to use R. It is not a completely self-contained package, but it complements other R functions. .../... At this first stage, vegan impl...

...WiSP/ ape www.stat.uni-muenchen.de/~strimmer/ publications/ape2003.pdf phylogr http://www.stat.ucl.ac.be/ISdidactique/Rhelp/library/PHYLOGR/html/00Index.html genetics cran.r-project.org/doc/packages/genetics.pdf VEGAN http://cc.oulu.fi/~jarioksa/softhelp/vegan.html ADE4 http://pbil.univ-lyon1.fr/ADE-4/ADE-4.html Spatstat http://www.maths.uwa.edu.au/~adrian/spatstat.html geoR http://www.est.ufpr.br/geoR/ grasp-R http://www.fivaz.ch/grasper/index.html nlme packages.r-project.org/nlme/...

Hi! Is there a way to get biplot and identify to work togheter. Having the output of prcomp I would like to draw a biplot that. Instead of plotting the sample (row-names) names plots some "pch" symbols. (thats easy with xlabs) But now I would like to add using identify the names to only some of the points. I have noticed that both biplot.prcomp and biplot.default does a lot of

Hi everyone, I'd like to project two pcas onto one device window. I plot my first PCA: biplot(prcomp(t(cerebdevmat)), var.axes=FALSE, cex=c(1,.1), pc.biplot=TRUE) Now I'd like to project the features of another PCA onto this graph. Any suggestions? I know this is easily done in MatLab but haven't figured it out in R. Thanks, Tanya [[alternative HTML version deleted]]

Hi Some of our smaller Central London clients (5 to 25 terminals), who use the NetWare & GroupWise software from Novell Small Business Suite 6, are becoming increasingly concerned about the possibility of their offices becoming inaccessible for a prolonged period in the event of a terrorist attack. We've been asked to provide a low cost solution consisting of replicated offsite servers to

Hi I have a large dataset, containing a wide range of binary variables. I would like first of all to compute a jaccard matrix, then do a PCA on this matrix, so that I finally can do a hierarchical clustering on the principal components. My problem is, that I don't know how to compute the jaccard dissimilarity matrix in R? Which package to use, and so on... Can anybody help me? Alternatively

I'm trying to use the pictex driver for bargraphs, and the shading isn't showing up. Is there any way to get some sort of shading in the plots? A hatch or stipple would be fine, too; just some way to differentiate the bars. The postscript driver won't do, since I'm trying to embed this in a LaTeX document which I'll use pdflatex on and \includegraphics for pdftex doesn't

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....88333333, 0.88888889, 0.89444444, 0.94444444, 0.95555556) # What I want to do is a log-likelihood model selection process where i check if a Gaussian fit or a skewed unimodal fit (among others) is better. # The first thing I do is use this function written by Oksanen http://cc.oulu.fi/~jarioksa/softhelp/hof3.pdf HOF.start<-function(y,x,model=5) { if (model >=4) { k<-glm(y ~ x + I(x^2),family=binomial) k1<-k$coefficients[1] k2<-k$coefficients[2] k3<-k$coefficients[3] u<-(-k2/2/k3) h<-plogis(k1-k2^2/4/k3) r<-log(1/h*(-2*h+2*sqrt(h))/2) b<-5.07-0.227*k3...

Dr. Stevens, Hi, my name is Trey Scott, and I'm a grad student of Brian McCarthy's. He referred me to you because of your expertise in handling complex R problems. We were hoping you could help us solve a nagging problem that is prohibiting me from producing graphicl output. Here is a simple mock-up of the matrix I'm using a b c d e f 1i 1 4