similar to: PC biplot display

Hi, I am trying to understand how the biplot.prcomp is constructed so I can manipulate it to emphasise particular observations and reduce the number of variables shown. The prcomp model I have ran has cor=TRUE and scale=TRUE I have worked out from looking at str(prcomp.model) that... prcomp.model$x = the observations ploted in the biplot prcomp.model$rotation = the variables that form the

I'm using R for PCA and? factor analysis. I want to create biplots of varimax rotated factors that color-code points by their classification. My research is on streams that are urban and rural. So, I want to color code them by this classification. If you just do a biplot from prcomp or princomp, you cannot add this color. So, I have used some code developed by a graduate student in our

Hello, I'd like to reproduce the standard biplot with pc.biplot=TRUE using xyplot in lattice in order to assign different symbols to groupings of observations (similar to the example in fig. 11.2 on page 285 in DAAG). In order to reproduce the biplots I need to know how to scale the observations and variables. In ?biplot.princomp I found that the variables are scaled by 'lambda ^

I have 2 questions about the Biplot function: Both of the questions refer to the following type of graph, which is a biplot of a principal component analysis: biplot(prcomp(dataset)) 1. Does anyone know how to change the appearance of data points on the biplot? As it is currently, for this type of graph, the label for each data point shows up on the graph - does anyone know how to get rid

hey, im trying hard to display names (given in a seperate variable) instead of "case numbers" in a pca plot (by biplot of a prcomp output). somebody could help me with this? lukas

Dear all, I've been learning biplot (Gabriel, 1971) and some days ago I sent for this list a procedural function with invitation for a collaborative package. Jari Oksanen made some suggestions and I agree with all. So, I reworked the function under the object-oriented programming (OOP/S3). I think it is now a good frame for more resources. Below it is the function and a small script to

Hi everybody,   I am doing principal component analysis (PCA) using "prcomp' function. When i did "Biplot", i did not found interesting result and it is based on Principal component (PC) 1 vs PC2. Now, i want to see"Biplot" in combination of either PC1 vs PC3 or PC2 vs PC 3. I did not get the ideas. Does any one have ideas ? I am optimistic on getting some idea.

Is there an option to draw concentration ellipses in biplots ? It seems really nice to summarize large number of points of each group. Cheers../ Murli

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

Dear all, >From the documentation of biplot.prcomp: scale: The variables are scaled by 'lambda ^ scale' and the observations are scaled by 'lambda ^ (1-scale)' where 'lambda' are the singular values as computed by 'princomp'. >From the source code of prcomp: lam <- x$sdev[choices] n <- NROW(scores) lam <- lam * sqrt(n)

The script below successfully produces a biplot of the data but the 'site names' (rows) and the names of the 'response variables' (columns) are shown as simple numerals (rather than the column and row names). How might I 'enforce' the use of the row/column names used in the datafile (section of datafile shown below)? Can anyone help, please? Section of datafile sample a b

Hi, I recently uploaded a package called "calibrate" to CRAN. This package contains routines for the calibration of (oblique) axes in biplots and scatter plots. Documentation provides examples for ordinary scatter plots with additional axes, biplots from principal component analysis, correspondence analysis, canonical correlation analysis and redundancy analysis. Jan Graffelman --

I've tried a few things both with prcomp(), and rda() and its friends in vegan (including biplot.rda and ordiplot), but can't find a solution. I'd like to associate subsets of the points in a resulting biplot ("sites" in the rda object) with different plotting colors/text styles to emphasize certain sets of points. I can't figure out how to keep the arrows (for

My previous post about prcomp and princomp was done in some haste as I had long ago indicated to Kurt that I would try to have this ready for the June release, and it appeared that I would miss yet another release. I also need to get it out before it becomes hopelessly buried by other work. Brian Ripley kindly pointed out some errors, and also pointed out that I was suggesting replacing some

Hi all I have produced a biplot for a PCA (see attached pdf) that I ran however the names of the variables which are placed at the end of the arrows overlap and are thus unreadable. Similarly some of the numbered points overlap. I was wondering if there was a way to edit the biplot to move the label names and if not what the best alternative is. Thanks Anna pca<-biodata[,3:10]

Dear list, I'm trying to make a biplot, but instead of plotting the row number for each observation, plot a group factor. Example: prcomp(iris[,1:4]) -> PCA biplot(PCA) #this makes a nice biplot but with row names Instead of row numbers I want to plot iris[,5], which is a factor. I can do this: plot(PCA$x[,1], PCA$x[,2], type="n") text(PCA$x[,1], PCA$x[,2], labels=iris[,5],

Dear all here is my data called "rglp" structure(list(vzorek = structure(1:17, .Label = c("179/1/1", "179/2/1", "180/1", "181/1", "182/1", "183/1", "184/1", "185/1", "186/1", "187/1", "188/1", "189/1", "190/1", "191/1", "192/1",

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]]

>>>>> Ross Ihaka writes: > I have got a little side-tracked (from graphics) and am putting > together a little multivariate analysis library. This is just > intended to be a "core" library rather than anything exhaustive. > Mainly it is a matter of putting togther code which already exists at > StatLib. Here is my present list (only some of which is

Thanks Andris, Michael and Petr for your prompt and kind feedbacks. I will try generating my own biplot from low-level graph commands... I hope it will work. Best regards, Marco -- Marco Manca, MD University of Maastricht Faculty of Health, Medicine and Life Sciences (FHML) Cardiovascular Research Institute (CARIM) PO Box 616 6200 MD Maastricht E-mail: m.manca at path.unimaas.nl Office