similar to: plotting prcomp

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

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 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],

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

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

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 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 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)

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

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

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 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

Dear friends, I am beginning to use R software in my academic research and I'm having some problems regarding the use of PCA. I have a table with 24445 rows and 9 columns, and I used the function prcomp() to do the analysis. Working with an example?: x<-read.table("test.txt", header=T) row.names(x)<-x[,1] x<-x[,-1] require(stats) pca<-prcomp(x, scale=T) names(pca) ##

Hi, I have been using the prcomp function to perform PCA on my example microarray data, (stored in metric text files) which looks like this: 1a 1b 1c 1d 1e 1f ...................................................4r 4s 4t g1 1.2705 1.2766 ...........................................................2.0298 g2 0.1631

Hi all, I'm new to PCA in R, so this might be a basical thing, but I cannot find anything on the net about it. I need to make a PCA plot with two response variables (df$resp1 and df$resp2) against eight metabolites (df$met1, df$met2, ...) and I don't have a clue how to do... and I've only used the simplest PCAs before, like this: pcaObj=prcomp(t(df[idx, c(40:47)]))

Hi, I want to include a vector representing the sites - environmental data correlation in a PCA. I currently use prcomp (no scaling) to perform the PCA, and envfit to retrieve the coordinates of the environmental data vector. However, the vector length is different from the one obtained in CAnoco when performing a species - environmental biplot (scaling -2). How can I scale the vector in order to

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]]

If I perform PCA on the 'eurodist' data, should I get an accurate geographic layout of the cities with biplot? (barring inversions, i.e. their is no way to define north.. but you get the idea...) I have a complex distance matrix, and I am thinking about how to cluster it and how to visualize the quality of the resulting clusters. If I could 'see' the clusters in space I could

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.

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