similar to: colored PCA biplot

x=rmvnorm(2000, rep(0, 6), diag(c(5, rep(1,5)))) x=scale(x, center=T, scale=F) pc <- princomp(x) biplot(pc) There are a bunch of red arrows plotted, what do they mean? I knew that the first arrow labelled with "Var1" should be pointing the most varying direction of the data-set (if we think them as 2000 data points, each being a vector of size 6). I also read from

Hi everyone, I am doing PCA with labdsv package. I was trying to create a biplot graphs in order to observe arrows related to my variables. However when I run the script for this graph, the console just keep saying: *Error in nrow(y) : element 1 is empty; the part of the args list of 'dim' being evaluated was: (x)* could please someone tell me what this means? what i am doing

Hi is there a way to plot only the loadings in a biplot (with the nice arrows), and to skip the scores? thanks christoph

[was sent a wrong R-help address; manually resent by MM] Hello I'am using the 'biplot' and 'biplot.pincomp' functions of the 'mva' package for my studies. The biplot represents both the observations and the variables of a matrix of multivariate data on the same plot. The observations are represented by their numbers (the line of the data matrix), but I would need to

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

I'm attempting to modify how biplot draws its red vectors (among other things). This is how I've started: Biplot <- function(xx, comps = c(1, 2), cex = c(.6, .4)) { ## Purpose: Makes a biplot with princomp() object to not show arrows ## ---------------------------------------------------------------------- ## Arguments: xx is an object made using princomp() ##

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

Dear R help I am having difficulty doing a biplot of the first two factors of a factor analysis. I presume it is because the values in factor 2 for Milk and NUTS are not displayed in the component loadings. Loadings: Factor1 Factor2 RedMeat 0.561 -0.112 WhiteMeat 0.593 -0.432 Eggs 0.839 -0.195 Milk 0.679 Fish 0.300 0.951 Cereals -0.902 -0.267

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]]

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

Dear list, I want to perform a biplot, using customized titels for the x and y axis. Setting xlab="" and ylab="" resulted in an error, e.g.: > data(USArrests) > biplot(princomp(USArrests),xlab="",ylab="") Error in biplot.default(t(t(scores[, choices])/lam), t(t(x$loadings[, : length of dimnames[1] not equal to array extent > How do I

Hi Listers, I am trying to reflect a PCA biplot in the x-axis (i.e. PC1) but am not having much success. In theory I believe all I need to do is multiply the site and species scores for the PC1 by -1, which would effectively flip the biplot. I am creating a blank plot using the plot command and accessing the results from a call to rda. I then use the calls to scores to obtain separate site and

Hi R-community, I am doing a PCA and I need plots for different combinations of axes (e.g., PC1 vs PC3, and PC2 vs PC3) with the arrows indicating the loadings of each variables. What I need is exactly what I get using biplot (pca.object) but for other axes. I have plotted PC2 and 3 using the scores of the cases, but I don't get the arrows proportional to the loadings of each variables on

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

Dear all I'm unable to find an example of extracting the rotated scores of a principal components analysis. I can do this easily for the un-rotated version. data(mtcars) .PC <- princomp(~am+carb+cyl+disp+drat+gear+hp+mpg, cor=TRUE, data=mtcars) unclass(loadings(.PC)) # component loadings summary(.PC) # proportions of variance mtcars$PC1 <- .PC$scores[,1] # extract un-rotated scores of

Hi all, I am using the vegan package to run a prcincipal components analysis on forest structural variables (tree density, basal area, average height, regeneration density) in R. However, I could not find out how to extract factor loadings (correlations of each variable with each pca axis), as is straightforwar in princomp. Do anyone know how to do that? Moreover, do anyone knows

I am doing a principle component analysis on a dataset with a lot of different variables and have constructed a biplot of the data. Unfortunately, as can be seen on the attached image, the biplot is very messy, cluttered, and hard to read. I have performed a few modifications including outlier removal from a few of the variables, which has made the plot better, however it still is too cluttered

Dear colleagues, I a m a beginner with R and I would like to add labels (i.e. the variable names) on a pca loading plot to determine the most relevant variables. Could you please tell me the way to do this kind of stuff. The command I use to draw the pca loading plot is the following : Plot(molprop.pc$loading[,1] ~ molprop.pc$loading[,2]) Thanks for your help Fred Ooms

I have a decent sized matrix (36 x 11,000) that I have preformed a PCA on with prcomp(), but due to the large number of variables I can't plot the result with biplot(). How else can I plot the PCA output? I tried posting this before, but got no responses so I'm trying again. Surely this is a common problem, but I can't find a solution with google? The University of Dundee is a

Hi, I have a problem with making PCA plots that are readable. I would like to set different sympols instead of the numbers of my samples or their names, that I get plotted (xlabs). How is this possible? With points, i don´t seem to get the right data plotted onto the PCA plot, as I do not quite understand from where it is taken. I dont know how to plot the correct columns of the prcomp