similar to: 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

Dear forum, I need to create biplot graphic. I took a look at the code of the biplot.default function from the stats package and I found that the arrows for the variables are multiplied by a coefficient of 0.8 before plotting: ... if (var.axes) arrows(0, 0, y[, 1L] * 0.8, y[, 2L] * 0.8, col = col[2L], length = arrow.len) ... I have no idea why this is done. Could somebody

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'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

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

Dears, I've been learning biplot (Gabriel, 1971) and I found the function 'biplot', inside of the package 'stats', useful but, a bit limited. So, I'm thinking to start a colaborative package to enhance this methods to other multivariate methods. In this way, I would like to start it, making public a new function (biplot.pca, still in development, but running) that make

Dear R helpers, When producing a PCA biplot, vectors of environmental variables (as red arrows with labels) and scores of the observations (black labels (observation names)) are plotted by default. How can I change the graphical output? Let's say I would like that the scores are plottet only as symbols and not text. The only solution I found was this post in the help archive

I want to plot biplots. I have seen the function biplot, but there are some extra features I would like, that I do not know how to achieve. 1. My observations, and my variables, fall into groups. Is there a way to, say, plot the observations in several different colours, according to which group the observation falls into? Similarly with the variables? I am used to the lattice idiom, in which one

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

Hello, Something incredible (at least for me) has happen. Yesterday night I downloaded biplot.R to edit this function and add new features I wished. Namely I wanted to plot points belonging to different groups using different colors and symbols. I identified which part of the original code I had to modify. Then, I rename biplot by biplotes and executing biplotes(x), being x a princomp class

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

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 1.6.2 on a win 2k box. (I know I'm due for an upgrade.) I've used brute force to label a series of vectors, and I'm wondering if there's a better way to do this. I wanted to create a biplot of the 2nd & 3rd PCs, and did this: test <- edit(loadings(cv.prc.spr)) test.1 <- test[,1] test.2 <- test[,2] test.3 <- test[,3] x0 <- 0 y0 <- 0 i <-

Hi everybody, Excuse me for this silly question, but after searching the help archives I'm still unable to find my way to read the source code of the "biplot" function in R. I have installed the mvbutils package, and tried: > fixr(biplot) which only gives me: function (x, ...) UseMethod("biplot") with no further details.... I'd like to read the code to see if

Dear R-help fellows good afternoon. I am struggling in the attempt to impose some graphical conditions (changing point symbols, colors, etc) to biplot function (I am using it to visualize the results of princomp) but I can't apparently manage to change anything but the axis... and I have been browsing manuals and vignettes without finding any explicit suggestions on how to operate... Can

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

Dear all, I have a very large dataset (1712351 , 20) and would like to plot only the arrows that represent the contribution of each variables. On the sample below I woild like to plot only the explanatory variables (Murder, Assault..) and not the sites. prcomp(USArrests) # inappropriate prcomp(USArrests, scale = TRUE) prcomp(~ Murder + Assault + Rape, data = USArrests, scale = TRUE)

Hello everybody, I am afraid this might be a stupid question, but after scanning a little bit through the help archive and the internet, I didn't come up with an answer myself. I have done a principle component analysis on a data set, which yields the mean response of 14 olfactory neurons to 16 different odors. When plotting the result in a biplot, it nicely shows me the odors in

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]