similar to: Colour points in plot according to third variable

Hi, I am trying to find out how to interpret the summary output from a neg bin GLM? I have 3 significant variables and I can see whether they have a positive or negative effect, but I can't work out how to calculate the magnitude of the effect on the mean of the dependent variable. I used a log link function so I think I might have to use the antilogs of the coefficients but I have no idea

Hi, I receive the following warning message when I run a poisson GLM in R: "glm.fit: fitted rates numerically 0 occurred" The model summary is shown below. The variable 'Species' consists of counts of different species ranging from 0 to 4. I suspect this may have something to do with the warning message but I'm not sure. Can anybody help? Thank you! Anna Call:

Dear R-users, Does anyone knows how I can order my serie of boxplots from lowest to highest median (which is much better for visualization purposes). thanks in advance, willem [[alternative HTML version deleted]]

Hello, I would like to plot my data in a fashion similar to a boxplot, but plot the true data points without a box, just overlay lines of the summary generated by the boxplot. I have less than 10 observations within each group, so I think showing the actual data would be more effective than the box of the boxplot. I have been unable to find a way to do this. Here is example data: >

I think this was asked recently but I can't find the item. Is it possible to find the colour at a point on a graphics page? I want to estimate the area of a complex shape by colouring it then random sampling from an enclosing box ... Richard Rowe Richard Rowe Senior Lecturer Department of Zoology and Tropical Ecology, James Cook University Townsville, Queensland 4811, Australia fax (61)7

Hi, after reading about it in the forum, I tried the Tinn-R editor (in WinXP) running R 2.5.0... nice one! However, I am trying to change the syntax-colouring from the default to my own preferences... and I can do that, but my options don't appear to be saved and get lost when I close Tinn-R. I've searched help menus, and google... and I can't find how to make sure my

HI lily, for the colouring of individual points you can set the colour aesthetic. The ID is numeric so ggplot applies a colour scale. If we cast ID to a factor we get the appropriate colouring. test_df <- data.frame(ID = 1:20, v1 = rnorm(20), v2 = rnorm(20), v3 = rnorm(20)) ggplot(data=test_df, aes(x=v1,y=v2, colour = as.factor(ID))) + geom_point()+ theme_bw()+ xlab('Variable 1')+

Inspired by colouring the dots of box-whisker plots I am trying to also fill the boxes (rectangles) with different colours. This seems not to work as I expected. Looking at the help page of panel.bwplot it says: 'fill - color to fill the boxplot'. Obviously it is only intended to fill all boxes with only one colour? Nevertheless the following example shows, that 'fill' from

I've been thinking hard about generating colour schemes for data. There's quite a bit of existing code scattered in various packages for playing with colours and colour palettes, but I can't find the sort of thing I'm after for applying colours to data... To my mind a colour scheme is a mapping from data values to colours. There's a multitude of such mappings depending on the

I require some help in debugging this code  library(neuralnet) ir<-read.table(file="iris_data.txt",header=TRUE,row.names=NULL) ir1 <- data.frame(ir[1:100,2:6]) ir2 <- data.frame(ifelse(ir1$Species=="setosa",1,ifelse(ir1$Species=="versicolor",0,""))) colnames(ir2)<-("Output") ir3 <- data.frame(rbind(ir1[1:4],ir2))

I have a data set where I want the correlations between 2 variables conditional on a students grade level. This code works just fine. by(tmp[,c('mtsc07', 'DCBASmathscoreSPRING')], tmp$Grade, cor, use='complete', method='pearson') However, this generates an error by(tmp[,c('mtsc07', 'DCBASmathscoreSPRING')], tmp$Grade, cor, use='complete',

Hi list, One of my co-workers found this problem with 'cor' in his code and I confirm it too (see below). He's using R 2.2.1 under Win 2K and I'm using R 2.3.0 under Win XP. =========================================== > R.Version() $platform [1] "i386-pc-mingw32" $arch [1] "i386" $os [1] "mingw32" $system [1] "i386, mingw32" $status

Dear all This may be obvious, but I cannot get it working. I'm trying to subset & sort a data frame in one go. x <- iris x$Species1 <- as.character(x$Species) ##subsetting alone works fine with(x, x[Sepal.Length==6.7,]) ##sorting alone works fine with(x, x[order(Sepal.Length, rev(sort(Species1))),]) ##gets subsetted, but not sorted as expected with(x, x[(Sepal.Length==6.7) &

I am making a battery of levelplots and wireframes for several fitted models. I wrote a function that takes the fitted model object as the sole argument and produces these plots. Various strange behavior ensued, but I have identified one very concrete issue (illustrated below): when my figure-drawing function includes the addition of points/lines to trellis plots, some of the

Hello, I'll use part of the iris dataset for an example of what I want to do. > data(iris) > iris<-iris[1:10,1:4] > iris Sepal.Length Sepal.Width Petal.Length Petal.Width 1 5.1 3.5 1.4 0.2 2 4.9 3.0 1.4 0.2 3 4.7 3.2 1.3 0.2 4 4.6 3.1 1.5

I would like to create an xyplot with varying y-axis limits and horizontal labels at the y-axis tickmarks. The following does not seem to work, although I think it should, going by the documentation for par. R version 2.5.1, Windows XP Prof. Thanks for a clue. Andreas Krause library(lattice) # axis labels for y-axis are horizontal xyplot(Sepal.Length ~ Sepal.Width | Species, data=iris) #

Dear all When using Sweave, I'm always hitting the same bump: I want to group repetitive calls in a function, but I want both the results and the function calls in the printed output. Let me explain myself. Consider the following computation in an Sweave document: summary(iris[,1:2]) cor(iris[,1:2]) When using these two calls directly, I obtain the following output: > summary(iris[,1:2])

Greetings R experts, I'm having some difficulty recovering lda objects that I've saved within sublists using the save.image() function. I am running a script that exports a variety of different information as a list, included within that list is an lda object. I then take that list and create a list of that with all the different replications I've run. Unfortunately I've been

Hi! The kernlab function kpca() mentions that new observations can be transformed by using predict. Theres also an example in the documentation, but as you can see i am getting an error there (As i do with my own data). I'm not sure whats wrong at the moment. I haven't any predict functions written by myself in the workspace either. I've tested it with using the matrix version and the

I have a bivariate plot of axis2 against axis1 (data below). I would like to use different size, type and color for points in the plot for the point coming from different region. For some reasons, I cannot get it done. Below is my code. col <- rep(c("blue", "red", "darkgreen"), c(16, 16, 16)) ## Choose different size of points cex <- rep(c(1, 1.2, 1), c(16, 16,