similar to: data(eurodist) and PCA ??

The eurodist dataset (my favorite for mds) is malformed. Instead of a standard distance matrix, it's a data frame. The rownames have gotten 'bumped' to a new anonymous dimension "X". It's possible to fix the data, but it messes up a lot of example code out there. X Athens Barcelona Brussels Calais ... 1 Athens 0 3313 2963 3175 2 Barcelona

Hi, I am doing PCA on several columns of data in a data.frame. I am interested in particular rows of data which may have a particular combination of 'types' of column values (without any pre-conception of what they may be). I do the following... # My data table. allDat <- read.table("big_select_thresh_5", header=1) # Where some rows look like this... # PDB SUNID1

## i have one question anouth this package.. library(datasets) eurodist ## if i type this i get max distance between european cities > max(eurodist) [1] 4532 ## but i would like get something like this: 4532 Gilbratar - Anthens ## and another one.. ## if a live in barcelona and i would like travel in all cities ## how can i get sum of all distance to other cities... i try

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

Please consider the following PCA example; my.df <- data.frame(A=(x <- rnorm(100,mean=100, sd=10)), B=(y <- x + rnorm(100,mean=10, sd=10))) plot(my.df) my.pc <- prcomp(my.df, center=TRUE, scale=TRUE) biplot(my.pc) my.x <- (my.pc$x)[,1] my.y <- (my.pc$x)[,2] plot(my.x, my.y, type="n") text(my.x, my.y, labels=1:100) Clearly the plots have the same

Hello, supposing that I have two or three clear categories for my data, lets say pet preferece across fish, cat, dog. Lets say most people rate their preference as being mostly one of the categories. I want to do pca on the data to see three 'groups' of people, one group for fish, one for cat and one for dog. I would like to see the odd person who likes both or all three in the

On Sat, Apr 25, 2020 at 1:23 PM Joerg Roedel <joro at 8bytes.org> wrote: > > On Sat, Apr 25, 2020 at 12:47:31PM -0700, Andy Lutomirski wrote: > > I assume the race you mean is: > > > > #VC > > Immediate NMI before IST gets shifted > > #VC > > > > Kaboom. > > > > How are you dealing with this? Ultimately, I think that NMI will need

I was looking at the example on the manual page of plot.window, and noticed that it needs fixing - names(eurodist) should now be labels(eurodist): --- /home/rsb/topics/R-2.2.0/src/library/graphics/man/plot.window.Rd 2005-04-18 12:18:59.000000000 +0200 +++ plot.window.Rd 2005-10-11 21:08:57.000000000 +0200 @@ -48,6 +48,6 @@ ry <- range(y <- -loc[,2]) plot(x, y, type="n",

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 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]

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

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

[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

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

I use the following code to scan a (limited) parameter space of clustering strategies ... data <- read.table(... dataTranspose <- t(data) distMeth <- c("euclidean", "maximum", "manhattan", "canberra", "binary" ) clustMeth <- c("ward",

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'm trying to make my PCA (princomp) colored. In my csv excel sheet, I have the first column numbered according to the groupings I want to assign to the PCA. I've played around with trying to set this first column as the color vector, but haven't had any luck. Any suggestions? Thanks, Hillary [[alternative HTML version deleted]]

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 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 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.