similar to: multiple plots for data sets of inconsistent size

Hello all, I have performed PCA on stacked wind vector data for 20 different spatial locations. In this case I therefore am in effect working out a PCA for 40 different stations (2 paired pieces of information [ie u and v vector information] for each station), so have 40 PCs. In my previous PCA (for none vector data) i have plotted the PC loadings onto a map of the area of concern, and would

Hello, I submitted this bug report to r-core and got a rejection saying I should post to r-help. This is my first time ever submitting a bug report, so forgive me if I'm using some wrong format. So, here's my bug report: Component: Graphics OS: Mac OS 10.5.8, X11 XQuartz 2.5.0 Summary: In the symbols function of the graphics package, scaling of the y-axis is wrong, causing symbols

I ran into a problem with "subset" while working at home that I am not sure is a bug or not. I defined a custom function to take a data frame of tree positions, sizes, and types (containing the columns TRT, COMP, PLOT, X, Y, DBH and CON) and wanted to make a stem map of the plot using different symbols and colors to represent the different types of tree stems. I copied a bit of the

Hi all, I use the symbol functions to draw circles. But the argument lty does not work on windows but works correctly on my macbook: x <- -4:4 y <- -4:4 plot(x,y,type="n") symbols(0, 0, add = TRUE, circles = 1, inches = 1, fg="black", lty="solid") symbols(0, 0, add = TRUE, circles = 1, inches = 2, fg="black", lty="dashed") The

Hi, I was wondering if there is a way of plotting smoothed contours of PCA loadings onto a map. At the moment I have the loadings plotted as positive/negative (red/blue) scaled circles centred around where the physical stations are on a map - but I was wondering if there is a nicer way of plotting this data, perhaps as contours of "regions of influence" or somesuch? Any suggestions

Hi, I am applying the following code to map pca loadings onto a 3d grid, my problem is this - the output only plots the spheres in the requested color (in this case "red") for the first argument. The sphere from the second argument appear as flat dark circles. Also the text3d() command only seems to work for a couple of the positions, with no text added in most cases. Could anyone offer

Is there a grayscale equivalent to alpha levels in rgb? Example: I have the following to make red transparent circles overlap with previously plotted blue symbols. symbols(x=sites$long,y=sites$lat,circles=log(sites$prop.nem +1),add=T,inches=F,bg=rgb(red=1,green=0,blue=0, alpha=0.5),fg=rgb(red=1,green=0,blue=0, alpha=0.5)) I'm having a hard time coming up with a grayscale equivalent.

I'm new to R and i'm having some trouble with a bubble chart. Basically I have 3 series (a,b,c), but the third one is a binnary variable (assumes only 0 or 1 to the entire data). How can I use these binnary information to make 2 different colours in a bubble chart?. I.e., I'm using this code: symbols(inv$a, inv$b, circles=radius, inches=0.35, fg="white", bg="red",

I'm trying to create a fairly basic map using R. What i want to get is the map of the country with circles representing a count of students in each state. What I've done so far is as following - map("state") symbols(data1$count,circles=log(data1$count)*3,fg=col,bg=col,add=T,inches=F) this gives me the map of the country, but one that's not populated by my counts. Does

Hi, I am trying to draw a dotted circle by using symbols command: symbols(0, 0, circles = 1, inches = FALSE, fg = 'gray', lty=2) But it gives me a solid line. I was just wondering whether am I making a mistake? Ved [[alternative HTML version deleted]]

Hi all, I'm an R newbie, I did this script to create a scatterplot using the "tree" matrix from "datasets" package: library('datasets') with(trees, { plot(Height, Volume, pch=3, xlab="Height", ylab="Volume") symbols(Height, Volume, circles=Girth/12, fg="grey", inches=FALSE, add=FALSE) } ) I'd like to use the column Named

I have created a bubble plot in R using the following formula: symbols(Data$Day.Number,Data$Team,circles=Data$Total.amount, inches=0.5, fg="white",bg="red",xlab="Day Number",ylab="Team") The data set is called Data, and I have the columns Day.Number, Team and Total.amount. The data is plotting fine, but where my y axis should have the names of each team,

Hi all, I am attempting to run PCA on a matrix (nrow=66, ncol=84) using 'prcomp' (stats package). My data (referred to as 'Q' in the code below) are separate river streamflow gaging stations (columns) and peak instantaneous discharge (rows). I am attempting to use PCA to identify regions of that vary together. I am entering the following command:

Dear list, I'm trying to get two lattice plots aligned on a page. They should share a common x axis, hence the need for perfect alignment, but the data is taken from unrelated, separate sources (it is therefore inappropriate to combine them and use facetting to get an automatic layout: the legend and y axis need to be different). I can get the panels to be of the same size, but

Dear list, I need to align two plots on top of each other for comparison (they only have the x-axis in common). When the y-labels have a different extent, I cannot find a way to align the x-axes, as illustrated below, > library(grid) > library(lattice) > x <- seq(0, 10, length=100) > y <- sin(x) > y2 <- 10*sin(x) > f <- rep(c("1", "2"),

Dear all, I'm using R 2.8.1 under Vista. I programmed a Simulation with the code enclosed at the end of the eMail. After the simulation I want to analyse the columns of the single simulation-runs, i.e. e.g. Simulation[[1]][,1] sth. like that but I cannot address these columns... Can anybody please help? Best, Thomas ############################ CODE ############################

Hello, Please take a look at the attached plot and let me know if this is normal. The circle has radio I am using R 2.9.2 inside OS X Leopard. The plot was generated with: png('bizarre_circle.png') plot(c(-5,0,0,5), c(0,5,-5,0)) symbols(0,0, circles=c(sqrt(25)), inches=FALSE, add=TRUE) dev.off() If I resize the x11's plot window I can manage to make the circle pass through all the

In comparing the results of princomp and prcomp I find: 1. The reported standard deviations are similar but about 1% from each other, which seems well above round-off error. 2. princomp returns what I understand are variances and cumulative variances accounted for by each principal component which are all equal. "SS loadings" is always 1. 3. Same happens

I start a clean session of R 1.9.1 on Windows and I run the following code: > library(MASS) > data(painters) > pca.painters <- princomp(painters[ ,1:4]) > loadings(pca.painters) Loadings: Comp.1 Comp.2 Comp.3 Comp.4 Composition 0.484 -0.376 0.784 -0.101 Drawing 0.424 0.187 -0.280 -0.841 Colour -0.381 -0.845 -0.211 -0.310 Expression 0.664 -0.330 -0.513

hi, I have two questions: #first (SPSS vs. R): I just compared the output of different PCA routines in R (pca, prcomp, princomp) with results from SPSS. the loadings of the variables differ vastly! in SPSS the variables load constantly higher than in R. I made sure that both progr. use the correlation matrix as basis. I found the same problem with rotated values (varimax rotation and rtex=T