similar to: Solved: Help plotting some data

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

Which is the parameter that is used to decrease the size of ylabs plotted in biplot? I tried playing with cex and cex.lab I am not getting it right pc <- princomp(USArrests) biplot(pc, xlabs = rep("", nrow(USArrests)),ylabs=(colnames(USArrests))) Thanks../Murli [[alternative HTML version deleted]]

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

Dear R-help list, I'd like to create visualize the clustering of a dataset with a dendrogram. I'm using the following script: data = read.table("data.csv", header=T, sep=";") require(cluster) res = as.dendrogram(agnes(data)) chlab <- function(n) { if(is.leaf(n)) { att <- attributes(n) labx <- data$category1[att$label] lab_color <- ifelse(labx ==

Hello all, I just started in on R today. I am at the point where I am trying to distinguish different groups of data (hydrochemical data) in biplot. I search and found a post about converting the sample number in biplot to a symbol like x or + "> temp <- matrix(runif(50), nrow=10) > temp.pca <- princomp(temp) > biplot(temp.pca, xlabs=c("A", "A",

I'd like to do some plots of historical event data on a reverse log scale, started, say at the year 2000 and going backwards in time, with tick marks spaced according to log(2000-year). For example, see: http://euclid.psych.yorku.ca/SCS/Gallery/images/log-timeline.gif As an example, I'd like to create a density plot of such data with the horizontal axis reverse-logged, a

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! Is there a way to get biplot and identify to work togheter. Having the output of prcomp I would like to draw a biplot that. Instead of plotting the sample (row-names) names plots some "pch" symbols. (thats easy with xlabs) But now I would like to add using identify the names to only some of the points. I have noticed that both biplot.prcomp and biplot.default does a lot of

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

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'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

Hello, I am trying to draw the biplot of a PCA, but I would like to use another variable of my initial data frame than my "row.names" to assign labels to the points. A part of my R file follows ; "m" is my initial data frame, which has the variable "code" as row.names, and another variable "name" that I'd like to use as labels for the points. >

Hi all, i am looking to built a simple example of a very basic propensity score adjustment, just using the estimated propensity scores as inverse probability weights (respectively 1-estimated weights for the non-treated). As far as i understood, MLE predictions of a logit model can directly be used as to estimates of the propensity score. I already considered the twang package and the

termplot() does not carry subsetting over to carriers that are in the environment but not in the data frame. This generates a "subscript out of bounds" error. > data(ToothGrowth) > logdose <- log(ToothGrowth$dose) > tooth.lm <- lm(len ~ logdose, data=ToothGrowth) > termplot(tooth.lm) ## Works fine > toothVC2.lm <- lm(len ~ poly(dose,2),

Dear all here is my data called "rglp" structure(list(vzorek = structure(1:17, .Label = c("179/1/1", "179/2/1", "180/1", "181/1", "182/1", "183/1", "184/1", "185/1", "186/1", "187/1", "188/1", "189/1", "190/1", "191/1", "192/1",

Dear guRus, after solving serveral other probs with boxplots, my ylabs do not appear correct. They area cut off. I guess I have to change the letf and right margins, but I do not know how. Here is an example: http://frosch.homelinux.org/tmp/plot.png Thats the code i tried to use: <R-code> oldpar <- par() # changing the margins par(mar=c(4.1,5.1,4.1,5.1) +0.1) P <- boxplot(bs.s ~

I have been trying to specify a different color palette to the image method in plot.Design. My model has crossed two rcs() arguments and one two-level gender argument. The goal which appears to have been mostly achieved is to produce separate bivariate plots for men and women The call to plot does produce a level plot but it appears only with the default color palette despite various

Dear R-helpers, The vectors in my biplot are completely obscured by the ~1400 labels R is printing on my biplot. I don't really care about the labels. How can I make the biplot without the annoying labels? See attached, if that helps you see my problem. Many thanks, Mark Na

I like the functionality provided by outer=TRUE, but when it comes time to place separate xlabs or ylabs, I always end up 'eyeballing' it on a case-by-case basis. For example, ##begin example require(lattice) cars.lo <- loess(dist ~ speed, cars) print(xyplot(cars.lo$residuals+cars.lo$fitted~cars.lo$x, strip=FALSE, outer=TRUE, layout=c(1,2),

Hi All, I have been trying to get to plot my PCA legend outside of the PCA plot, but success still alludes me. Can you guys please advise how I can achieve this. I used locater() to obtain coordinates for below the Comp.1 axis. Using these coordinates the legend disappears. Below is the code for the PCA and legend. Thanks in advance for the help. Regards Tinus r.cols <-